Beam sensing method and device, communication equipment, storage medium and chip

Abstract

The invention relates to the technical field of communication, in particular to a beam sensing method and device, communication equipment, a storage medium and a chip. The beam sensing method comprises the following steps: acquiring a first beam feature set and a second beam feature set related to a current network type; and in response to the condition that at least one first parameter of the first beam feature set and at least one second parameter of the second beam feature set meet a preset condition, selecting the first beam feature set or the second beam feature set as an acquisition source of wireless channel state information, the first beam feature set is related to the at least one first parameter, and the second beam feature set is related to the at least one second parameter. The receiving state of the communication equipment can be improved, and the communication quality of the communication equipment can be improved.

Description

Technical Field

[0001] The present disclosure relates to the field of communication technologies, and in particular, to a beam sensing method, apparatus, communication device, storage medium, and chip. Background Art

[0002] With the development of communication technologies, beamforming, as a key technology in mid- to high-frequency broadband wireless communication systems, has been widely applied in cellular mobile communication systems including New Radio (NR, commonly known as 5G). Among them, beamforming technology can, for example, generate a beam by adjusting the parameters of the basic units of a phase array such that signals at certain angles obtain constructive interference while signals at other angles obtain destructive interference. Summary of the Invention

[0003] The present disclosure provides a beam sensing method, apparatus, communication device, storage medium, and chip to improve the receiving state of a communication device and enhance the communication quality of the communication device. The technical solution of the present disclosure is as follows:

[0004] According to a first aspect of an embodiment of the present disclosure, a beam sensing method is provided, including:

[0005] Obtaining a first beam feature set and a second beam feature set related to a current network mode;

[0006] In response to at least one first parameter of the first beam feature set and at least one second parameter of the second beam feature set satisfying a preset condition, selecting the first beam feature set or the second beam feature set as a source for obtaining wireless channel state information, where the first beam feature set is related to the at least one first parameter, and the second beam feature set is related to the at least one second parameter.

[0007] According to a second aspect of an embodiment of the present disclosure, a beam sensing apparatus is provided, including:

[0008] A set obtaining unit, configured to obtain a first beam feature set and a second beam feature set related to a current network mode;

[0009] A source determining unit, configured to, in response to at least one first parameter of the first beam feature set and at least one second parameter of the second beam feature set satisfying a preset condition, select the first beam feature set or the second beam feature set as a source for obtaining wireless channel state information, where the first beam feature set is related to the at least one first parameter, and the second beam feature set is related to the at least one second parameter.

[0010] According to a third aspect of the embodiments of the present disclosure, there is provided a communication device, including:

[0011] a processor;

[0012] a memory for storing executable instructions of the processor;

[0013] wherein the processor is configured to execute the instructions to implement the beam sensing method according to any one of the foregoing aspects.

[0014] According to a fourth aspect of the embodiments of the present disclosure, there is provided a storage medium, when the instructions in the storage medium are executed by a processor of a communication device, enabling the communication device to execute the beam sensing method according to any one of the foregoing aspects.

[0015] According to a fifth aspect of the embodiments of the present disclosure, there is provided a computer program product, including a computer program, where the computer program implements the method according to any one of the foregoing aspects when executed by a processor.

[0016] According to a sixth aspect of the embodiments of the present disclosure, there is provided a chip, including: a processor and an interface; the processor is used to read instructions to implement the method according to any one of the foregoing aspects.

[0017] The technical solutions provided by the embodiments of the present disclosure at least bring the following beneficial effects:

[0018] In some related embodiments, by obtaining a first beam feature set and a second beam feature set related to the current network mode; in response to at least one first parameter of the first beam feature set and at least one second parameter of the second beam feature set satisfying a preset condition, selecting the first beam feature set or the second beam feature set as the acquisition source of the wireless channel state information, where the first beam feature set is related to the at least one first parameter, and the second beam feature set is related to the at least one second parameter. Therefore, a beam sensing mechanism can be provided, which can determine the acquisition source corresponding to the wireless channel state information according to whether at least one first parameter of the first beam feature set and at least one second parameter of the second beam feature set satisfy the preset condition, can improve the accuracy of determining the acquisition source corresponding to the wireless channel state information, reduce the situation that the wireless channel state information determined by the mismatch between the wireless channel state information required for channel estimation and the acquisition source is inaccurate, can improve the accuracy of obtaining the wireless channel state information, can improve the receiving state of the communication device, and improve the communication quality of the communication device.

[0019] It should be understood that the above general description and the following detailed description are only exemplary and explanatory, and cannot limit the present disclosure. BRIEF DESCRIPTION OF THE DRAWINGS

[0020] The accompanying drawings herein are incorporated into the specification and constitute a part of this specification, showing embodiments consistent with the present disclosure, and are used together with the specification to explain the principles of the present disclosure, and do not constitute an undue limitation of the present disclosure.

[0021] Figure 1 is a flowchart of a beamforming method shown according to an exemplary embodiment;

[0022] Figure 2 is an example schematic diagram of a beamforming application shown according to an exemplary embodiment;

[0023] Figure 3 is an example schematic diagram of a beamforming application shown according to an exemplary embodiment;

[0024] Figure 4 is an example schematic diagram of a static wide beam of a time-frequency tracking reference signal (TRS) and a dynamic narrow beam of a physical downlink control channel (PDSCH) shown according to an exemplary embodiment;

[0025] Figure 5 is a flowchart of a beam sensing method shown according to an exemplary embodiment;

[0026] Figure 6 is a flowchart of a beam sensing method shown according to an exemplary embodiment;

[0027] Figure 7 is a flowchart of determining downlink beamforming support information shown according to an exemplary embodiment;

[0028] Figure 8a is an example schematic diagram of a neural network model shown according to an exemplary embodiment;

[0029] Figure 8b is an example schematic diagram of a neural network model shown according to an exemplary embodiment;

[0030] Figure 8c is an example schematic diagram of a neural network model shown according to an exemplary embodiment;

[0031] Figure 8d is an example schematic diagram of an implementation manner of a single decision tree shown according to an exemplary embodiment;

[0032] Figure 9 is an example schematic diagram of first time information and second time information shown according to an exemplary embodiment;

[0033] Figure 10 It is an exemplary schematic diagram showing a first time information and a second time information according to an exemplary embodiment;

[0034] Figure 11 It is a block diagram of a beam sensing device shown according to an exemplary embodiment;

[0035] Figure 12 It is a block diagram of a communication device shown according to an exemplary embodiment;

[0036] Figure 13 It is a block diagram of a chip shown according to an exemplary embodiment. Detailed implementation manners

[0037] In order to enable those of ordinary skill in the art to better understand the technical solutions of the present disclosure, the technical solutions in the embodiments of the present disclosure will be clearly and completely described below with reference to the accompanying drawings.

[0038] The embodiments of the present disclosure propose a beam sensing method, device, communication device, storage medium and chip. In some embodiments, the terms such as beam sensing method and information processing method, communication method can be replaced with each other, the terms such as beam sensing device and information processing device, communication device can be replaced with each other, and the terms such as information processing system, communication system can be replaced with each other.

[0039] The embodiments of the present disclosure are not exhaustive, but only schematic of some embodiments, and do not constitute a specific limitation on the protection scope of the present disclosure. Without contradiction, each step in an embodiment can be implemented as an independent embodiment, and the steps can be combined arbitrarily. For example, the solution after removing some steps in an embodiment can also be implemented as an independent embodiment, and the order of the steps in an embodiment can be arbitrarily exchanged. In addition, the optional implementation manners in an embodiment can be arbitrarily combined; moreover, the embodiments can be combined arbitrarily. For example, some or all of the steps of different embodiments can be arbitrarily combined, and an embodiment can be arbitrarily combined with the optional implementation manners of other embodiments.

[0040] In each embodiment of the present disclosure, if there is no special description and logical conflict, the terms and / or descriptions between the embodiments are consistent and can be cited from each other, and the technical features in different embodiments can be combined to form a new embodiment according to their inherent logical relationship.

[0041] The terms used in the embodiments of the present disclosure are only for the purpose of describing specific embodiments, and are not intended as a limitation on the present disclosure.

[0042] In the embodiments of the present disclosure, unless otherwise specified, elements expressed in the singular form, such as "a", "an", "the", "above", "said", "aforesaid", "this", etc., may mean "one and only one", or may also mean "one or more", "at least one", etc. For example, in the case of using articles such as "a", "an", "the" in English translation, the noun after the article can be understood as a singular expression or a plural expression.

[0043] In the embodiments of the present disclosure, "a plurality of" means two or more.

[0044] In some embodiments, terms such as "at least one of (at least one item, at least one)", "one or more", "a plurality of", "multiple", etc. may be used interchangeably.

[0045] In some embodiments, notations such as "at least one of A and B", "A and / or B", "in one case A, in another case B", "in response to one case A, in response to another case B", etc. may, depending on the circumstances, include the following technical solutions: In some embodiments, A (performing A independently of B); in some embodiments, B (performing B independently of A); in some embodiments, selecting to perform from A and B (A and B are selectively performed); in some embodiments, A and B (both A and B are performed). The same is true when there are more branches such as A, B, C, etc.

[0046] In some embodiments, notations such as "A or B" may, depending on the circumstances, include the following technical solutions: In some embodiments, A (performing A independently of B); in some embodiments, B (performing B independently of A); in some embodiments, selecting to perform from A and B (A and B are selectively performed). The same is true when there are more branches such as A, B, C, etc.

[0047] The prefix words such as "first", "second", etc. in the embodiments of the present disclosure are only used to distinguish different described objects, and do not constitute restrictions on the position, order, priority, quantity, content, etc. of the described objects. The statements of the described objects refer to the descriptions in the context of the claims or embodiments, and should not constitute redundant restrictions due to the use of prefix words. For example, if the described object is "field", the ordinal numbers before "field" in "first field" and "second field" do not limit the position or order between the "fields", and "first" and "second" do not limit whether the "fields" they modify are in the same message, nor do they limit the order of "first field" and "second field". For another example, if the described object is "level", the ordinal numbers before "level" in "first level" and "second level" do not limit the priority between the "levels". For another example, the quantity of the described object is not limited by the ordinal number and can be one or more. Taking "first device" as an example, the quantity of "device" can be one or more. In addition, the objects modified by different prefix words can be the same or different. For example, if the described object is "device", "first device" and "second device" can be the same device or different devices, and their types can be the same or different; for another example, if the described object is "information", "first information" and "second information" can be the same information or different information, and their content can be the same or different.

[0048] In some embodiments, "including A", "containing A", "for indicating A", "carrying A" can be interpreted as directly carrying A or indirectly indicating A.

[0049] In some embodiments, terms such as "in response to...", "in response to determining...", "in the case of...", "when...", "while...", "if...", "if... then..." can be substituted for each other.

[0050] In some embodiments, terms such as "greater than", "greater than or equal to", "not less than", "more than", "more than or equal to", "not less than", "higher than", "higher than or equal to", "not lower than", "above", etc. can be substituted for each other, and terms such as "less than", "less than or equal to", "not greater than", "less than", "less than or equal to", "not more than", "lower than", "lower than or equal to", "not higher than", "below", etc. can be substituted for each other.

[0051] In some embodiments, the apparatus and device can be interpreted as physical or virtual, and their names are not limited to those recorded in the embodiments. In some cases, they can also be understood as "equipment", "device", "circuit", "network element", "node", "function", "unit", "section", "system", "network", "chip", "chip system", "entity", "subject", etc.

[0052] In some embodiments, the "network" can be interpreted as the apparatuses included in the network. For example, access network devices, core network devices, etc.

[0053] In some embodiments, the "terminal" or "terminal device" can be referred to as "user equipment (UE)", "user terminal", "mobile station (MS)", "mobile terminal (MT)", subscriber station, mobile unit, subscriber unit, wireless unit, remote unit, mobile device, wireless device, wireless communication device, remote device, mobile subscriber station, access terminal, mobile terminal, wireless terminal, remote terminal, handset, user agent, mobile client, client, etc.

[0054] In some embodiments, data, information, etc. can be obtained after obtaining the consent of the user.

[0055] It should be noted that the terms "first", "second", etc. in the specification, claims and above-mentioned drawings of the present disclosure are used to distinguish similar objects, and do not necessarily describe a specific order or sequence. It should be understood that the data used in this way can be interchanged under appropriate circumstances, so that the embodiments of the present disclosure described herein can be implemented in an order other than those illustrated or described herein. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with the present disclosure. On the contrary, they are merely examples of devices and methods consistent with some aspects of the present disclosure as detailed in the appended claims.

[0056] According to some embodiments, Figure 1 is a flowchart of a beamforming method shown according to an exemplary embodiment, as Figure 1 shown, the beamforming technology adjusts the parameters of the basic units of the phase array, so that signals at certain angles obtain constructive interference, while signals at other angles obtain destructive interference, thereby generating a beam.

[0057] According to some embodiments, Figure 2 is an example schematic diagram of a beamforming application shown according to an exemplary embodiment, as Figure 2 shown, taking the application of the new radio (NR) 5G downlink direction as an example: the base station node B (gNodeB, gNB) uses a static beam method for transmitting the synchronization signal / PBCH (SSB for short) and the system information block (SIB for short) to ensure the service quality of all user equipments (UEs for short) within the coverage area.

[0058] According to some embodiments, Figure 3 is an example schematic diagram of a beamforming application shown according to an exemplary embodiment, as Figure 3 shown, taking the typical static beam design of the NR 5G first frequency range (Frequency Range 1, FR1 for short, commonly known as Sub-6G) as an example, full coverage is achieved through a static beam design of no more than 8. Among them, Figure 3 each of the 8 beams has two polarization directions, and the numbers before and after the " / " represent the two polarization direction numbers respectively.

[0059] According to some embodiments, when the communication device completes the reception of the SSB / SIB message, that is, initiates the random access process to complete the residence, the gNB continues to use Figure 3 the broadcast static beam shown.

[0060] Enter the Radio Resource Control (RRC) connected state. To achieve the best dedicated user service quality, the Physical Downlink Shared Channel (PDSCH) of the gNB uses dynamic beam transmission obtained based on Sounding Reference Signal (SRS) estimation and Precoding Matrix Indicator (PMI) reporting. In particular, when the SRS / PMI information is not timely or reliable, it will switch to a static beam to ensure the basic service quality of the user. Similarly, the Physical Downlink Control Channel (PDCCH) and Channel-State Information Reference Signal (CSI-RS) use dynamic beam / static beam transmission.

[0061] Furthermore, in the downlink direction, the beam information synchronization mechanism between the gNB and the User Equipment (UE) is called beam indication. The beam indication mechanism is completed based on the downlink signaling "Transmission Configuration Indication" (TCI). A group of TCI states is configured for the UE through high-layer signaling, and each TCI state corresponds to a group of reference signals, namely CSI-RS (Channel State Indication-Reference Signal, also known as Tracking RS, TRS) or SSB, indicating that the radio channel propagation state of the PDSCH or PDCCH is associated with the corresponding reference signal.

[0062] The way to characterize the corresponding association is to indicate the Quasi co-located (QCL) type, including:

[0063] -'typeA': {Doppler shift, Doppler spread, average delay, delay spread}

[0064] -'typeB': {Doppler shift, Doppler spread}

[0065] -'typeC': {Doppler shift, average delay}

[0066] -'typeD': {Spatial Rx parameter}

[0067] Taking 'typeA', which is the most common in the existing network deployment, as an example, the TCI status indication informs that the propagation status of the corresponding reference signal and the PDSCH radio channel is the same in terms of Doppler shift, Doppler spread, average delay, and delay spread. The UE can use the reference signal indicated by the relevant TCI for the radio channel estimation (Channel Estimation, abbreviated as CE) required for PDSCH / PDCCH reception of the radio channel state.

[0068] According to some embodiments, as a long-period static beam, the TRS cannot be exactly the same as the beam actually used by the physical downlink shared channel PDSCH in the time domain. And according to the protocol, the TRS cannot perform beamforming at the precoding resource block group (PRG) or subband granularity, so it cannot be exactly the same as the beam of the Parallel Data System (PDS) in the frequency domain. To cover the beam changes of the PDS as much as possible, the gNB generally configures a wider and more robust static beam for the TRS to use. As Figure 4 shown, the beam used by the gNB to send the TRS is a static wide beam and remains unchanged within a certain period of time, while the PDSCH signal beam is usually the narrowest beam that the gNB can achieve in the spatial domain and changes with the scheduling information (Rank, SU / MU-MIMO, etc.), UE transmission, or feedback status in the time domain.

[0069] Figure 4 In [figure], at Slot1, the gNB configures the service channel PDSCH in the single-user multiple-input multiple-output mode (abbreviated as SU-MIMO), the number of service flows is 3, and each flow is configured with the best dedicated dynamic beam at the current moment; at Slot2, the gNB configures the service channel PDSCH in the multi-user multiple-input multiple-output mode (abbreviated as MU-MIMO), the number of service flows is 2, and each flow is configured with the best dedicated dynamic beam at the current moment; however, at Slot1 and 2, the TRS corresponding to the TCI QCL 'typeA' status remains unchanged. Among them, for example, the non-ideal effect brought by guiding the dynamic narrow beam reception with the above static wide beam can be called the "wide-narrow beam" effect. The "wide-narrow beam" effect can be used to indicate, for example, the impact of the beam width of the transmitting and receiving antennas on signal transmission in wireless communication. The "wide-narrow beam" effect can include, for example, the situation where the static wide beam guides the reception of the dynamic narrow beam signal, resulting in the radio channel state information not meeting the requirements.

[0070] According to some embodiments, although the QCL 'type A' carried in the TCI state indication tells that the reference signals (TRS and / or SSB) of the static wide beam can provide the channel state information (CSI) available for PDSCH CE, and the CSI message can be, for example, Doppler shift, Doppler spread, average delay, delay spread, etc., in fact, due to the "wide and narrow beam" effect, the wireless channel state information is inaccurate, including:

[0071] Average delay spread. The static wide beam and the dynamic narrow beam experience different scattering and diffraction paths, and the static wide beam usually has a larger delay spread.

[0072] Maximum delay spread. The static wide beam and the dynamic narrow beam experience different scattering and diffraction paths, and the static wide beam usually has a larger maximum delay spread.

[0073] Doppler shift. The static wide beam and the dynamic narrow beam experience different scattering and diffraction paths, and the Doppler shifts are different.

[0074] Doppler spread. The static wide beam and the dynamic narrow beam experience different scattering and diffraction paths, and the Doppler spreads are different.

[0075] According to some embodiments, for the reception of 5G PDSCH / PDCCH service channels, for example, it can be default to strictly follow the QCL reference signals of the TCI state indication to obtain the wireless channel state information (Doppler shift, Doppler spread, average delay, delay spread); in view of the "wide and narrow beam" effect, the wireless channel state information obtained by the corresponding static wide beam cannot accurately match the actual performance of the dynamic narrow beam; generally, the farther the UE is from the base station coverage, the more significant the "wide and narrow beam" effect is, and the lower the accuracy of the wireless channel state information obtained by the corresponding static wide beam is compared with that of the dynamic narrow beam.

[0076] In some embodiments, for the reception of the 4th generation mobile communication technology (4G) PDSCH TM7 / 8 / 9 service channels, wireless channel state information (Doppler shift, Doppler spread, average delay, delay spread) can be obtained by default using Cell-Specific Reference Signals (CRS). Given the "wide and narrow beam" effect, the wireless channel state information obtained by the corresponding static wide beam cannot accurately match the actual performance of the dynamic narrow beam. Generally, the more distant a UE is from the base station within the coverage area, the more significant the "wide and narrow beam" effect becomes, and the lower the accuracy of the wireless channel state information obtained by the corresponding static wide beam compared to that of the dynamic narrow beam.

[0077] Figure 5 is a flowchart of a beam sensing method shown according to an exemplary embodiment, as Figure 5 shown, this beam sensing method can be used in broadband wireless communication systems that support beamforming, such as Long Term Evolution (LTE) systems, NR systems, 6-Generation (6G) systems, etc., and includes the following steps:

[0078] In step S11, obtain a first beam feature set and a second beam feature set related to the current network mode;

[0079] According to some embodiments, the network mode can be, for example, a communication standard and protocol used to indicate communication between different mobile communication networks. The current network mode in the embodiments of the present disclosure can be, for example, one of the network modes supported by the communication device, not limited to the currently used network mode in a narrow sense. The current network mode does not specifically refer to a certain fixed network mode. For example, when the specific network mode corresponding to the current network mode changes, the current network mode can also change accordingly. For example, when the execution time point of the beam sensing method changes, the current network mode can also change accordingly.

[0080] In some embodiments, the network mode can be the second-generation mobile communication technology specification (2G) network mode represented by the Global System for Mobile Communications (GSM), the third-generation mobile communication technology (3G) network mode represented by Wideband Code Division Multiple Access (WCDMA), the fourth-generation mobile communication technology (4G) network mode represented by Long Term Evolution (LTE), the 5G network mode represented by New Radio (NR), and so on.

[0081] In some embodiments, the first beam feature set may include, for example, a downlink static beam feature set. The first beam feature set may be a set including at least one beam feature. The embodiments of the present disclosure do not limit the quantity corresponding to the first beam feature set. The name of the first beam feature set is also not limited. The first beam feature set may also be referred to as at least one first beam feature, for example. Among them, the downlink static beam feature set may include, for example, at least one aggregation of downlink static beam features. The downlink static beam feature set does not specifically refer to a certain fixed set. For example, when the number of features included in the first beam feature set changes, the first beam feature set may also change accordingly. For example, when any beam feature in the first beam feature set changes, the first beam feature set may also change accordingly.

[0082] In some embodiments, the second beam feature set may include, for example, a downlink dynamic beam feature set. The second beam feature set may be a set including at least one beam feature. The embodiments of the present disclosure do not limit the quantity corresponding to the second beam feature set. The name of the second beam feature set is also not limited. It may also be at least one second beam feature, for example. Among them, the downlink dynamic beam feature set may include at least one downlink dynamic beam feature. The downlink dynamic beam feature set does not specifically refer to a certain fixed set. For example, when the number of features included in the second beam feature set changes, the second beam feature set may also change accordingly. For example, when any beam feature in the second beam feature set changes, the second beam feature set may also change accordingly.

[0083] According to some embodiments, when it is determined that dynamic beamforming is supported under the current network mode, a first beam feature set and a second beam feature set related to the current network mode can be obtained. The order of obtaining the first beam feature set and the second beam feature set is not limited. For example, the first beam feature set can be obtained first, and then the second beam feature set can be obtained. For another example, the second beam feature set can be obtained first, and then the first beam feature set can be obtained. For still another example, the first beam feature set and the second beam feature set can be obtained simultaneously.

[0084] According to some embodiments, when it is determined that dynamic beamforming is supported under the current network mode, a downlink static beam feature set and a downlink dynamic beam feature set related to the current network mode can be obtained. The order of obtaining the downlink static beam feature set and the downlink dynamic beam feature set is not specified. For example, the downlink static beam feature set and the downlink dynamic beam feature set can be obtained simultaneously, or the downlink static beam feature set and the downlink dynamic beam feature set can be obtained separately. For example, the downlink static beam feature set can be obtained first and then the downlink dynamic beam feature set can be obtained. Since both the downlink static beam feature set and the downlink dynamic beam feature set include at least one beam feature, one downlink static beam feature can be obtained first, then one downlink dynamic beam feature can be obtained, and then the downlink static beam feature can be obtained, etc. For example, the two sets can be obtained alternately or non-alternately. The specific process of obtaining the downlink static beam feature set and the downlink dynamic beam feature set corresponding to the current network mode in the embodiments of the present disclosure is not limited.

[0085] In step S12, in response to at least one first parameter of the first beam feature set and at least one second parameter of the second beam feature set satisfying a preset condition, the first beam feature set or the second beam feature set is selected as the acquisition source of the radio channel state information, where the first beam feature set is related to at least one first parameter, and the second beam feature set is related to at least one second parameter.

[0086] In some embodiments, the preset condition can be used to judge the condition of the acquisition source corresponding to the radio channel state information. Different preset conditions can correspond to different acquisition sources. The preset condition does not specifically refer to a certain fixed condition. For example, when a condition modification instruction for the preset condition is received, the preset condition can also change accordingly. For example, when a certain parameter in the preset condition changes, the preset condition can also change accordingly. The preset condition can include, for example, whether the RRC connection of the terminal has been reconfigured or released, whether the feature recognition result is the same as the preset result, whether the proportion of the feature recognition result being the preset result is greater than a proportion threshold, etc.

[0087] In some embodiments, wireless channel state information (CSI) can be used to describe the channel attributes of a communication link. Among them, when the acquisition time point of the wireless channel state information changes, the wireless channel state information can also change accordingly.

[0088] In some embodiments, the acquisition source is used to indicate the acquisition source of the wireless channel state information. The acquisition source includes but is not limited to a dynamic beam feature acquisition source, a static beam feature acquisition source, etc.

[0089] In some or related embodiments, by acquiring a first beam feature set and a second beam feature set related to the current network mode; in response to at least one first parameter of the first beam feature set and at least one second parameter of the second beam feature set satisfying a preset condition, selecting the first beam feature set or the second beam feature set as the acquisition source of the wireless channel state information, where the first beam feature set is related to at least one first parameter, and the second beam feature set is related to at least one second parameter. Therefore, a beam sensing mechanism can be provided, which can determine the acquisition source corresponding to the wireless channel state information according to whether at least one first parameter of the first beam feature set and at least one second parameter of the second beam feature set satisfy the preset condition, can improve the accuracy of determining the acquisition source corresponding to the wireless channel state information, reduce the situation that the wireless channel state information determined by the mismatch between the wireless channel state information required for channel estimation and the acquisition source is inaccurate, can improve the accuracy of acquiring the wireless channel state information, can improve the receiving state of the communication device, and improve the communication quality of the communication device.

[0090] Figure 6 is a flowchart of a beam sensing method shown according to an exemplary embodiment, as Figure 6 shown, this beam sensing method can be used in a wireless communication scenario, and includes the following steps:

[0091] In step S21, acquire the current resident cell of the communication device;

[0092] According to some embodiments, the current resident cell of the communication device can be acquired, for example. For example, the current resident cell acquired of the communication device can be cell A, for example. The communication device can also be referred to as a terminal, for example, and the present disclosure embodiment does not limit the name of the communication device.

[0093] In step S22, in response to the network mode information corresponding to the current resident cell and the downlink beamforming determination order, determine the downlink beamforming support information corresponding to the current network mode of the current resident cell;

[0094] According to some embodiments, the network mode information is used to indicate the type of network mode. For example, the network mode information corresponding to the currently resident cell may be the 4G network mode.

[0095] Among some embodiments, the downlink beamforming determination order may be, for example, the determination process of the preset downlink beamforming support information. For example, the communication device modifies the downlink beamforming determination order according to the received order adjustment instruction.

[0096] According to some embodiments, the downlink beamforming support information may be used to indicate whether downlink dynamic beamforming is supported.

[0097] According to some embodiments, Figure 7 is a flowchart of determining a downlink beamforming support information shown according to an exemplary embodiment, as Figure 7 shown, the method includes:

[0098] According to some embodiments, in response to the network mode information corresponding to the currently resident cell and the downlink beamforming determination order, determining the downlink beamforming support information corresponding to the current network mode of the currently resident cell includes:

[0099] Obtaining the network mode information corresponding to the currently resident cell;

[0100] In response to the network mode information corresponding to the currently resident cell being the first network mode, determining that the communication device is in the radio resource control connected state (RRC_CONNECTED);

[0101] In response to the dedicated configuration signaling indicating that the communication device is in the preset transmission mode, obtaining the first scenario information corresponding to the currently resident cell;

[0102] In response to the first scenario information being the preset scenario information, determining that the downlink beamforming support information corresponding to the first network mode is that the first network mode supports downlink dynamic beamforming.

[0103] According to some embodiments, in response to the network mode information corresponding to the currently resident cell and the downlink beamforming determination order, determining the downlink beamforming support information corresponding to the current network mode of the currently resident cell includes:

[0104] Obtaining the network mode information corresponding to the currently resident cell;

[0105] In response to the network mode information corresponding to the currently resident cell being the first network mode, determining that the communication device is in the radio resource control connected state;

[0106] In response to a dedicated configuration signaling indicating that the communication device is not in a preset transmission mode, or the first scenario information is not preset scenario information, it is determined that the downlink beamforming support information corresponding to the first network mode is that the first network mode does not support downlink dynamic beamforming. Therefore, when in the first network mode, the downlink beamforming support information can be determined according to the dedicated configuration signaling and the first scenario information, which can improve the accuracy of determining the downlink beamforming support information and the accuracy of determining the acquisition source.

[0107] In some embodiments, the first network mode can be, for example, a 4G network mode.

[0108] According to some embodiments, the preset transmission mode can be, for example, at least one of TM7, TM8, and TM9. For example, when the dedicated configuration signaling indicates that the communication device is in TM7, the first scenario information corresponding to the currently camped cell can be obtained.

[0109] In some embodiments, the first scenario information can be used to indicate the scenario information corresponding to the currently camped cell. The first scenario information does not specifically refer to a certain fixed information. Among them, for example, a scenario recognition method can be used to obtain the first scenario information. The embodiments of the present disclosure do not limit this.

[0110] According to some embodiments, the preset scenario information can be, for example, pre-determined scenario information. The preset scenario information can be, for example, high-speed rail scenario information or subway scenario information. For example, when the network mode information corresponding to the currently camped cell is a 4G network mode, it is determined that the communication device is in the radio resource control connected state (RRC_CONNECTED). When the dedicated configuration signaling indicates that the communication device is in TM7 and the first scenario information corresponding to the currently camped cell is high-speed rail scenario, it is determined that the downlink beamforming support information corresponding to the 4G network mode supports downlink dynamic beamforming.

[0111] When the network mode information corresponding to the currently camped cell is a 4G network mode, it is determined that the communication device is in the radio resource control connected state (RRC_CONNECTED). When the dedicated configuration signaling indicates that the communication device is not in the preset transmission mode, it is determined that the downlink beamforming support information corresponding to the 4G network mode does not support downlink dynamic beamforming.

[0112] When the network mode information corresponding to the currently camped cell is a 4G network mode, it is determined that the communication device is in the radio resource control connected state (RRC_CONNECTED). When the dedicated configuration signaling indicates that the communication device is in the preset transmission mode and the first scenario information corresponding to the currently camped cell is not the preset scenario information, it is determined that the downlink beamforming support information corresponding to the 4G network mode does not support downlink dynamic beamforming.

[0113] According to some embodiments, the method further includes:

[0114] In response to a radio resource control (RRC) signaling reconfiguration occurring in the radio resource control connected state, re-determine the downlink beamforming support information corresponding to the current network mode of the current resident cell. Among them, re-determining the downlink beamforming support information corresponding to the current network mode of the current resident cell is applicable to the case where the current network mode is the first network mode or the second network mode. The embodiments of the present disclosure do not limit this. Therefore, the downlink beamforming support information can be re-determined when an RRC signaling reconfiguration occurs, improving the accuracy of determining the downlink beamforming support information and the accuracy of determining the acquisition source.

[0115] According to some embodiments, in the case where an RRC signaling reconfiguration occurs in the radio resource control connected state, it is possible to determine whether the communication device is in the radio resource control connected state, and in the case of determining that the communication device is in the radio resource control connected state, re-determine the downlink beamforming support information corresponding to the current network mode of the current resident cell according to the dedicated configuration signaling and the first scenario information.

[0116] According to some embodiments, in response to the network mode information corresponding to the current resident cell and the downlink beamforming determination sequence, determining the downlink beamforming support information corresponding to the current network mode of the current resident cell includes:

[0117] In response to the network mode information corresponding to the current resident cell not being the first network mode, determine that the network mode information corresponding to the current resident cell is the second network mode;

[0118] In response to the frequency range information of the current resident cell being the first frequency range, the communication mode of the current resident cell being time division duplex, and the second scenario information corresponding to the current resident cell being the preset scenario information, determine that the downlink beamforming support information corresponding to the second network mode is that the second network mode supports downlink dynamic beamforming.

[0119] Exemplarily, in an embodiment of the present disclosure, in response to the network mode information corresponding to the current resident cell and the downlink beamforming determination sequence, determining the downlink beamforming support information corresponding to the current network mode of the current resident cell includes:

[0120] In the case where the network mode information corresponding to the current resident cell is not the first network mode, determine that the network mode information corresponding to the current resident cell is the second network mode;

[0121] Obtain the frequency range information corresponding to the current resident cell;

[0122] In response to the frequency range information being the first frequency range (Frequency range 1, FR1), obtain the communication mode of the current serving cell.

[0123] In response to the communication mode being time division duplex, obtain the second scenario information corresponding to the current serving cell.

[0124] In response to the second scenario information being the preset scenario information, determine that the downlink beamforming support information corresponding to the second network mode is that the second network mode supports downlink dynamic beamforming.

[0125] According to some embodiments, in response to the network mode information corresponding to the current serving cell and the downlink beamforming determination order, determine the downlink beamforming support information corresponding to the current network mode of the current serving cell, including:

[0126] In response to the network mode information corresponding to the current serving cell not being the first network mode, determine that the network mode information corresponding to the current serving cell is the second network mode.

[0127] In response to the frequency range information corresponding to the current serving cell not being the first frequency range, or the communication mode of the current serving cell not being time division duplex, or the second scenario information corresponding to the current serving cell not being the preset scenario information, determine that the downlink beamforming support information corresponding to the second network mode is that the second network mode does not support downlink dynamic beamforming. Therefore, in the second network mode, the downlink beamforming support information can be determined according to the frequency range information and the communication mode, and in different network modes, the downlink beamforming support information can be determined according to different information, which can improve the accuracy of determining the downlink beamforming support information and the accuracy of obtaining the source determination.

[0128] According to some embodiments, the second network mode can be, for example, the 5G network mode.

[0129] According to some embodiments, the frequency range information can be used to indicate, for example, the frequency range of the current serving cell. The frequency range information can include, for example, the first frequency range, i.e., Frequency range 1, Frequency range 2, etc.

[0130] According to some embodiments, the communication mode can include, for example, time division duplex and frequency division duplex, etc.

[0131] In some embodiments, it is determined that the network mode information corresponding to the current serving cell is the 5G network mode, and the frequency range information corresponding to the current serving cell is obtained. In response to the frequency range information being the first frequency range, the communication mode of the current serving cell is obtained. In response to the communication mode being time division duplex, the second scenario information corresponding to the current serving cell is obtained. In response to the second scenario information being the subway scenario, it is determined that the downlink beamforming support information corresponding to the 5G network mode is that the 5G network mode supports downlink dynamic beamforming.

[0132] According to some embodiments, in response to a radio resource control signaling reconfiguration occurring in the radio resource control connected state, the downlink beamforming support information corresponding to the second network mode of the current serving cell is re-determined.

[0133] In some embodiments, in response to the network mode information corresponding to the current serving cell and the downlink beamforming determination sequence, the downlink beamforming support information corresponding to the current network mode of the current serving cell is determined, including:

[0134] In response to the network mode information corresponding to the current serving cell not being the second network mode, it is determined whether the network mode information corresponding to the current serving cell is the third network mode;

[0135] In response to determining that the network mode information corresponding to the current serving cell is the third network mode, the downlink beamforming support information corresponding to the current network mode of the current serving cell is determined by using the determination method corresponding to the third network mode. Among them, the third network mode can be, for example, a 6G or higher network mode.

[0136] According to some embodiments, in response to a radio resource control signaling reconfiguration occurring in the radio resource control connected state, the downlink beamforming support information corresponding to the third network mode of the current serving cell is re-determined.

[0137] In some embodiments, for example, when it is determined that the network mode information corresponding to the current serving cell is not the second network mode, it can be determined whether the network mode information corresponding to the current serving cell is the third network mode. When it is determined that the network mode information corresponding to the current serving cell is the third network mode, the determination method corresponding to the third network mode can be used to determine whether the third network mode supports downlink dynamic beamforming.

[0138] According to some embodiments, it is determined that the network mode information corresponding to the current serving cell is the 5G network mode, and the frequency range information corresponding to the current serving cell is obtained. In the case where the frequency range information is not the first frequency range, it is determined that the downlink beamforming support information corresponding to the 5G network mode is that the 5G network mode does not support downlink dynamic beamforming.

[0139] In some embodiments, it is determined that the network mode information corresponding to the current resident cell is the 5G network mode, and the frequency range information corresponding to the current resident cell is obtained. When the frequency range information is the first frequency range, the communication mode of the current resident cell is obtained. When the communication mode is not time division duplex, it is determined that the downlink beamforming support information corresponding to the 5G network mode is that the 5G network mode does not support downlink dynamic beamforming.

[0140] In some embodiments, it is determined that the network mode information corresponding to the current resident cell is the 5G network mode, and the frequency range information corresponding to the current resident cell is obtained. When the frequency range information is the first frequency range, the communication mode of the current resident cell is obtained. When the communication mode is time division duplex, the second scenario information corresponding to the current resident cell is obtained. When the second scenario information is the subway scenario or the high-speed rail scenario, it is determined that the downlink beamforming support information corresponding to the 5G network mode is that the 5G network mode does not support downlink dynamic beamforming.

[0141] In some embodiments, it is determined that the network mode information corresponding to the current resident cell is the 5G network mode, and the frequency range information corresponding to the current resident cell is obtained. When the frequency range information is the first frequency range, the communication mode of the current resident cell is obtained. When the communication mode is time division duplex, the second scenario information corresponding to the current resident cell is obtained. When the second scenario information is not the subway scenario or the high-speed rail scenario, it is determined that the downlink beamforming support information corresponding to the 5G network mode is that the 5G network mode supports downlink dynamic beamforming.

[0142] According to some embodiments, for example, when the network mode information corresponding to the current resident cell is not the 5G network mode, it is determined whether the network mode information corresponding to the current resident cell is the 6G network mode. For example, when the network mode information corresponding to the current resident cell is the 6G network mode, the determination method corresponding to the 6G network mode can be used to determine the downlink beamforming support information corresponding to the 6G network mode.

[0143] In step S23, in response to the current network mode supporting downlink dynamic beamforming, the first beam feature set and the second beam feature set related to the current network mode are obtained;

[0144] The specific process is as described above and will not be elaborated here.

[0145] According to some embodiments, wherein the first beam feature set includes a downlink static beam feature set, and the second beam feature set includes a downlink dynamic beam feature set. Obtaining the first beam feature set and the second beam feature set related to the current network mode includes:

[0146] Extract the features of the synchronization signal and / or reference signal of a broadband wireless communication system with downlink beamforming enabled, and obtain a set of downlink static beam features related to the current network mode;

[0147] Extract the features of the demodulation reference signal of a broadband wireless communication system with downlink dynamic beamforming enabled, and obtain a set of downlink dynamic beam features related to the current network mode.

[0148] Among them, the synchronization signal and / or reference signal includes at least one of the following:

[0149] Primary Synchronization Signal (PSS) in the first network mode;

[0150] Secondary Synchronization Signal (SSS) in the first network mode;

[0151] Cell-Specific Reference Signal (CRS) in the first network mode;

[0152] SSB in the second network mode;

[0153] TRS in the second network mode.

[0154] Among them, the set of downlink static beam features includes but is not limited to Signal to Interference plus Noise Ratio (SINR), maximum delay spread Tmax, root mean square delay spread Trms, maximum Doppler, specifically, it can include:

[0155] Primary Synchronization Signal - Signal to Interference plus Noise Ratio (PSS - SINR), Secondary Synchronization Signal - Signal to Interference plus Noise Ratio (SSS - SINR), Cell - Specific Reference Signal - Signal to Interference plus Noise Ratio (CRS - SINR), Cell - Specific Reference Signal - maximum delay spread (CRS - Tmax), Cell - Specific Reference Signal - rms delay spread (CRS - Trms), Cell - Specific Reference Signal - Doppler (CRS - Doppler) corresponding to the first network mode;

[0156] SSS - SINR, Tracking Reference Signal Channel - state information - Signal to Interference plus Noise Ratio (TRS CSI - SINR), Tracking Reference Signal Channel - maximum delay spread (TRS - Tmax), Tracking Reference Signal Channel - rms delay spread (TRS - Trms), Tracking Reference Signal Channel - Doppler (TRS - Doppler) corresponding to the second network mode.

[0157] Among them, the first network mode can be, for example, the 4G network mode, and the second network mode can be, for example, the 5G network mode.

[0158] Among them, the demodulation reference signal includes at least one of the following:

[0159] The Physical Downlink Shared Channel (PDSCH) demodulation reference signal (Demodulation Reference Signal, DMRS) under the first network mode or the second network mode;

[0160] The Physical Downlink Control Channel (PDCCH) DMRS under the second network mode.

[0161] Among them, the set of downlink dynamic beam characteristics includes, but is not limited to, Signal to Interference plus Noise Ratio (SINR), maximum delay spread Tmax, root mean square delay spread Trms, and maximum Doppler. Specifically, it may include:

[0162] The Physical Downlink Shared Channel - Signal to Interference plus Noise Ratio (PDCCH - SINR), Physical Downlink Shared Channel - maximum delay spread (PDCCH - Tmax), Physical Downlink Shared Channel - root mean square delay spread (PDCCH - Trms), and Physical Downlink Shared Channel - Doppler (PDCCH - Doppler) corresponding to the first network mode or the second network mode;

[0163] Physical Downlink Control Channel - Signal to Interference plus Noise Ratio (PDCCH - SINR), Physical Downlink Control Channel - maximum delay spread (PDCCH - Tmax), Physical Downlink Control Channel - rms delay spread (PDCCH - Trms), Physical Downlink Control Channel - Doppler (PDCCH - Doppler) corresponding to the second network mode.

[0164] Among them, the first network mode can be, for example, a 4G network mode, and the second network mode can be, for example, a 5G network mode.

[0165] In step 24, in response to the operation result between at least one first parameter of the first beam feature set and at least one second parameter of the second beam feature set and at least one threshold information, obtain a feature recognition result, where the feature recognition result is used to indicate whether at least one first parameter of the first beam feature set and at least one second parameter of the second beam feature set meet a preset condition;

[0166] The specific process is as described above and will not be elaborated here.

[0167] Among them, when obtaining the operation result between at least one first parameter of the first beam feature set and at least one second parameter of the second beam feature set, the first parameter and the second parameter can be, for example, parameters of the same beam feature, and the beam feature includes but is not limited to Signal to Interference plus Noise Ratio (SINR), maximum delay spread Tmax, rms delay spread Trms, Doppler, etc.

[0168] According to some embodiments, the obtaining the feature recognition result in response to the operation result between at least one first parameter of the first beam feature set and at least one second parameter of the second beam feature set and at least one threshold information includes:

[0169] Compare the result of subtraction and / or division between at least one first parameter of the first beam feature set and at least one second parameter of the second beam feature set with at least one threshold information to obtain a feature recognition result.

[0170] Among them, the feature recognition result can be, for example, a wide and narrow beam effect recognition result. Among them, the wide and narrow beam effect recognition result can be, for example, corresponding to the network mode. Among them, different network modes can determine the wide and narrow beam effect recognition result according to different recognition methods, for example.

[0171] Among them, the setting of each threshold in at least one threshold information can be, for example, set according to experience or modulation effect. For example, it can be set according to the accuracy of the wide and narrow beam effect recognition result. The embodiments of the present disclosure do not limit this.

[0172] It should be noted that when there are multiple beam features corresponding to at least one first parameter, at least one first parameter can include, for example, at least one parameter of each beam feature among the multiple beam features. When there are multiple beam features corresponding to at least one second parameter, at least one second parameter can include, for example, at least one parameter of each beam feature among the multiple beam features.

[0173] According to some embodiments, obtaining a feature recognition result in response to the operation result between at least one first parameter of the first beam feature set and at least one second parameter of the second beam feature set and at least one threshold information includes:

[0174] Obtain a feature recognition result in response to the operation result between any first parameter in the first beam feature set and any second parameter in the second beam feature set and at least one threshold information, where the any first parameter and the any second parameter correspond to the same beam feature.

[0175] In some embodiments, the beam feature is the signal-to-interference-plus-noise ratio SINR. Among them, at least one first parameter includes at least one of the following: cell-specific reference signal-signal-to-interference-plus-noise ratio CRS-SINR, primary synchronization signal-signal-to-interference-plus-noise ratio PSS-SINR, and secondary synchronization signal-signal-to-interference-plus-noise ratio SSS-SINR; at least one second parameter includes at least one of the following: physical downlink shared channel-signal-to-interference-plus-noise ratio PDSCH-SINR;

[0176] Alternatively, at least one of the first parameters includes at least one of the following: Time-Frequency Tracking Reference Signal Channel State Information - Signal-to-Interference-plus-Noise Ratio (TRS CSI-SINR) and Synchronization Signal - Signal-to-Interference-plus-Noise Ratio (SS-SINR); at least one of the second parameters includes at least one of the following: Physical Downlink Shared Channel - Time-Frequency Tracking Reference Signal (PDSCH-SINR) and Physical Downlink Control Channel - Signal-to-Interference-plus-Noise Ratio (PDCCH-SINR).

[0177] In some embodiments, the beam characteristic is the maximum delay spread Tmax, where at least one of the first parameters includes at least one of the following: Cell-Specific Reference Signal - Maximum Delay Spread (CRS-Tmax), and at least one of the second parameters includes at least one of the following: Physical Downlink Shared Channel - Maximum Delay Spread (PDSCH-Tmax);

[0178] Or

[0179] At least one of the first parameters includes at least one of the following: Time-Frequency Tracking Reference Signal - Maximum Delay Spread (TRS-Tmax), and at least one of the second parameters includes at least one of the following: Physical Downlink Shared Channel - Maximum Delay Spread (PDSCH-Tmax) and Physical Downlink Control Channel - Maximum Delay Spread (PDCCH-Tmax).

[0180] In some embodiments, the beam characteristic is the root mean square delay spread Trms, where at least one of the first parameters includes at least one of the following: Cell-Specific Reference Signal - Root Mean Square Delay Spread (CRS-Trms), and at least one of the second parameters includes at least one of the following: Physical Downlink Shared Channel - Root Mean Square Delay Spread (PDSCH-Trms);

[0181] Or

[0182] At least one of the first parameters includes at least one of the following: Time-Frequency Tracking Reference Signal - Root Mean Square Delay Spread (TRS-Trms), and at least one of the second parameters includes at least one of the following: Physical Downlink Shared Channel - Root Mean Square Delay Spread (PDSCH-Trms) and Physical Downlink Control Channel - Root Mean Square Delay Spread (PDCCH-Trms).

[0183] In some embodiments, the beam characteristic is the maximum Doppler, where at least one of the first parameters includes CRS-SINR, PSS-SINR, and SSS-SINR and Cell-Specific Reference Signal - Maximum Doppler (CRS-Doppler), and at least one of the second parameters includes at least one of the following: PDSCH-SINR, Physical Downlink Shared Channel - Maximum Doppler (PDSCH-Doppler);

[0184] Or,

[0185] At least one first parameter includes at least one of the following: TRS CSI-SINR, SS-SINR, and time-frequency tracking reference signal - maximum Doppler TRS-Doppler, and at least one second parameter includes at least one of the following: PDSCH-SINR, PDCCH-SINR, physical downlink control channel - maximum Doppler PDCCH-Doppler, and physical downlink shared channel - maximum Doppler PDSCH-Doppler.

[0186] According to some embodiments, obtaining a feature recognition result in response to an operation result between at least one first parameter of a first beam feature set and at least one second parameter of a second beam feature set and at least one threshold information includes:

[0187] Obtaining a feature recognition result in response to an operation result between two first parameters of a first beam feature set and two second parameters of a second beam feature set and at least one threshold information, where the two first parameters and the two second parameters correspond to two different beam features, and the operation result is two results obtained by performing operation processing on any one first parameter and any one second parameter of the same beam feature.

[0188] Among some embodiments, where at least one first parameter includes at least one of the following: CRS-Tmax and cell-specific reference signal - maximum Doppler CRS-Doppler, and at least one second parameter includes at least one of the following: PDSCH-Doppler and PDCCH-Tmax;

[0189] Or,

[0190] At least one first parameter includes at least one of the following: TRS-Tmax and TRS-Doppler, and at least one second parameter includes at least one of the following: PDSCH-Tmax, PDCCH-Tmax, PDSCH-Doppler, and PDCCH-Doppler.

[0191] Among some embodiments, where at least one first parameter includes at least one of the following: CRS-Trms and CRS-Dopple, and at least one second parameter includes at least one of the following: PDSCH-Trms and PDSCH-Doppler;

[0192] Or

[0193] At least one first parameter includes at least one of the following: TRS-Trms and TRS-Doppler, and at least one second parameter includes at least one of the following: PDSCH-Trms, PDCCH-Trms, PDSCH-Doppler, and PDCCH-Doppler.

[0194] In some embodiments, at least one first parameter includes at least one of the following: CRS - SINR, PSS - SINR, SSS - SINR, and CRS - Tmax, and at least one second parameter includes at least one of the following: PDSCH - SINR and PDSCH - Tmax;

[0195] Or,

[0196] At least one first parameter includes at least one of the following: TRS CSI - SINR, SS - SINR, and TRS - Tmax, and at least one second parameter includes at least one of the following: PDSCH - SINR, PDCCH - SINR, PDSCH - Tmax, and PDCCH - Tmax.

[0197] In some embodiments, at least one first parameter includes at least one of the following: CRS - SINR, PSS - SINR, SSS - SINR, and CRS - Trms, and at least one second parameter includes at least one of the following: PDSCH - SINR and PDSCH - Tmax;

[0198] Or,

[0199] At least one first parameter includes at least one of the following: TRS CSI - SINR, SS - SINR, and TRS - Trms, and at least one second parameter includes at least one of the following: PDSCH - SINR, PDCCH - SINR, PDSCH - Trms, and PDCCH - Trms.

[0200] According to some embodiments, in response to an operation result between at least one first parameter of a first beam feature set and at least one second parameter of a second beam feature set and at least one threshold information, obtaining a feature recognition result, includes:

[0201] In response to an operation result between three first parameters of a first beam feature set and three second parameters of a second beam feature set and at least one threshold information, obtaining a feature recognition result, wherein the three first parameters and the three second parameters correspond to three different beam features, and the operation result is three results obtained by performing operation processing on any one first parameter and any one second parameter of the same beam feature.

[0202] In some embodiments, at least one first parameter includes at least one of the following: CRS - SINR, PSS - SINR, SSS - SINR, CRS - Tmax, and CRS - Trms, and at least one second parameter includes at least one of the following: PDSCH - SINR, PDSCH - Tmax, and PDSCH - Trms;

[0203] Alternatively,

[0204] at least one first parameter includes at least one of the following: TRS CSI-SINR, SS-SINR, TRS-Tmax, and TRS-Trms, and at least one second parameter includes at least one of the following: PDSCH-SINR, PDCCH-SINR, PDSCH-Tmax, PDCCH-Tmax, PDSCH-Trms, and PDCCH-Trms.

[0205] According to some embodiments, when determining a feature recognition result based on an operation result between at least one first parameter of a first beam feature set and at least one second parameter of a second beam feature set and at least one threshold information, a threshold-based design rule can be adopted, which belongs to a decision design, balances the correct decision rate and the false alarm rate, improves the accuracy of obtaining the feature recognition result, and can improve the accuracy of obtaining the source determination.

[0206] According to some embodiments, obtaining a feature recognition result in response to an operation result between at least one first parameter of a first beam feature set and at least one second parameter of a second beam feature set and at least one threshold information includes:

[0207] In response to a first difference between any one of the second parameters and any one of the first parameters being greater than a first threshold, determining that the feature recognition result is a preset result, where the first threshold represents a relative SINR metric threshold, and the preset result is used to indicate that at least one first parameter of the first beam feature set and at least one second parameter of the second beam feature set meet a preset condition. Any one of the second parameters and any one of the first parameters may correspond to the same beam feature, for example.

[0208] According to some embodiments, wherein at least one first parameter includes at least one of the following: cell-specific reference signal-signal to interference plus noise ratio CRS-SINR, primary synchronization signal-signal to interference plus noise ratio PSS-SINR, and secondary synchronization signal-signal to interference plus noise ratio SSS-SINR; at least one second parameter includes at least one of the following: physical downlink shared channel-signal to interference plus noise ratio PDSCH-SINR;

[0209] Alternatively, wherein at least one first parameter includes at least one of the following: time-frequency tracking reference signal channel state information-signal to interference plus noise ratio TRS CSI-SINR and synchronization signal-signal to interference plus noise ratio SS-SINR; at least one second parameter includes at least one of the following: physical downlink shared channel-time-frequency tracking reference signal PDSCH-SINR and physical downlink control channel-signal to interference plus noise ratio PDCCH-SINR.

[0210] Exemplarily, in an embodiment of the present disclosure, when the current network mode is the 4G network mode, if the difference between the PDSCH - SINR and the CRS - SINR (or PSS - SINR or SSS - SINR) is greater than the first threshold, the feature recognition result can be determined as the preset result. For example, it can indicate that the wide and narrow beam effect occurs. When the difference between the PDSCH - SINR and the CRS - SINR (or PSS - SINR or SSS - SINR) is not greater than the first threshold, the feature recognition result can be determined not to be the preset result. For example, when the difference between the PDSCH - SINR and the CRS - SINR is greater than the first threshold, it can be determined that the wide and narrow beam effect recognition result is that the wide and narrow beam effect occurs. When the difference between the PDSCH - SINR and the CRS - SINR is not greater than the first threshold, it can be determined that the wide and narrow beam effect recognition result is that the wide and narrow beam effect does not occur. Among them, the second threshold can, for example, represent the relative SINR index threshold th - sinr - for - BF, and the value range can be, for example, 5 - 10 dB.

[0211] Exemplarily, in an embodiment of the present disclosure, when the current network mode is the 5G network mode, the difference between the PDSCH - SINR (or PDCCH - SINR) and the TRS CSI - SINR (or Synchronization Signal - Signal to Interference plus Noise Ratio, SS - SINR) and the first threshold are used to determine the feature recognition result as the preset result. Among them, the first threshold can, for example, represent the relative SINR index threshold th - sinr - for - BF, and the value range can be, for example, 5 - 10 dB.

[0212] Exemplarily, in an embodiment of the present disclosure, when the PDSCH - SINR (or PDCCH - SINR) - TRS CSI - SINR (or SS - SINR) is greater than the first threshold, the feature recognition result can be determined as the preset result. For example, it can be determined that the wide and narrow beam effect recognition result is that the wide and narrow beam effect occurs. When the PDSCH - SINR (or PDCCH - SINR) - TRS CSI - SINR (or SS - SINR) is not greater than the first threshold, the feature recognition result can be determined not to be the preset result. For example, it can be determined that the wide and narrow beam effect recognition result is that the wide and narrow beam effect does not occur.

[0213] According to some embodiments, in response to the operation result between at least one first parameter of the first beam feature set and at least one second parameter of the second beam feature set and at least one threshold information, obtaining the feature recognition result includes:

[0214] In response to the first ratio of any first parameter and any second parameter being greater than a second threshold, determine that the feature recognition result is a preset result, where the second threshold represents a relative maximum delay spread metric threshold, and the preset result is used to indicate that at least one first parameter of the first beam feature set and at least one second parameter of the second beam feature set meet the preset conditions.

[0215] According to some embodiments, at least one of the first parameters includes at least one of the following: cell-specific reference signal - maximum delay spread CRS-Tmax, and at least one of the second parameters includes at least one of the following: physical downlink shared channel - maximum delay spread PDSCH-Tmax;

[0216] Or

[0217] At least one of the first parameters includes at least one of the following: time-frequency tracking reference signal - maximum delay spread TRS-Tmax, and at least one of the second parameters includes at least one of the following: physical downlink shared channel - maximum delay spread PDSCH-Tmax and physical downlink control channel - maximum delay spread PDCCH-Tmax. Wherein, the second threshold may, for example, represent a relative maximum delay spread metric threshold th-tmax-for-BF, and the value range may be, for example, 1.5 to 3.

[0218] Exemplarily, in an embodiment of the present disclosure, when the current network mode is the 4G network mode, if CRS-Tmax / PDSCH-Tmax is greater than the second threshold, it can be determined that the feature recognition result is the preset result. For example, it can be determined that the wide and narrow beam effect recognition result is that the wide and narrow beam effect occurs. If CRS-Tmax / PDSCH-Tmax is not greater than the second threshold, it can be determined that the feature recognition result is not the preset result. For example, it can be determined that the wide and narrow beam effect recognition result is that the wide and narrow beam effect does not occur.

[0219] Exemplarily, in an embodiment of the present disclosure, when the current network mode is the 5G network mode, if TRS-Tmax / PDSCH-Tmax (or PDCCH-Tmax) is greater than the second threshold, it can be determined that the feature recognition result is the preset result. For example, it can be determined that the wide and narrow beam effect recognition result is that the wide and narrow beam effect occurs. When

[0220] TRS-Tmax / PDSCH-Tmax (or PDCCH-Tmax) is not greater than the fourth threshold, it can be determined that the feature recognition result is not the preset result. For example, it can be determined that the wide and narrow beam effect recognition result is that the wide and narrow beam effect does not occur.

[0221] According to some embodiments, obtaining a feature recognition result in response to an operation result between at least one first parameter of a first beam feature set and at least one second parameter of a second beam feature set and at least one threshold information, includes:

[0222] In response to a second ratio of any one of the first parameters to any one of the second parameters being greater than a third threshold, determining that the feature recognition result is a preset result, where the third threshold represents a relative root mean square delay spread index threshold, and the preset result is used to indicate that at least one first parameter of the first beam feature set and at least one second parameter of the second beam feature set meet a preset condition.

[0223] According to some embodiments, where at least one of the first parameters includes at least one of the following: cell-specific reference signal - root mean square delay spread CRS-Trms, and at least one of the second parameters includes at least one of the following: physical downlink shared channel - root mean square delay spread PDSCH-Trms;

[0224] Or

[0225] At least one of the first parameters includes at least one of the following: time-frequency tracking reference signal - root mean square delay spread TRS-Trms, and at least one of the second parameters includes at least one of the following: physical downlink shared channel - root mean square delay spread PDSCH-Trms and physical downlink control channel - root mean square delay spread PDCCH-Trms. Wherein, the third threshold may represent, for example, a relative root mean square delay spread index threshold th-trms-for-BF, and the value range may be, for example, 2 to 4.

[0226] Exemplarily, in an embodiment of the present disclosure, when the current network mode is the 4G network mode, if CRS-Trms / PDSCH-Trms is greater than the third threshold, it may be determined that the feature recognition result is the preset result. For example, it may be determined that the wide and narrow beam effect recognition result is that the wide and narrow beam effect occurs. If CRS-Trms / PDSCH-Trms is not greater than the third threshold, it may be determined that the feature recognition result is not the preset result. For example, it may be determined that the wide and narrow beam effect recognition result is that the wide and narrow beam effect does not occur.

[0227] Exemplarily, in an embodiment of the present disclosure, when the current network mode is the 5G network mode, if the TRS-Trms / PDSCH-Trms (or PDCCH-Trms) is greater than the third threshold, the feature recognition result can be determined as a preset result. For example, it can be determined that the wide and narrow beam effect recognition result is that the wide and narrow beam effect occurs. When the TRS-Trms / PDSCH-Trms (or PDCCH-Trms) is not greater than the third threshold, it can be determined that the feature recognition result is not the preset result. For example, it can be determined that the wide and narrow beam effect recognition result is that the wide and narrow beam effect does not occur.

[0228] According to some embodiments, in response to the operation result between at least one first parameter of the first beam feature set and at least one second parameter of the second beam feature set and at least one threshold information, obtaining a feature recognition result includes:

[0229] In response to the second difference between any signal-to-interference-plus-noise ratio SING in at least one second parameter and any signal-to-interference-plus-noise ratio SING in at least one first parameter being greater than a fourth threshold, and the third ratio between any maximum Doppler Doppler in at least one second parameter and any maximum Doppler Doppler in at least one first parameter being less than a fifth threshold, determining that the feature recognition result is a preset result, where the fourth threshold represents the relative SINR index threshold, the fifth threshold represents the relative maximum Doppler index threshold, and the preset result is used to indicate that at least one first parameter of the first beam feature set and at least one second parameter of the second beam feature set meet the preset conditions.

[0230] According to some embodiments, wherein at least one first parameter includes at least one of the following: CRS-SINR, PSS-SINR, and SSS-SINR and cell-specific reference signal-maximum Doppler CRS-Doppler, and at least one second parameter includes at least one of the following: PDSCH-SINR, physical downlink shared channel-maximum Doppler PDSCH-Doppler;

[0231] Or,

[0232] At least one first parameter includes at least one of the following: TRS CSI-SINR, SS-SINR, and time-frequency tracking reference signal-maximum Doppler TRS-Doppler, and at least one second parameter includes at least one of the following: PDSCH-SINR, PDCCH-SINR, physical downlink control channel-maximum Doppler PDCCH-Doppler, and physical downlink shared channel-maximum Doppler PDSCH-Doppler.

[0233] Exemplarily, in an embodiment of the present disclosure, when the current network mode is the 4G network mode, the PDSCH - SINR - CRS - SINR (or PSS - SINR or SSS - SINR) and the fourth threshold, as well as the PDSCH - Doppler / CRS - Doppler and the fifth threshold are used to determine the feature recognition result. Among them, the fourth threshold can, for example, represent the relative SINR index threshold th - sinr - for - BF, and the value range can be, for example, 5 to 10 dB; the fifth threshold can, for example, represent the relative maximum Doppler index threshold th - doppler - for - BF, and the value range can be, for example, 0.7 to 1.3.

[0234] Exemplarily, in an embodiment of the present disclosure, when the current network mode is the 4G network mode, if the PDSCH - SINR - CRS - SINR (or PSS - SINR or SSS - SINR) is greater than th - sinr - for - BF and the PDSCH - Doppler / CRS - Doppler is less than th - doppler - for - BF, the feature recognition result can be determined as the preset result. For example, it can be determined that the recognition result of the wide - narrow beam effect is that the wide - narrow beam effect occurs. If the PDSCH - SINR - CRS - SINR (or PSS - SINR or SSS - SINR) is not greater than th - sinr - for - BF and / or the PDSCH - Doppler / CRS - Doppler is not less than th - doppler - for - BF, the feature recognition result can be determined not to be the preset result. For example, it can be determined that the recognition result of the wide - narrow beam effect is that the wide - narrow beam effect does not occur.

[0235] In some embodiments, when the current network mode is the 5G network mode, the PDSCH - SINR (or PDCCH - SINR) - TRS CSI - SINR (or SS - SINR) and the fourth threshold, as well as the PDSCH - Doppler (or PDCCH - Doppler) / TRS - Doppler and the fifth threshold are used to determine the feature recognition result. Among them, the fourth threshold can, for example, represent the relative SINR index threshold th - sinr - for - BF, and the value range can be, for example, 5 to 10 dB; the fifth threshold can, for example, represent the relative maximum Doppler index threshold th - doppler - for - BF, and the value range can be, for example, 0.7 to 1.3.

[0236] Exemplarily, in an embodiment of the present disclosure, when the current network mode is the 5G network mode, the PDSCH - SINR (or PDCCH - SINR) - TRS CSI - SINR (or SS - SINR) is greater than th - sinr - for - BF and

[0237] When PDSCH-Doppler (or PDCCH-Doppler) / TRS-Doppler is less than th-doppler-for-BF, the feature recognition result can be determined as a preset result. For example, it can be determined that the wide and narrow beam effect recognition result is the occurrence of the wide and narrow beam effect.

[0238] When PDSCH-SINR (or PDCCH-SINR)-TRS CSI-SINR (or SS-SINR) is not greater than th-sinr-for-BF and / or PDSCH-Doppler (or PDCCH-Doppler) / TRS-Doppler is not less than th-doppler-for-BF, the feature recognition result can be determined not to be the preset result. For example, it can be determined that the wide and narrow beam effect recognition result is the non-occurrence of the wide and narrow beam effect.

[0239] In some embodiments, in response to the operation result between at least one first parameter of the first beam feature set and at least one second parameter of the second beam feature set and at least one threshold information, obtaining a feature recognition result includes:

[0240] In response to the fourth ratio of any one of the maximum delay spreads Tmax in at least one second parameter and any one of the maximum delay spreads Tmax in at least one first parameter being greater than a sixth threshold, and the fifth ratio of any one of the maximum Dopplers in at least one second parameter and any one of the maximum Dopplers in at least one first parameter being less than a seventh threshold, determining the feature recognition result as a preset result, where the sixth threshold characterizes the relative maximum delay spread index threshold, the seventh threshold characterizes the relative maximum Doppler index threshold, and the preset result is used to indicate that at least one first parameter of the first beam feature set and at least one second parameter of the second beam feature set meet the preset conditions.

[0241] In some embodiments, where at least one first parameter includes at least one of the following: CRS-Tmax and cell-specific reference signal-maximum Doppler CRS-Doppler, and at least one second parameter includes at least one of the following: PDSCH-Doppler and PDCCH-Tmax;

[0242] Or,

[0243] At least one first parameter includes at least one of the following: TRS-Tmax and TRS-Doppler, and at least one second parameter includes at least one of the following: PDSCH-Tmax, PDCCH-Tmax, PDSCH-Doppler, and PDCCH-Doppler. Among them, the sixth threshold can, for example, characterize the relative maximum delay spread index threshold th-tmax-for-BF, and the value range can, for example, be 1.5 to 3; the seventh threshold can, for example, characterize the relative maximum Doppler index threshold th-doppler-for-BF, and the value range can, for example, be 0.7 to 1.3.

[0244] Exemplarily, in an embodiment of the present disclosure, when the current network mode is the 4G network mode, if CRS-Tmax / PDSCH-Tmax is greater than th-tmax-for-BF and PDSCH-Doppler / CRS-Doppler is less than th-doppler-for-BF, the feature recognition result can be determined as the preset result. For example, it can be determined that the wide and narrow beam effect recognition result is that the wide and narrow beam effect occurs. If CRS-Tmax / PDSCH-Tmax is not greater than th-tmax-for-BF and / or PDSCH-Doppler / CRS-Doppler is not less than th-doppler-for-BF, the feature recognition result can be determined not to be the preset result. For example, it can be determined that the wide and narrow beam effect recognition result is that the wide and narrow beam effect does not occur.

[0245] In some embodiments, when the current network mode is the 4G network mode,

[0246] TRS-Tmax / PDSCH-Tmax (or PDCCH-Tmax) and the sixth threshold, and

[0247] PDSCH-Doppler (or PDCCH-Doppler) / TRS-Doppler and the seventh threshold are used to determine the feature recognition result. Among them, the sixth threshold can, for example, characterize the relative maximum delay spread index threshold th-tmax-for-BF, and the value range can, for example, be 1.5 to 3; the seventh threshold can, for example, characterize the relative maximum Doppler index threshold th-doppler-for-BF, and the value range can, for example, be 0.7 to 1.3.

[0248] Exemplarily, in one embodiment of the present disclosure, when TRS-Tmax / PDSCH-Tmax (or PDCCH-Tmax) is greater than th-tmax-for-BF and PDSCH-Doppler (or PDCCH-Doppler) / TRS-Doppler is less than th-doppler-for-BF, the feature recognition result can be determined as a preset result. For example, it can be determined that the recognition result of the wide and narrow beam effect is that the wide and narrow beam effect occurs. In

[0249] when TRS-Tmax / PDSCH-Tmax (or PDCCH-Tmax) is not greater than th-tmax-for-BF and / or

[0250] when PDSCH-Doppler (or PDCCH-Doppler) / TRS-Doppler is not less than th-doppler-for-BF, it can be determined that the feature recognition result is not the preset result. For example, it can be determined that the recognition result of the wide and narrow beam effect is that the wide and narrow beam effect does not occur.

[0251] In some embodiments, in response to the operation result between at least one first parameter of the first beam feature set and at least one second parameter of the second beam feature set and at least one threshold information, obtaining the feature recognition result includes:

[0252] When the sixth ratio of any maximum root mean square delay spread Trms in at least one second parameter to any maximum root mean square delay spread Trms in at least one first parameter is greater than the eighth threshold, and the seventh ratio of any maximum Doppler Doppler in at least one second parameter to any maximum Doppler Doppler in at least one first parameter is less than the ninth threshold, it is determined that the feature recognition result is the preset result, where the eighth threshold represents the relative maximum root mean square delay spread threshold, the ninth threshold represents the relative maximum Doppler index threshold, and the preset result is used to indicate that at least one first parameter of the first beam feature set and at least one second parameter of the second beam feature set meet the preset conditions.

[0253] In some embodiments, where at least one first parameter includes at least one of the following: CRS-Trms and CRS-Dopple, and at least one second parameter includes at least one of the following: PDSCH-Trms and PDSCH-Doppler;

[0254] Or

[0255] At least one first parameter includes at least one of the following: TRS-Trms and TRS-Doppler, and at least one second parameter includes at least one of the following: PDSCH-Trms, PDCCH-Trms, PDSCH-Doppler, and PDCCH-Doppler.

[0256] In some embodiments, when the current network mode is the first network mode, the feature recognition result can be determined by the CRS-Trms / PDSCH-Trms corresponding to at least one time point and the eighth threshold, and PDSCH-Doppler / CRS-Doppler and the ninth threshold. Among them, the eighth threshold can, for example, represent the relative root mean square delay spread index threshold th-trms-for-BF, and the value range can be, for example, 2 to 4; the ninth threshold can, for example, represent the relative maximum Doppler index threshold th-doppler-for-BF, and the value range can be, for example, 0.7 to 1.3.

[0257] Exemplarily, in an embodiment of the present disclosure, when the current network mode is the first network mode, if CRS-Trms / PDSCH-Trms is greater than th-trms-for-BF and PDSCH-Doppler / CRS-Doppler is less than th-doppler-for-BF, the feature recognition result can be determined as a preset result. For example, it can be determined that the narrow and wide beam effect recognition result is that the narrow and wide beam effect occurs. If CRS-Trms / PDSCH-Trms is not greater than th-trms-for-BF and / or PDSCH-Doppler / CRS-Doppler is not less than th-doppler-for-BF, the feature recognition result can be determined not to be the preset result. For example, it can be determined that the narrow and wide beam effect recognition result is that the narrow and wide beam effect does not occur.

[0258] In some embodiments, when the current network mode is the second network mode, the feature recognition result can be determined by the TRS-Trms / PDSCH-Trms (or PDCCH-Trms) corresponding to at least one time point and the eighth threshold, and

[0259] PDSCH-Doppler (or PDCCH-Doppler) / TRS-Doppler and the ninth threshold. Among them, the eighth threshold can, for example, represent the relative root mean square delay spread index threshold th-trms-for-BF, and the value range can be, for example, 2 to 4; the ninth threshold can, for example, represent the relative maximum Doppler index threshold th-doppler-for-BF, and the value range can be, for example, 0.7 to 1.3.

[0260] Exemplarily, in an embodiment of the present disclosure, when the current network mode is the second network mode, if TRS-Trms / PDSCH-Trms (or PDCCH-Trms) is greater than th-trms-for-BF and

[0261] PDSCH-Doppler (or PDCCH-Doppler) / TRS-Doppler is less than th-doppler-for-BF, it can be determined that the feature recognition result is a preset result. For example, it can be determined that the narrow and wide beam effect recognition result is that the narrow and wide beam effect occurs. When

[0262] TRS-Trms / PDSCH-Trms (or PDCCH-Trms) is not greater than th-trms-for-BF and / or

[0263] PDSCH-Doppler (or PDCCH-Doppler) / TRS-Doppler is not less than th-doppler-for-BF, it can be determined that the feature recognition result is not the preset result. For example, it can be determined that the narrow and wide beam effect recognition result is that the narrow and wide beam effect does not occur.

[0264] In some embodiments, in response to the operation result between at least one first parameter of the first beam feature set and at least one second parameter of the second beam feature set and at least one threshold information, obtaining a feature recognition result includes:

[0265] In response to the third difference between any SINR in at least one second parameter and any SINR in at least one first parameter being greater than the tenth threshold, and the eighth ratio between any maximum delay spread Tmax in at least one second parameter and any maximum delay spread Tmax in at least one first parameter being greater than the eleventh threshold, it is determined that the feature recognition result is a preset result, where the tenth threshold represents the relative SINR index threshold, the eleventh threshold represents the relative maximum delay spread index threshold, and the preset result is used to indicate that at least one first parameter of the first beam feature set and at least one second parameter of the second beam feature set meet the preset conditions.

[0266] In some embodiments, where at least one first parameter includes at least one of the following: CRS-SINR, PSS-SINR, SSS-SINR, and CRS-Tmax, and at least one second parameter includes at least one of the following: PDSCH-SINR and PDSCH-Tmax;

[0267] Or,

[0268] At least one first parameter includes at least one of the following: TRS CSI-SINR, SS-SINR, and TRS-Tmax, and at least one second parameter includes at least one of the following: PDSCH-SINR, PDCCH-SINR, PDSCH-Tmax, and PDCCH-Tmax.

[0269] Among some embodiments, when the current network mode is the first network mode, it can be determined through

[0270] PDSCH-SINR-CRS-SINR (or PSS-SINR or SSS-SINR) and a tenth threshold, and CRS-Tmax / PDSCH-Tmax and an eleventh threshold to determine the feature recognition result. Among them, the tenth threshold can, for example, represent the relative SINR metric threshold th-sinr-for-BF, and the value range can be, for example, 5 to 10 dB; the eleventh threshold can, for example, represent the relative maximum delay spread metric threshold th-tmax-for-BF, and the value range can be, for example, 1.5 to 3.

[0271] Exemplarily, in an embodiment of the present disclosure, when the current network mode is the first network mode, if PDSCH-SINR-CRS-SINR (or PSS-SINR or SSS-SINR) is greater than th-sinr-for-BF and CRS-Tmax / PDSCH-Tmax is greater than th-tmax-for-BF, the feature recognition result can be determined as a preset result. For example, it can be determined that the wide and narrow beam effect recognition result is that the wide and narrow beam effect occurs. If PDSCH-SINR-CRS-SINR (or PSS-SINR or SSS-SINR) is not greater than th-sinr-for-BF and / or CRS-Tmax / PDSCH-Tmax is not greater than th-tmax-for-BF, the feature recognition result can be determined not to be the preset result. For example, it can be determined that the wide and narrow beam effect recognition result is that the wide and narrow beam effect does not occur.

[0272] Among some embodiments, when the current network mode is the second network mode, it can be determined through

[0273] PDSCH-SINR (or PDCCH-SINR)-TRS CSI-SINR (or SS-SINR) and a tenth threshold, and

[0274] TRS-Tmax / PDSCH-Tmax (or PDCCH-Tmax) and an eleventh threshold to determine the feature recognition result. Among them, the tenth threshold can, for example, represent the relative SINR metric threshold th-sinr-for-BF, and the value range is 5 to 10 dB; the eleventh threshold can, for example, represent

[0275] For the relative maximum delay spread metric threshold th-tmax-for-BF, the value range is 1.5 to 3.

[0276] Exemplarily, in an embodiment of the present disclosure, when the current network mode is the second network mode, PDSCH-SINR (or PDCCH-SINR)-TRS CSI-SINR (or SS-SINR) is greater than th-sinr-for-BF and

[0277] when TRS-Tmax / PDSCH-Tmax (or PDCCH-Tmax) is greater than th-tmax-for-BF, it can be determined that the feature recognition result is a preset result. For example, it can be determined that the narrow and wide beam effect recognition result is that the narrow and wide beam effect occurs. In

[0278] when PDSCH-SINR (or PDCCH-SINR)-TRS CSI-SINR (or SS-SINR) is not greater than th-sinr-for-BF and / or TRS-Tmax / PDSCH-Tmax (or PDCCH-Tmax) is not greater than th-tmax-for-BF, it can be determined that the feature recognition result is not the preset result. For example, it can be determined that the narrow and wide beam effect recognition result is that the narrow and wide beam effect does not occur.

[0279] In some embodiments, in response to the operation result between at least one first parameter of the first beam feature set and at least one second parameter of the second beam feature set and at least one threshold information, obtaining a feature recognition result includes:

[0280] In response to the fourth difference between any SINR in at least one second parameter and any SINR in at least one first parameter being greater than the twelfth threshold, and the ninth ratio of any maximum root mean square delay spread Trms in at least one second parameter to any maximum root mean square delay spread Trms in at least one first parameter being greater than the thirteenth threshold, determining that the feature recognition result is a preset result. The twelfth threshold represents the relative SINR metric threshold, and the thirteenth threshold represents the relative maximum root mean square delay spread. The preset result is used to indicate that at least one first parameter of the first beam feature set and at least one second parameter of the second beam feature set meet the preset conditions.

[0281] In some embodiments, wherein, at least one first parameter includes at least one of the following: CRS-SINR, PSS-SINR, and SSS-SINR and CRS-Trms, and at least one second parameter includes at least one of the following: PDSCH-SINR and PDSCH-Tmax;

[0282] Or,

[0283] At least one of the at least one first parameter includes at least one of the following: TRS CSI-SINR, SS-SINR, and TRS-Trms, and at least one of the at least one second parameter includes at least one of the following: PDSCH-SINR, PDCCH-SINR, PDSCH-Trms, and PDCCH-Trms.

[0284] Among some embodiments, when the current network mode is the first network mode, it can be determined through

[0285] PDSCH-SINR-CRS-SINR (or PSS-SINR or SSS-SINR) and a twelfth threshold, and CRS-Trms / PDSCH-Trms and a thirteenth threshold to determine the feature recognition result. Among them, the twelfth threshold can, for example, represent the relative SINR index threshold th-sinr-for-BF, and the value range can be, for example, 5 to 10 dB; the thirteenth threshold can, for example, represent the relative root mean square delay spread index threshold th-trms-for-BF, and the value range can be, for example, 2 to 4.

[0286] Exemplarily, in an embodiment of the present disclosure, when the current network mode is the first network mode, when PDSCH-SINR-CRS-SINR (or PSS-SINR or SSS-SINR) is greater than th-sinr-for-BF and CRS-Trms / PDSCH-Trms is greater than th-trms-for-BF, the feature recognition result can be determined as a preset result. For example, it can be determined that the wide and narrow beam effect recognition result is that the wide and narrow beam effect occurs. When PDSCH-SINR-CRS-SINR (or PSS-SINR or SSS-SINR) is not greater than th-sinr-for-BF and / or CRS-Trms / PDSCH-Trms is not greater than th-trms-for-BF, the feature recognition result can be determined not to be the preset result. For example, it can be determined that the wide and narrow beam effect recognition result is that the wide and narrow beam effect does not occur.

[0287] Among some embodiments, when the current network mode is the second network mode, it can be determined through

[0288] PDSCH-SINR (or PDCCH-SINR)-TRS CSI-SINR (or SS-SINR) and a twelfth threshold, and

[0289] Determine the feature recognition result based on the TRS-Trms / PDSCH-Trms (or PDCCH-Trms) and the thirteenth threshold. Among them, the twelfth threshold can, for example, represent the relative SINR metric threshold th-sinr-for-BF, and its value range can be, for example, 5 to 10 dB; the thirteenth threshold can, for example, represent the relative root mean square delay spread metric threshold th-trms-for-BF, and its value range can be, for example, 2 to 4.

[0290] Exemplarily, in an embodiment of the present disclosure, when the current network mode is the second network mode, if PDSCH-SINR (or PDCCH-SINR)-TRS CSI-SINR (or SS-SINR) is greater than th-sinr-for-BF and

[0291] TRS-Trms / PDSCH-Trms (or PDCCH-Trms) is greater than th-trms-for-BF, it can be determined that the feature recognition result is a preset result. For example, it can be determined that the wide and narrow beam effect recognition result is that the wide and narrow beam effect occurs. When PDSCH-SINR (or PDCCH-SINR)-TRS CSI-SINR (or SS-SINR) is not greater than th-sinr-for-BF and / or TRS-Trms / PDSCH-Trms (or PDCCH-Trms) is not greater than th-trms-for-BF, it can be determined that the feature recognition result is not the preset result. For example, it can be determined that the wide and narrow beam effect recognition result is that the wide and narrow beam effect does not occur.

[0292] In some embodiments,

[0293] Obtain the feature recognition result in response to the operation result between at least one first parameter of the first beam feature set and at least one second parameter of the second beam feature set and at least one threshold information, including:

[0294] In response to that the fifth difference between any SINR among at least one second parameter and any SINR among at least one first parameter is greater than the fourteenth threshold, and the tenth ratio between any maximum delay spread Tmax among at least one second parameter and any maximum delay spread Tmax among at least one first parameter is greater than the fifteenth threshold, and the eleventh ratio between any maximum root-mean-square delay spread Trms among at least one second parameter and any maximum root-mean-square delay spread Trms among at least one first parameter is greater than the sixteenth threshold, determine that the feature recognition result is a preset result, where the fourteenth threshold characterizes the relative SINR index threshold, the fifteenth threshold characterizes the relative maximum delay spread index threshold, the sixteenth threshold characterizes the relative maximum root-mean-square delay spread, and the preset result is used to indicate that at least one first parameter of the first beam feature set and at least one second parameter of the second beam feature set meet the preset conditions.

[0295] In some embodiments, where at least one first parameter includes at least one of the following:

[0296] CRS-SINR, PSS-SINR, SSS-SINR, CRS-Tmax, and CRS-Trms, and at least one second parameter includes at least one of the following: PDSCH-SINR, PDSCH-Tmax, and PDSCH-Trms;

[0297] Or,

[0298] At least one first parameter includes at least one of the following: TRS

[0299] CSI-SINR, SS-SINR, TRS-Tmax, and TRS-Trms, and at least one second parameter includes at least one of the following:

[0300] PDSCH-SINR, PDCCH-SINR, PDSCH-Tmax, PDCCH-Tmax, PDSCH-Trms, and PDCCH-Trms.

[0301] In some embodiments, when the current network mode is the first network mode, it is possible to

[0302] PDSCH-SINR - CRS-SINR (or PSS-SINR or SSS-SINR) and the fourteenth threshold, and CRS-Tmax / PDSCH-Tmax and the fifteenth threshold, and CRS-Trms / PDSCH-Trms and the sixteenth threshold to determine the feature recognition result. Among them, the fourteenth threshold can, for example, characterize the relative SINR index threshold th-sinr-for-BF, and the value range can, for example, be 5 to 10 dB; the fifteenth threshold can, for example, characterize

[0303] For the relative maximum delay spread metric threshold th-tmax-for-BF, the value range can be, for example, 1.5 to 3. The sixteenth threshold can represent, for example, the relative root mean square delay spread metric threshold th-trms-for-BF, and the value range can be, for example, 2 to 4.

[0304] Exemplarily, in an embodiment of the present disclosure, when the current network mode is the first network mode, if PDSCH-SINR-CRS-SINR (or PSS-SINR or SSS-SINR) is greater than th-sinr-for-BF and CRS-Tmax / PDSCH-Tmax is greater than th-tmax-for-BF and CRS-Trms / PDSCH-Trms is greater than th-trms-for-BF, the feature recognition result can be determined as a preset result. For example, it can be determined that the wide and narrow beam effect recognition result is that the wide and narrow beam effect occurs.

[0305] If PDSCH-SINR-CRS-SINR (or PSS-SINR or SSS-SINR) is not greater than th-sinr-for-BF and / or CRS-Tmax / PDSCH-Tmax is not greater than th-tmax-for-BF and / or CRS-Trms / PDSCH-Trms is not greater than th-trms-for-BF, the feature recognition result can be determined not to be the preset result. For example, it can be determined that the wide and narrow beam effect recognition result is that the wide and narrow beam effect does not occur.

[0306] In some embodiments, when the current network mode is the second network mode, it can be determined by

[0307] PDSCH-SINR (or PDCCH-SINR)-TRS CSI-SINR (or SS-SINR) and the fourteenth threshold, and

[0308] TRS-Tmax / PDSCH-Tmax (or PDCCH-Tmax) and the fifteenth threshold, and TRS-Trms

[0309] Based on / PDSCH-Trms (or PDCCH-Trms) and the sixteenth threshold, determine the recognition result of the wide and narrow beam effect corresponding to at least one time point. Among them, the fourteenth threshold can, for example, represent the relative SINR metric threshold th-sinr-for-BF, and its value range can be, for example, 5 to 10 dB; the fifteenth threshold can, for example, represent the relative maximum delay spread metric threshold th-tmax-for-BF, and its value range can be, for example, 1.5 to 3. The sixteenth threshold can, for example, represent the relative root mean square delay spread metric threshold th-trms-for-BF, and its value range can be, for example, 2 to 4.

[0310] Exemplarily, in an embodiment of the present disclosure, when PDSCH-SINR (or PDCCH-SINR)-TRS CSI-SINR (or SS-SINR) is greater than th-sinr-for-BF and TRS-Tmax / PDSCH-Tmax (or PDCCH-Tmax) is greater than th-tmax-for-BF and TRS-Trms / PDSCH-Trms (or PDCCH-Trms) is greater than th-trms-for-BF, the feature recognition result can be determined as a preset result. For example, it can be determined that the recognition result of the wide and narrow beam effect is that the wide and narrow beam effect occurs. When PDSCH-SINR (or PDCCH-SINR)-TRS CSI-SINR (or SS-SINR) is not greater than th-sinr-for-BF and / or TRS-Tmax / PDSCH-Tmax (or PDCCH-Tmax) is not greater than th-tmax-for-BF and / or TRS-Trms / PDSCH-Trms (or PDCCH-Trms) is not greater than th-trms-for-BF, it can be determined that the feature recognition result is not the preset result. For example, it can be determined that the recognition result of the wide and narrow beam effect is that the wide and narrow beam effect does not occur.

[0311] Among them, in the embodiments of the present disclosure, multiple schemes for determining the feature recognition result based on the operation result between at least one first parameter of the first beam feature set and at least one second parameter of the second beam feature set and at least one threshold information can, for example, be combined with each other to determine the feature recognition result, which can improve the accuracy of determining the feature recognition result, reduce the situation where the acquisition accuracy of the wireless channel state information required for channel estimation is poor, can improve the receiving state of the communication device, and improve the communication quality of the communication device.

[0312] In step 25, at least one first parameter of the first beam feature set and at least one second parameter of the second beam feature set are input into a preset beam perception neural network model to obtain a feature recognition result output by the beam perception neural network model, where the feature recognition result is used to indicate whether at least one first parameter of the first beam feature set and at least one second parameter of the second beam feature set meet a preset condition;

[0313] The specific process is as described above and will not be elaborated here.

[0314] Among them, in an embodiment of the present disclosure, the type of the preset beam perception neural network model is not limited. For example, any model that can determine the feature recognition result based on at least one first parameter of the first beam feature set and at least one second parameter of the second beam feature set is acceptable.

[0315] According to some embodiments, the step of inputting at least one first parameter of the first beam feature set and at least one second parameter of the second beam feature set into a preset beam perception neural network model to obtain the feature recognition result output by the beam perception neural network model includes:

[0316] Inputting at least one first parameter of the first beam feature set and at least one second parameter of the second beam feature set into a preset beam perception neural network model to obtain a vector corresponding to the at least one first parameter and the at least one second parameter;

[0317] Performing recognition processing on the vector by using the activation function of the preset beam perception neural network model to obtain the feature recognition result output by the beam perception neural network model.

[0318] In some embodiments, when the current network mode is the first network mode, CRS - SINR, CRS - Tmax, CRS - Trms, CRS - Doppler, PDSCH - SINR, PDSCH - Tmax, PDSCH - Trms, and PDSCH - Doppler can be input into a preset beam perception neural network model. It is possible to control whether the wide - narrow beam effect occurs at the current time point through the inference of the beam perception neural network model.

[0319] In some embodiments, when the current network mode is the second network mode, SS-SINR, TRSCSI-SINR, TRS-Tmax, TRS-Trms, TRS-Doppler, PDCCH-SINR, PDSCH-Tmax (PDCCH-Tmax), PDSCH-Trms (PDCCH-Trms), PDSCH-Doppler (PDCCH-Doppler) can be input into the beam perception neural network model. The beam perception neural network model can be controlled to infer whether the wide / narrow beam effect occurs at the current time point.

[0320] In response to some embodiments, the wide / narrow beam effect recognition result can be, for example, the output period Tbf, and its value range can be, for example, 0.5 to 5 ms.

[0321] In some embodiments, the input features of the preset beam perception neural network model can be, for example where x[t] can be, for example, N in ×1 dimensional vector, where N in takes corresponding values respectively in the 4 / 5G camped network state.

[0322] Among them, when the current network mode is the first network mode, the input of the preset beam perception neural network model is represented in the following form:

[0323] x[t] = [CRS-SINR[t], CRS-Tmax[t], CRS-Trms[t], CRS-Doppler[t], PDSCH-SINR[t], PDSCH-Tmax[t], PDSCH-Trms[t], PDSCH-Doppler[t]]T, which is an 8×1 vector (where the superscript T at the end of the formula indicates transpose, that is, the 1×8 row vector is rearranged in order to form an 8×1 column vector). Each element of this vector represents the result obtained from the t-th sampling, and X[t] represents the signal feature obtained from the t-th sampling.

[0324] Among them, when the current network mode is the second network mode, the input of the preset beam perception neural network is represented in the following form:

[0325] x[t] = [SS - SINR[t], TRS CSI - SINR[t], TRS - Tmax[t], TRS - Trms[t], TRS - Doppler[t], PDSCH - SINR[t] (or PDCCH - SINR), PDSCH - Tmax[t] (or PDCCH - Tmax), PDSCH - Trms[t] (or PDCCH - Trms), PDSCH - Doppler[t] (or PDCCH - Doppler)] T , a 9×1 vector, where each element of the vector represents the result obtained from the t - th sampling, and X[t] represents the signal feature obtained from the t - th sampling.

[0326] In some embodiments, under the beam perception neural network model based on the fully - connected neural network, for each signal feature obtained from sampling, only the signal feature of the current sampling is used to call the fully - connected neural network model once to obtain the inference output value corresponding to the current sampling. Therefore, in the embodiments of the present disclosure, the input N in ×1 - dimensional vector is represented by , and the [t] identifier indicating the sampling time can be omitted.

[0327] In some embodiments, Figure 8a is an example schematic diagram of a neural network model shown according to an exemplary embodiment. As Figure 8a shown, the preset beam perception neural network model can be, for example, a fully - connected network model. This network model includes 1 input layer, M≥1 hidden layers, and 1 output layer, and the corresponding number of nodes are In the present invention, the number of hidden layers ranges from 1 to 16, and the number of nodes in each hidden layer ranges from 1 to 1024.

[0328] Each node in hidden layer 1 is defined as The calculation method is

[0329]

[0330] where W1 is a - dimensional matrix, and b1 is a - dimensional vector. Both are preset fixed real coefficients obtained through a pre - trained neural network process. f1(·) represents applying an activation function to each element of the input vector. The definition of the activation function is the same as that of a general neural network and will not be elaborated here. Taking the activation function ReLU as an example, its definition is f(x) = max(x, 0), then the calculation method of hidden layer 1 is That is, taking the lower limit of 0 for each element of the - dimensional vector W1x + b1, and then obtaining the result.

[0331] According to some embodiments, each node of the hidden layer k is defined as The calculation method is

[0332]

[0333] where W k is a matrix of dimension k is a vector of dimension k f(·) represents the activation function used in the k-th layer. Similarly, W k and b k are obtained in advance through a pre-training process, and the activation function is defined as above.

[0334] According to some embodiments, each node of the output layer is defined as The calculation method is

[0335]

[0336] where W out is a matrix of dimension out is N out × 1 vector, f out (·) represents the activation function applicable to the output layer. Similarly, W out and b out are obtained in advance through a pre-training process, and the activation function is defined as above.

[0337] According to some embodiments, the default value of N out is 1, and the following judgment is made based on the output layer node: If z1 > 0, it is determined that the narrow and wide beam effect occurs at the current moment; otherwise, it is determined that the narrow and wide beam effect does not occur at the current moment.

[0338] Among them, in an embodiment of the present disclosure, the number of input nodes N in = 8, the number of output nodes N out = 1, the number of hidden layers M = 2, and the number of nodes in the hidden layer

[0339] The activation function of each layer is Sigmoid;

[0340] W1 is a 6 × 8 matrix:

[0341]

[0342]

[0343] b1 is a 6 × 1 vector: [0.56686;

[0345] -0.47827;

[0346] -0.91867; 1.8984; 0.61859; 0.030253]

[0350] W2 is a 4×6 dimensional matrix:

[0351]

[0352] b2 is a 4×1 dimensional vector:

[0353] [-0.32724; 1.7266; 0.15219;

[0356] -1.319]

[0357] W out is a 1×4 dimensional vector:

[0358] [-0.036337 -1.234 -1.2407 -1.4056]

[0359] b out is a 1×1 dimensional scalar:

[0360] [-0.3172]

[0361] Among them, in one embodiment of the present disclosure, the number of input nodes N in = 9, the number of output nodes N out = 1, the number of hidden layers M = 3, the number of nodes in the hidden layer

[0362] The activation function of each hidden layer is ReLU, and the activation function of the output layer is Softmax;

[0363] W1 is a 4×9 dimensional matrix:

[0364]

[0365] b1 is a 4×1 dimensional vector:

[0366] [-0.52743;

[0367] -0.72111;

[0368] -0.96918; 1.2817]

[0370] W2 is a 3×4 dimensional matrix:

[0371]

[0372] b2 is a 3×1 dimensional vector: [0.68037; 0.043459; 0.54384]

[0376] W3 is a 2×3 dimensional matrix:

[0377] [0.48873 -0.74289 1.1725;

[0378] 1.49 1.5016 -1.5343]

[0379] b3 is a 2×1 dimensional vector: [1.203;

[0381] -0.50165]

[0382] W out is a 1×2 dimensional vector:

[0383] [-1.6399 0.18647]

[0384] b out is a 1×1 dimensional scalar: [0.30811]

[0386] Among them, in one embodiment of the present disclosure, for example, the beam perception neural network model can be trained. Among them, the training data and test data can, for example, come from historical communication data and can also come from simulation data. The embodiments of the present disclosure do not limit this. Among them, in the actual communication process or data simulation, the signal characteristics related to the input of the beam perception neural network model can be recorded, and according to the current actual communication performance or simulation performance, the label (i.e., the desired output value) of the signal characteristics can be marked. Among them, each sampling can obtain a set of input data and the corresponding output label. Taking the second network mode as an example, it is assumed that the input obtained from the t-th sampling is x[t]=[SS-SINR[t],TRS CSI-SINR[t],TRS-Tmax[t],TRS-Trms[t],TRS-Doppler[t],PDSCH-SINR[t](or PDCCH-SINR),PDSCH-Tmax[t](or PDCCH-Tmax),PDSCH-Trms[t](or PDCCH-Trms),PDSCH-Doppler[t](or PDCCH-Doppler)] T, if the marked output value is z[t], then {x[t], z[t]} constitutes a piece of training or test data for this beam perception neural network model. After multiple samplings, multiple pieces of data are obtained, and these data can be divided into a training data set and a test data set. Among them, the training data set is used for neural network parameter training, that is, to obtain the above-mentioned preset parameter matrices / vectors / scalars, and the test data set is used to verify the performance of the training results.

[0387] In some embodiments, Figure 8b is an example schematic diagram of a neural network model shown according to an exemplary embodiment, as Figure 8b shown, the preset beam perception neural network model can be, for example, a recurrent neural network model. Under the beam perception model based on the recurrent neural network, each time a signal feature is sampled, based on the signal features sampled L times forward from the current sampling, a recurrent neural network model is called once to obtain the inference output value corresponding to the current sampling. Therefore, in the recurrent neural network, the input data is represented by [x[t - L + 1], …, x[t - 1], x[t]].

[0388] According to some embodiments, the network model includes L hidden states {h[t - L + 1], …, h[t]}, where each hidden state is respectively a dimensional vector, and L fully connected layers with activation functions {φ1, …, φ L} and 1 output layer φ out . In the present invention, the number of hidden states ranges from 1 to 16, and the dimensions of each hidden state range from 1 to 1024.

[0389] According to some embodiments, the calculation method (1) of the first hidden state h[t - L + 1] is:

[0390] h[t - L + 1] = f1(W hx,1 x[t - L + 1] + b1) (1)

[0391] where W hx,1 is a dimensional matrix, and b1 is a dimensional vector, both of which are preset fixed real coefficients obtained through a pre - neural network training process. f1(·) represents applying an activation function to each element of the input vector respectively, and the definition of the activation function is the same as that of a general neural network. Taking the activation function Sigmoid as an example, its definition is f(x) = (1 + e - x)-1, then the calculation method of hidden state 1 is: first calculate the intermediate variable a = W hx,1 x[t - L + 1] + b1, which is a dimensional vector, and then calculate h[t - L + 1], and its i - th element is (1 + e -a[i] )-1 , where a[i] is calculated from the i-th element of the intermediate variable a.

[0392] The calculation method (2) of the k-th hidden state (k = 2, …, L) is:

[0393] h[t - L + k] = f k (W hx，k x[t - L + k] + W hh，k h[t - L + k - 1] + b k ) (2)

[0394] where W hx,k is a matrix of dimension, W hh,k is a matrix of dimension, b k is a vector of dimension. All three are preset fixed real coefficients obtained through a pre-training process of a neural network. h[t - L + k - 1] is the (k - 1)-th hidden state ( a vector of dimension), and f k (·) represents the activation function applicable to the k-th layer.

[0395] According to some embodiments, each node of the output layer is defined as The calculation method (3) is:

[0396] z = f out (W out h[t] + b out ) (3)

[0397] where W out is a matrix of dimension, b out is N out ×1 vector. Both are preset fixed real coefficients obtained through a pre-training process of a neural network. f out (·) represents the activation function applicable to the output layer, and the activation function is defined as above.

[0398] According to some embodiments, the default value of N out is 1. Based on the nodes of the output layer, the following judgment is made: If z1 > 0, the beam perception neural network determines that the narrow and wide beam effect occurs at the current moment; otherwise, it determines that the narrow and wide beam effect does not occur at the current moment.

[0399] According to some embodiments, the number of input nodes N in = 8, the number of output nodes N out = 1, the number of hidden states L = 2, and the number of nodes in the hidden layer

[0400]

[0401] The activation function of each layer is Sigmoid;

[0402] W hx,1 is a 2×8 dimensional matrix:

[0403]

[0404] b1 is a 2×1 dimensional vector: [0.13263; 2.5974]

[0407] W hx,2 is a 3×8 dimensional matrix:

[0408]

[0409] b2 is a 3×1 dimensional vector:

[0410] [-0.41078;

[0411] -0.097416;

[0412] -0.15023]

[0413] W hh,2 is a 3×2 dimensional matrix:

[0414] [-0.27852 0.91732; 0.12799 0.76073;

[0416] -0.075746 -0.99056]

[0417] W out is a 1×3 dimensional vector:

[0418] [-0.45479 -0.48775 -0.67786]

[0419] b out is a 1×1 dimensional scalar: [1.2692]

[0421] According to some embodiments, the number of input nodes N in = 9, the number of output nodes N out = 1, the number of hidden states L = 3, the number of nodes in the hidden layer

[0422]

[0423] The activation functions of the 1st, 2nd, and 3rd hidden layers are Sigmoid, ReLU, and Softplus respectively, and the activation function of the output layer is Softmax;

[0424] W hx,1 is a 3×9 matrix:

[0425]

[0426] b1 is a 3×1 vector; [1.4983; 0.93334;

[0429] -0.84369]

[0430] W hx,2 is a 2×9 matrix:

[0431]

[0432] b2 is a 2×1 vector: [0.98282;

[0434] -0.85696]

[0435] W hh,2 is a 2×3 matrix:

[0436] [-0.113 -0.92787 0.38149;

[0437] 1.1621 -0.32756 -0.70608]

[0438] W hx,3 is a 2×9 matrix:

[0439]

[0440]

[0441] b3 is a 2×1 vector:

[0442] [-1.2314; 0.49445]

[0444] W hh,3 is a 2×2 matrix;

[0445] [-1.6949 0.95131;

[0446] -0.37369 -1.6743]

[0447] W out is a 1×2 vector: [0.88022 0.77134]

[0449] b outis a 1×1 dimensional scalar:

[0450] [-1.4642]

[0451] Among them, in an embodiment of the present disclosure, the training data or test data of the recurrent neural network may, for example, come from historical communication actual data or simulation data. During the actual communication process or data simulation process, signal features related to the neural network input can be recorded, and according to the current actual communication performance or simulation performance, the labels (i.e., the expected output values) of the signal features are marked. Each sampling can obtain a set of input data and the corresponding output labels. Taking the second network mode, that is, the 5G camped network state as an example, assume that the input obtained at the t-th sampling is x[t] = [SS - SINR[t], TRSCSI - SINR[t], TRS - Tmax[t], TRS - Trms[t], TRS - Doppler[t], PDSCH - SINR[t] (or PDCCH - SINR), PDSCH - Tmax[t] (or PDCCH - Tmax), PDSCH - Trms[t] (or PDCCH - Trms), PDSCH - Doppler[t] (or PDCCH - Doppler)]T, and the marked output value is z[t]. Different from the fully connected neural network model, each piece of data of the recurrent neural network not only contains the input and output at the current moment, but also contains the inputs at the previous L - 1 moments, that is, {x[t - L +

[0452] 1,..., xt, zt constitute a piece of training or test data of the neural network. After multiple samplings, multiple pieces of data are obtained. These data can be divided into a training data set and a test data set. Among them, the training data set is used for training the parameters of the recurrent neural network, that is, obtaining each preset parameter matrix / vector / scalar of the recurrent neural network model, and the test data set is used to verify the performance of the training result.

[0453] Under a given neural network model, the training objective of the neural network model is to minimize the error between the predicted output value and the true output value label. To quantify the gap between the predicted value and the true value, a loss function can be defined. Taking the loss function as an example, the error is defined as where z and are the true output value label and the predicted output value respectively, represents the sum of the squares of all elements of the matrix or vector.

[0454] Based on the above training data and loss function, first set the initial values of all the parameters to be solved of the neural network (including W hx,1 , …, W hx,L , W out , b1, …, bL , b out , W hh,2 , …, W hh,L ), and then, under the training samples, calculate the total error, that is, the sum of the loss functions of all training set samples. Then, using the backpropagation process of the recurrent neural network model, continuously correct the above parameters to be solved during the iteration until the sum of the loss functions of all training set samples meets the requirements.

[0455] Optionally, Figure 8c is an example schematic diagram of a neural network model shown according to an exemplary embodiment. As Figure 8c shown, the preset beam perception neural network model in the embodiments of the present disclosure is a random forest model. Under the beam perception model based on random forest, each time a signal feature is sampled, only the currently sampled signal feature is used, and the random forest model is called once to obtain the inference output value corresponding to the current sampling. Therefore, in this subsection, the input N in ×1-dimensional vector is represented by , and the [t] identifier indicating the sampling time is omitted.

[0456] According to some embodiments, the network model contains decision trees. When P = 1, the random forest model degenerates into a decision tree. Each decision tree gives its own discriminant classification result according to the input data. For example, Figure 8c in A and B respectively refer to the occurrence of the wide and narrow beam effects at the current moment and the non-occurrence of the wide and narrow beam effects at the current moment. The classification result with more votes can be determined as the final classification result according to the classification results of multiple decision trees.

[0457] According to some embodiments, taking the binary tree shown in Figure 8c as an example, the implementation method of a single decision tree can be as shown in Figure 8d . The bottom layer of the decision tree is the leaf node, and each leaf node corresponds to a classification discriminant result. If the decision process falls into a certain leaf node, the final classification discriminant result of the decision tree can be determined. Except for the leaf nodes in the bottom layer of the decision tree, each node in the remaining layers takes a certain feature of the input data and determines whether it meets a specific condition to decide which sub-node the node will go to next.

[0458] Assume that the order relationship is used as the determination condition for each node. Then, the determination node of each non-leaf node can be expressed as [k, T], where k represents the feature number and T is the order relationship threshold, meaning that for the input data if x k < T, then the next step is to select the left branch, otherwise enter the right branch; and so on.

[0459] Specifically, for Figure 8dThe decision tree with internal nodes of layer Q, based on the input data will go through Q + 1 determinations to obtain the final judgment result:

[0460] The 1st determination: The root node has preset parameters [k 0,1 , T 0,1 , which are obtained through pre-training. Among them, the first parameter is a serial number among 1, …, N in in, and the second parameter is a real threshold. Determine whether holds. If it holds, enter the left branch connected to the root node, and mark the determination result as c1 = 0; otherwise, enter the right branch connected to the root node, and mark the determination result as c1 = 1.

[0461] The 2nd determination: Corresponding to the internal node of the 1st layer, there are preset parameters [k 1,1 , T 1,1 , [k 1,2 , T 1,2 , which are obtained through pre-training. The first of each group of parameters is a serial number among 1, …, N in in, and the second parameter is a real threshold. According to the determination result c1 of the 1st determination, determine the corresponding parameters of the associated node of the 2nd determination Determine whether holds. If it holds, enter the left branch connected to this internal node, and mark the determination result as c2 = 0; otherwise, enter the right branch connected to this internal node, and mark the determination result as c2 = 1.

[0462] The kth determination (3 ≤ k ≤ Q + 1): Corresponding to the internal node of the k - 1th layer, there are preset parameters obtained through pre-training. The first of each group of parameters is a serial number among 1, …, N in in, and the second parameter is a real threshold. According to the determination results c1, …, c k-1 of the 1st, …, k - 1th determinations, determine the corresponding parameters of the associated node of the kth determination Determine whether holds. If it holds, enter the left branch connected to this internal node, and mark the final judgment result as A; otherwise, enter the right branch connected to this internal node, and mark the final judgment result as B.

[0463] According to some embodiments, the number of input nodes N in = 8, the number of decision trees P = 3, and the number of internal node layers Q = 1. The corresponding parameters of the random forest are:

[0464] Decision tree 1: [k 0,1 , T 0,1 = [1, 2.5], [k1,1 , T 1,1 = [2, 1], [k 1,2 , T 1,2 = [4, 10];

[0465] Decision Tree 2: [k 0,1 , T 0,1 = [3, 1], [k 1,1 , T 1,1 = [1, 8.5], [k 1,2 , T 1,2 = [6, 5];

[0466] Decision Tree 3: [k 0,1 , T 0,1 = [5, 4.5], [k 1,1 , T 1,1 = [8, 7], [k 1,2 , T 1,2 = [7, 3].

[0467] According to some embodiments, the number of input nodes N in = 9, the number of decision trees P = 1, and the number of internal node layers Q = 2. The corresponding parameters of the random forest are:

[0468] Decision Tree 1: [k 0,1 , T 0,1 = [2, 3.5], [k 1,1 , T 1,1 = [3, 2], [k 1,2 , T 1,2 = [5, 7], [k 2,1 , T 2,1 = [9, 2], [k 2,2 , T 2,2 = [8, 2], [k 2,2 , T 2,2 = [4, 2.5], [k 2,2 , T 2,2 = [5, 3.5].

[0469] According to some embodiments, the training or test data of the random forest can, for example, come from historical communication actual data or numerical simulations. During the actual communication process or numerical simulation, signal features related to the neural network input can be recorded, and based on the current actual communication performance or simulation performance, the labels (i.e., the expected output values) of these signal features are marked. Each sampling can obtain a set of input data and the corresponding output label. Taking the second network mode, i.e., the 5G camping state, as an example, assume that the input obtained from the t-th sampling is x[t] = [SS - SINR[t], TRS CSI - SINR[t], TRS - Tmax[t], TRS - Trms[t], TRS - Doppler[t], PDSCH - SINR[t] (or PDCCH - SINR), PDSCH - Tmax[t] (or PDCCH - Tmax), PDSCH - Trms[t] (or PDCCH - Trms), PDSCH - Doppler[t] (or PDCCH - Doppler)]T, and the marked output value is z[t]. Then {x[t], z[t]} constitutes a piece of training or test data for the random forest. Through multiple samplings, multiple pieces of data are obtained, and these data can be divided into a training data set and a test data set. The training data set is used for random forest parameter training, that is, to obtain each preset parameter matrix / vector / scalar mentioned in this section, and the test data set is used to verify the performance of the training result.

[0470] Based on the above training data, each decision tree in the random forest can be constructed, for example, in the following manner. Different decision trees are constructed independently, and the construction methods are the same:

[0471] Draw a part of the samples from the total training set with replacement, and the drawn samples are used to train the decision tree;

[0472] Each sample has N in input attributes. At each node that needs to be split in the decision tree, a specific strategy is used to select 1 attribute as the split attribute of this node and determine the corresponding split threshold. The strategies for determining the attribute and the threshold are not limited. For example, information gain can be used.

[0473] During the formation process of the decision tree, each node is split according to the previous step until the maximum depth is reached or it can no longer be split;

[0474] To ensure the consistency of the process (i.e., after setting the maximum depth, the total number of decision-making times in any case is the same), the branches with a depth less than the maximum depth (premature termination due to samples not supporting further splitting) are extended to the maximum depth. The extension method is: for the leaf nodes with a depth less than the maximum depth, continue to expand the branches backward, and the decision-making parameters of each decision node are set to [1, T max +1], where Tmax Ensure that the value of x1[t] is greater than a certain value in any scenario, for example, take infinity; at the same time, the determination results of the final leaf nodes corresponding to these branches are all the determination results of the leaf nodes that do not reach the maximum depth.

[0475] In step S26, in response to at least one first parameter of the first beam feature set and at least one second parameter of the second beam feature set satisfying a preset condition, select the first beam feature set or the second beam feature set as the source for obtaining the wireless channel state information.

[0476] The specific process is as described above and will not be elaborated here.

[0477] In response to some embodiments, for a continuous observation fixed period, the first time information is any moment in the current period of the continuous observation preset period, and the second time information is the next preset period adjacent to the current period. At this time, an example schematic diagram of the first time information and the second time information can be as Figure 9 shown.

[0478] In response to some embodiments, selecting the first beam feature set or the second beam feature set as the source for obtaining the wireless channel state information includes:

[0479] In response to the feature recognition result corresponding to the first time information satisfying the first result requirement, and the radio resource control connection of the communication device not being reconfigured or released, determine that the source for obtaining the wireless channel state information within the second time information is the dynamic beam feature acquisition source, where the first time information is any moment in the current period of the continuous observation preset period, the second time information is the next preset period adjacent to the current period, and the first result requirement includes the result requirement that the feature recognition results corresponding to the first time information are all preset results or the result requirement that the first quantity of the preset results in the feature recognition results corresponding to the first time information meets the quantity requirement.

[0480] According to some embodiments, selecting the first beam feature set or the second beam feature set as the source for obtaining the wireless channel state information includes:

[0481] In the case where the feature recognition results corresponding to the first time information are all preset results, and the radio resource control connection of the communication device is not reconfigured or released, determine that the source for obtaining the wireless channel state information within the second time information is the dynamic beam feature acquisition source.

[0482] According to some embodiments, the first time information is any moment in the current period of the continuous observation preset period. Selecting the first beam feature set or the second beam feature set as the source for obtaining the wireless channel state information includes:

[0483] In the case where the first quantity of the preset result in the feature recognition result corresponding to the first time information meets the quantity requirement, and the radio resource control connection of the communication device does not undergo reconfiguration or release, determine that the acquisition source corresponding to the wireless channel state information within the second time information is the dynamic beam feature acquisition source.

[0484] Wherein, the first quantity may also be, for example, the first quantity ratio, the first quantity percentage, the first quantity multiple, etc. The embodiments of the present disclosure do not limit this.

[0485] According to some embodiments, selecting the first beam feature set or the second beam feature set as the acquisition source of the wireless channel state information includes:

[0486] In response to the feature recognition result corresponding to the first time information meeting the second result requirement, determine that the acquisition source corresponding to the wireless channel state information within the second time information is the static beam feature acquisition source, where the first time information is any moment of the current period in the continuous observation preset period, and the second result requirement includes the result requirement that the feature recognition results corresponding to the first time information are not all preset results or the result requirement that the first quantity of the preset results in the feature recognition results corresponding to the first time information does not meet the quantity requirement.

[0487] According to some embodiments, the first time information is any moment of the current period in the continuous observation preset period, and selecting the first beam feature set or the second beam feature set as the acquisition source of the wireless channel state information includes:

[0488] In the case where the feature recognition results corresponding to the first time information are not all preset results, determine that the acquisition source corresponding to the wireless channel state information within the second time information is the static beam feature acquisition source.

[0489] Wherein, the time information is the continuous observation preset period, which may be, for example, the observation time window (ObservitionTime, Tobs) period, which may be, for example, a fixed observation time window, and its value range may be, for example, 50 to 100 ms or the period corresponding to the number of effective narrow and wide beam effect recognition results of the continuous observation times (number of observation, Nbf), where Nbf is a fixed number of observations, and the value range is 20 to 50. Wherein, the time information being the Tobs period can balance the recognition success rate and the recognition timeliness, can improve the determination efficiency of the acquisition source of the wireless channel state information, and improve the data reception performance of the communication device.

[0490] In response to some embodiments, the first time information is any moment of the current period in the continuous observation preset period, and selecting the first beam feature set or the second beam feature set as the acquisition source of the wireless channel state information includes:

[0491] When the first quantity of the preset result in the feature recognition result corresponding to the first-time information does not meet the quantity requirement, determine that the acquisition source corresponding to the wireless channel state information within the second-time information is the static beam feature acquisition source.

[0492] Among them, the quantity requirement can be, for example, that the ratio of the first quantity to the third quantity is less than the seventeenth threshold. Among them, the third quantity can be, for example, the total number corresponding to the wide and narrow beam effect recognition result corresponding to the first-time information.

[0493] Among them, the seventeenth threshold can be, for example, the rate of observation (Rbf), and its value range can be, for example, 60% to 90%.

[0494] Among them, the time information is a continuous observation preset period, which can be, for example, the Tobs period. Tobs can be, for example, a fixed observation time window, and its value range can be 50 to 100 ms or the period corresponding to Nbf consecutive valid wide and narrow beam effect recognition results. Among them, Nbf is a fixed number of observations, and the value range is 20 to 50. When the time information is the Tobs period, it can balance the recognition success rate and recognition timeliness, improve the determination efficiency of the acquisition source of the wireless channel state information, and improve the data reception performance of the communication device.

[0495] According to some embodiments, for the continuous observation sliding period, the first-time information is any moment in the current period of the continuous observation sliding period, and the second-time information is the time information before the next feature recognition result is not obtained. At this time, a schematic example of the first-time information and the second-time information can be as Figure 10 shown. Among them, the period sliding direction is an example illustration direction.

[0496] According to some embodiments, selecting the first beam feature set or the second beam feature set as the acquisition source of the wireless channel state information includes:

[0497] In response to the feature recognition result corresponding to the first-time information meeting the first result requirement and the radio resource control connection of the communication device not being reconfigured or released, determine that the acquisition source corresponding to the wireless channel state information within the second-time information is the dynamic beam feature acquisition source. Among them, the first-time information is any moment in the current period of the continuous observation sliding period, the second-time information is the time information before the next feature recognition result is not obtained, and the first result requirement includes the result requirement that the feature recognition results corresponding to the first-time information are all preset results or the result requirement that the second quantity of the preset results in the feature recognition results corresponding to the first-time information meets the quantity requirement.

[0498] According to some embodiments, selecting the first beam feature set or the second beam feature set as the acquisition source of the wireless channel state information includes:

[0499] In response to the feature recognition result corresponding to the first time information satisfying the second result requirement, determining that the acquisition source corresponding to the wireless channel state information within the second time information is a static beam feature acquisition source, where the first time information is any moment in the current period of the continuous observation sliding period, the second time information is the time information before the next feature recognition result is not obtained, and the second result requirement includes the result requirement that the feature recognition results corresponding to the first time information are not all preset results or the result requirement that the second quantity of the preset results in the feature recognition results corresponding to the first time information does not meet the quantity requirement;

[0500] Before the feature recognition result corresponding to the second time information is not obtained, observe the update information corresponding to the first time information, and use the updated first time information as the first time information to re-determine the acquisition source corresponding to the wireless channel state information within the second time information.

[0501] According to some embodiments, the first time information may be, for example, a continuous observation Tobs sliding window. When the feature recognition results corresponding to the first time information are all preset results and the RRC connection of the communication device does not undergo reconfiguration or release, before the feature recognition result is re-obtained, the acquisition source of the wireless channel state information is locked as the dynamic beam feature acquisition source.

[0502] According to some embodiments, the first time information may be, for example, a continuous observation Tobs sliding window. When the feature recognition results corresponding to the first time information are not all preset results, before the feature recognition result is re-obtained, the acquisition source of the wireless channel state information is the static beam feature acquisition source. The preset result may be, for example, "yes", and the embodiments of the present disclosure are not limited thereto.

[0503] According to some embodiments, before the feature recognition result is re-obtained, if the sliding window is updated, the beam feature acquisition source is re-determined.

[0504] Among them, the value range of the sliding observation time window length Tobs corresponding to the continuous observation Tobs sliding window may be, for example, 50 to 100 ms or the period corresponding to the continuous Nbf effective narrow-wide beam effect recognition results, where Nbf is the number of sliding observations, and the value range is, for example, 20 to 50.

[0505] In response to some embodiments, the first time information is any moment in the current period of the continuous observation sliding period. Selecting the first beam feature set or the second beam feature set as the acquisition source of the wireless channel state information includes:

[0506] When the second quantity of the preset result in the feature recognition result corresponding to the first-time information meets the quantity requirement, and the radio resource control connection of the communication device does not undergo reconfiguration or release, determine that the acquisition source corresponding to the radio channel state information within the second-time information is the dynamic beam feature acquisition source, where the second-time information is the time information before the next feature recognition result is not obtained.

[0507] In response to some embodiments, the first-time information is any moment in the current period of the continuous observation sliding period. Selecting the first beam feature set or the second beam feature set as the acquisition source of the radio channel state information includes:

[0508] When the second quantity of the preset result in the feature recognition result corresponding to the first-time information does not meet the quantity requirement, determine that the acquisition source corresponding to the radio channel state information within the second-time information is the static beam feature acquisition source;

[0509] Before the feature recognition result corresponding to the second-time information is not obtained, observe the update information corresponding to the first-time information, and use the updated first-time information as the first-time information to re-determine the acquisition source corresponding to the radio channel state information within the second-time information. Among them, the first-time information is the sliding observation time window length, and the first-time information is the preset duration or the period corresponding to the effective wide and narrow beam effect recognition results of the continuous preset sliding observation times.

[0510] Among them, the quantity requirement can be, for example, that the ratio of the second quantity to the fourth quantity is greater than the eighteenth threshold. Among them, the fourth quantity can be, for example, the total number corresponding to the wide and narrow beam effect recognition results corresponding to the first-time information.

[0511] Among them, the nineteenth threshold can be, for example, the observation ratio threshold Rbf, and its value range can be, for example, 60% - 90%. Among them, the value range of the sliding observation time window length Tobs corresponding to the continuous observation Tobs sliding window can be 50 - 100 ms or the period corresponding to the continuous Nbf effective wide and narrow beam effect recognition results, where Nbf is the number of sliding observations, and the value range can be, for example, 20 - 50.

[0512] It should be noted that the various thresholds in the embodiments of the present disclosure do not specifically refer to a certain fixed threshold. For example, it can be adjusted according to the threshold modification instruction, or changed according to the network mode. The embodiments of the present disclosure do not limit this.

[0513] In some or related embodiments, the current resident cell of a communication device is obtained; in response to the network mode information corresponding to the current resident cell and the downlink beamforming determination order, the downlink beamforming support information corresponding to the current network mode of the current resident cell is determined; thus, a beam sensing mechanism can be provided, which can determine the downlink beamforming support information in response to the network mode information and the downlink beamforming determination order, can improve the accuracy of determining the downlink beamforming support information, can determine that in the case of supporting downlink dynamic beamforming, according to the downlink static beam feature set and the downlink dynamic beam feature set, determine the feature recognition result, improve the accuracy of determining the feature recognition result, can improve the accuracy of determining the acquisition source corresponding to the wireless channel state information, and reduce the situation where the acquisition accuracy of the wireless channel state information required for channel estimation is poor due to the wide and narrow beam effects, can improve the receiving state of the communication device, enhance the robustness of the downlink receiving performance, and improve the communication quality of the communication device. Secondly, the wide and narrow beam effect recognition result can be determined according to at least one threshold information or a preset beam sensing neural network model, and the feature recognition result can be determined in different ways, which can improve the accuracy of determining the acquisition source.

[0514] Figure 11 is a block diagram of a beam sensing device shown according to an exemplary embodiment. Referring to Figure 11 , the device 1100 includes:

[0515] A set acquisition unit 1101, configured to acquire a first beam feature set and a second beam feature set related to the current network mode;

[0516] A source determination unit 1102, configured to select the first beam feature set or the second beam feature set as the acquisition source of the wireless channel state information in response to that at least one first parameter of the first beam feature set and at least one second parameter of the second beam feature set satisfy a preset condition, where the first beam feature set is related to at least one first parameter, and the second beam feature set is related to at least one second parameter.

[0517] According to some embodiments, the source determination unit 1102 is further configured to:

[0518] Acquire a feature recognition result in response to an operation result between at least one first parameter of the first beam feature set and at least one second parameter of the second beam feature set and at least one threshold information, where the feature recognition result is used to indicate whether at least one first parameter of the first beam feature set and at least one second parameter of the second beam feature set satisfy a preset condition.

[0519] According to some embodiments, when the source determination unit 1102 is configured to obtain a feature recognition result in response to an operation result between at least one first parameter of the first beam feature set and at least one second parameter of the second beam feature set and at least one threshold information, it is specifically configured to:

[0520] Compare the difference result and / or ratio result between at least one first parameter of the first beam feature set and at least one second parameter of the second beam feature set with at least one threshold information to obtain a feature recognition result.

[0521] According to some embodiments, when the source determination unit 1102 is configured to obtain a feature recognition result in response to an operation result between at least one first parameter of the first beam feature set and at least one second parameter of the second beam feature set and at least one threshold information, it is specifically configured to:

[0522] In response to that a first difference between any second parameter and any first parameter is greater than a first threshold, determine that the feature recognition result is a preset result, where the first threshold characterizes a relative SINR metric threshold, and the preset result is used to indicate that at least one first parameter of the first beam feature set and at least one second parameter of the second beam feature set meet a preset condition.

[0523] According to some embodiments, where at least one first parameter includes at least one of the following: cell-specific reference signal - signal to interference plus noise ratio CRS - SINR, primary synchronization signal - signal to interference plus noise ratio PSS - SINR, and secondary synchronization signal - signal to interference plus noise ratio SSS - SINR; at least one second parameter includes at least one of the following: physical downlink shared channel - signal to interference plus noise ratio PDSCH - SINR;

[0524] Alternatively, where at least one first parameter includes at least one of the following: time-frequency tracking reference signal channel state information - signal to interference plus noise ratio TRS CSI - SINR and synchronization signal - signal to interference plus noise ratio SS - SINR; at least one second parameter includes at least one of the following: physical downlink shared channel - time-frequency tracking reference signal PDSCH - SINR and physical downlink control channel - signal to interference plus noise ratio PDCCH - SINR.

[0525] According to some embodiments, when the source determination unit 1102 is configured to obtain a feature recognition result in response to an operation result between at least one first parameter of the first beam feature set and at least one second parameter of the second beam feature set and at least one threshold information, it is specifically configured to:

[0526] In response to a first ratio of any first parameter and any second parameter being greater than a second threshold, determining that the feature recognition result is a preset result, where the second threshold characterizes a relative maximum delay spread metric threshold, and the preset result is used to indicate that at least one first parameter of the first beam feature set and at least one second parameter of the second beam feature set satisfy a preset condition.

[0527] According to some embodiments, where at least one first parameter includes at least one of the following: cell-specific reference signal - maximum delay spread CRS-Tmax, and at least one second parameter includes at least one of the following: physical downlink shared channel - maximum delay spread PDSCH-Tmax;

[0528] Or

[0529] At least one first parameter includes at least one of the following: time-frequency tracking reference signal - maximum delay spread TRS-Tmax, and at least one second parameter includes at least one of the following: physical downlink shared channel - maximum delay spread PDSCH-Tmax and physical downlink control channel - maximum delay spread PDCCH-Tmax.

[0530] According to some embodiments, when the source determination unit 1102 is used to obtain a feature recognition result in response to an operation result between at least one first parameter of the first beam feature set and at least one second parameter of the second beam feature set and at least one threshold information, it is specifically used for:

[0531] In response to a second ratio of any first parameter and any second parameter being greater than a third threshold, determining that the feature recognition result is a preset result, where the third threshold characterizes a relative root mean square delay spread metric threshold, and the preset result is used to indicate that at least one first parameter of the first beam feature set and at least one second parameter of the second beam feature set satisfy a preset condition.

[0532] According to some embodiments, where at least one first parameter includes at least one of the following: cell-specific reference signal - root mean square delay spread CRS-Trms, and at least one second parameter includes at least one of the following: physical downlink shared channel - root mean square delay spread PDSCH-Trms;

[0533] Or

[0534] At least one first parameter includes at least one of the following: time-frequency tracking reference signal - root mean square delay spread TRS-Trms, and at least one second parameter includes at least one of the following: physical downlink shared channel - root mean square delay spread PDSCH-Trms and physical downlink control channel - root mean square delay spread PDCCH-Trms.

[0535] According to some embodiments, when the source determination unit 1102 is configured to obtain a feature recognition result in response to an operation result between at least one first parameter of a first beam feature set and at least one second parameter of a second beam feature set and at least one threshold information, it is specifically configured to:

[0536] In response to that a second difference between any signal-to-interference-plus-noise ratio (SINR) in at least one second parameter and any SINR in at least one first parameter is greater than a fourth threshold, and a third ratio between any maximum Doppler in at least one second parameter and any maximum Doppler in at least one first parameter is less than a fifth threshold, determine that the feature recognition result is a preset result, where the fourth threshold represents a relative SINR metric threshold, the fifth threshold represents a relative maximum Doppler metric threshold, and the preset result is used to indicate that at least one first parameter of the first beam feature set and at least one second parameter of the second beam feature set satisfy a preset condition.

[0537] According to some embodiments, where at least one first parameter includes at least one of the following: CRS-SINR, PSS-SINR, and SSS-SINR, and cell-specific reference signal - maximum Doppler (CRS-Doppler), and at least one second parameter includes at least one of the following: PDSCH-SINR, physical downlink shared channel - maximum Doppler (PDSCH-Doppler);

[0538] Or,

[0539] At least one first parameter includes at least one of the following: TRS CSI-SINR, SS-SINR, and time-frequency tracking reference signal - maximum Doppler (TRS-Doppler), and at least one second parameter includes at least one of the following: PDSCH-SINR, PDCCH-SINR, physical downlink control channel - maximum Doppler (PDCCH-Doppler), and physical downlink shared channel - maximum Doppler (PDSCH-Doppler).

[0540] According to some embodiments, when the source determination unit 1102 is configured to obtain a feature recognition result in response to an operation result between at least one first parameter of a first beam feature set and at least one second parameter of a second beam feature set and at least one threshold information, it is specifically configured to:

[0541] In response to that a fourth ratio of any maximum delay spread Tmax in at least one second parameter and any maximum delay spread Tmax in at least one first parameter is greater than a sixth threshold, and a fifth ratio of any maximum Doppler in at least one second parameter and any maximum Doppler in at least one first parameter is less than a seventh threshold, determine that the feature recognition result is a preset result, where the sixth threshold represents a relative maximum delay spread index threshold, the seventh threshold represents a relative maximum Doppler index threshold, and the preset result is used to indicate that at least one first parameter of the first beam feature set and at least one second parameter of the second beam feature set meet the preset conditions.

[0542] According to some embodiments, where at least one first parameter includes at least one of the following: CRS-Tmax and cell-specific reference signal - maximum Doppler CRS-Doppler, and at least one second parameter includes at least one of the following: PDSCH-Doppler and PDCCH-Tmax;

[0543] Or,

[0544] At least one first parameter includes at least one of the following: TRS-Tmax and TRS-Doppler, and at least one second parameter includes at least one of the following: PDSCH-Tmax, PDCCH-Tmax, PDSCH-Doppler, and PDCCH-Doppler.

[0545] According to some embodiments, when the source determination unit 1102 is configured to obtain a feature recognition result in response to an operation result between at least one first parameter of the first beam feature set and at least one second parameter of the second beam feature set and at least one threshold information, it is specifically configured to:

[0546] In response to that a sixth ratio of any root mean square delay spread Trms in at least one second parameter and any root mean square delay spread Trms in at least one first parameter is greater than an eighth threshold, and a seventh ratio of any maximum Doppler in at least one second parameter and any maximum Doppler in at least one first parameter is less than a ninth threshold, determine that the feature recognition result is a preset result, where the eighth threshold represents a relative root mean square delay spread threshold, the ninth threshold represents a relative maximum Doppler index threshold, and the preset result is used to indicate that at least one first parameter of the first beam feature set and at least one second parameter of the second beam feature set meet the preset conditions.

[0547] According to some embodiments, at least one first parameter includes at least one of the following: CRS-Trms and CRS-Dopple, and at least one second parameter includes at least one of the following: PDSCH-Trms and PDSCH-Doppler;

[0548] Or

[0549] At least one first parameter includes at least one of the following: TRS-Trms and TRS-Doppler, and at least one second parameter includes at least one of the following: PDSCH-Trms, PDCCH-Trms, PDSCH-Doppler, and PDCCH-Doppler.

[0550] According to some embodiments, when the source determination unit 1102 is configured to obtain a feature recognition result in response to an operation result between at least one first parameter of a first beam feature set and at least one second parameter of a second beam feature set and at least one threshold information, it is specifically configured to:

[0551] In response to that a third difference between any SINR in at least one second parameter and any SINR in at least one first parameter is greater than a tenth threshold, and an eighth ratio between any maximum delay spread Tmax in at least one second parameter and any maximum delay spread Tmax in at least one first parameter is greater than an eleventh threshold, determine that the feature recognition result is a preset result, where the tenth threshold represents a relative SINR index threshold, the eleventh threshold represents a relative maximum delay spread index threshold, and the preset result is used to indicate that at least one first parameter of the first beam feature set and at least one second parameter of the second beam feature set meet a preset condition.

[0552] According to some embodiments, at least one first parameter includes at least one of the following: CRS-SINR, PSS-SINR, SSS-SINR, and CRS-Tmax, and at least one second parameter includes at least one of the following: PDSCH-SINR and PDSCH-Tmax;

[0553] Or,

[0554] At least one first parameter includes at least one of the following: TRS CSI-SINR, SS-SINR, and TRS-Tmax, and at least one second parameter includes at least one of the following: PDSCH-SINR, PDCCH-SINR, PDSCH-Tmax, and PDCCH-Tmax.

[0555] According to some embodiments, when the source determination unit 1102 is configured to obtain a feature recognition result in response to an operation result between at least one first parameter of a first beam feature set and at least one second parameter of a second beam feature set and at least one threshold information, it is specifically configured to:

[0556] In response to a fourth difference between any SINR in at least one second parameter and any SINR in at least one first parameter being greater than a twelfth threshold, and a ninth ratio between any maximum root mean square delay spread Trms in at least one second parameter and any maximum root mean square delay spread Trms in at least one first parameter being greater than a thirteenth threshold, determine that the feature recognition result is a preset result. The twelfth threshold represents a relative SINR index threshold, the thirteenth threshold represents a relative maximum root mean square delay spread, and the preset result is used to indicate that at least one first parameter of the first beam feature set and at least one second parameter of the second beam feature set meet a preset condition.

[0557] According to some embodiments, wherein at least one first parameter includes at least one of the following: CRS-SINR, PSS-SINR, and SSS-SINR and CRS-Trms, and at least one second parameter includes at least one of the following: PDSCH-SINR and PDSCH-Tmax;

[0558] Or,

[0559] At least one first parameter includes at least one of the following: TRS CSI-SINR, SS-SINR, and TRS-Trms, and at least one second parameter includes at least one of the following: PDSCH-SINR, PDCCH-SINR, PDSCH-Trms, and PDCCH-Trms.

[0560] According to some embodiments, when the source determination unit 1102 is configured to obtain a feature recognition result in response to an operation result between at least one first parameter of a first beam feature set and at least one second parameter of a second beam feature set and at least one threshold information, it is specifically configured to:

[0561] In response to that the fifth difference between any SINR among at least one second parameter and any SINR among at least one first parameter is greater than a fourteenth threshold, and the tenth ratio between any maximum delay spread Tmax among at least one second parameter and any maximum delay spread Tmax among at least one first parameter is greater than a fifteenth threshold, and the eleventh ratio between any maximum root-mean-square delay spread Trms among at least one second parameter and any maximum root-mean-square delay spread Trms among at least one first parameter is greater than a sixteenth threshold, determine that the feature recognition result is a preset result, where the fourteenth threshold represents the relative SINR index threshold, the fifteenth threshold represents the relative maximum delay spread index threshold, the sixteenth threshold represents the relative maximum root-mean-square delay spread, and the preset result is used to indicate that at least one first parameter of the first beam feature set and at least one second parameter of the second beam feature set meet the preset conditions.

[0562] According to some embodiments, where at least one first parameter includes at least one of the following: CRS-SINR, PSS-SINR, SSS-SINR, CRS-Tmax, and CRS-Trms, and at least one second parameter includes at least one of the following: PDSCH-SINR, PDSCH-Tmax, and PDSCH-Trms;

[0563] Or,

[0564] At least one first parameter includes at least one of the following: TRS CSI-SINR, SS-SINR, TRS-Tmax, and TRS-Trms, and at least one second parameter includes at least one of the following: PDSCH-SINR, PDCCH-SINR, PDSCH-Tmax, PDCCH-Tmax, PDSCH-Trms, and PDCCH-Trms.

[0565] According to some embodiments, the source determination unit 1102 is further configured to:

[0566] Input at least one first parameter of the first beam feature set and at least one second parameter of the second beam feature set into a preset beam perception neural network model, and obtain the feature recognition result output by the beam perception neural network model, where the feature recognition result is used to indicate whether at least one first parameter of the first beam feature set and at least one second parameter of the second beam feature set meet the preset conditions.

[0567] According to some embodiments, when the source determination unit 1102 is configured to input at least one first parameter of the first beam feature set and at least one second parameter of the second beam feature set into a preset beam perception neural network model and obtain the feature recognition result output by the beam perception neural network model, it is specifically configured to:

[0568] Input at least one first parameter of the first beam feature set and at least one second parameter of the second beam feature set into a preset beam perception neural network model to obtain a vector corresponding to the at least one first parameter and the at least one second parameter;

[0569] Perform recognition processing on the vector by using the activation function of the preset beam perception neural network model to obtain the feature recognition result output by the beam perception neural network model.

[0570] According to some embodiments, when the source determination unit 1102 is used to select the first beam feature set or the second beam feature set as the acquisition source of the wireless channel state information, it is specifically used for:

[0571] In response to the feature recognition result corresponding to the first time information satisfying the first result requirement and the radio resource control connection of the communication device not being reconfigured or released, determine that the acquisition source corresponding to the wireless channel state information within the second time information is a dynamic beam feature acquisition source, where the first time information is any moment in the current period of a continuous observation preset period, the second time information is the next preset period adjacent to the current period, and the first result requirement includes the result requirement that the feature recognition results corresponding to the first time information are all preset results or the result requirement that the first quantity of the preset results in the feature recognition results corresponding to the first time information meets the quantity requirement.

[0572] According to some embodiments, when the source determination unit 1102 is used to select the first beam feature set or the second beam feature set as the acquisition source of the wireless channel state information, it is specifically used for:

[0573] In response to the feature recognition result corresponding to the first time information satisfying the second result requirement, determine that the acquisition source corresponding to the wireless channel state information within the second time information is a static beam feature acquisition source, where the first time information is any moment in the current period of a continuous observation preset period, and the second result requirement includes the result requirement that the feature recognition results corresponding to the first time information are not all preset results or the result requirement that the first quantity of the preset results in the feature recognition results corresponding to the first time information does not meet the quantity requirement.

[0574] According to some embodiments, when the source determination unit 1102 is used to select the first beam feature set or the second beam feature set as the acquisition source of the wireless channel state information, it is specifically used for:

[0575] In response to the feature recognition result corresponding to the first time information meeting the first result requirement, and the radio resource control connection of the communication device not being reconfigured or released, determine that the acquisition source corresponding to the wireless channel state information within the second time information is the dynamic beam feature acquisition source, where the first time information is any moment in the current period of the continuous observation sliding period, the second time information is the time information before the next feature recognition result is not obtained, and the first result requirement includes the result requirement that the feature recognition results corresponding to the first time information are all preset results or the result requirement that the second quantity of the preset results in the feature recognition results corresponding to the first time information meets the quantity requirement.

[0576] According to some embodiments, when the source determination unit 1102 is used to select the first beam feature set or the second beam feature set as the acquisition source of the wireless channel state information, it is specifically used for:

[0577] In response to the feature recognition result corresponding to the first time information meeting the second result requirement, determine that the acquisition source corresponding to the wireless channel state information within the second time information is the static beam feature acquisition source, where the first time information is any moment in the current period of the continuous observation sliding period, the second time information is the time information before the next feature recognition result is not obtained, and the second result requirement includes the result requirement that the feature recognition results corresponding to the first time information are not all preset results or the result requirement that the second quantity of the preset results in the feature recognition results corresponding to the first time information does not meet the quantity requirement;

[0578] Before the feature recognition result corresponding to the second time information is not obtained, observe the update information corresponding to the first time information, and use the updated first time information as the first time information to re-determine the acquisition source corresponding to the wireless channel state information within the second time information.

[0579] According to some embodiments, the first beam feature set includes a downlink static beam feature set, and the second beam feature set includes a downlink dynamic beam feature set.

[0580] According to some embodiments, the first beam feature set includes a downlink static beam feature set, and the second beam feature set includes a downlink dynamic beam feature set. When the set acquisition unit 1101 is used to acquire the first beam feature set and the second beam feature set related to the current network mode, it is specifically used for:

[0581] Extract features from the synchronization signal and / or reference signal of the broadband wireless communication system with downlink beamforming enabled to obtain the downlink static beam feature set related to the current network mode;

[0582] Extract the features of the demodulation reference signal of a broadband wireless communication system that enables downlink dynamic beamforming, and obtain a set of downlink dynamic beam features related to the current network mode.

[0583] According to some embodiments, the set obtaining unit 1101 is further configured to:

[0584] Obtain the current resident cell of the communication device;

[0585] In response to the network mode information corresponding to the current resident cell and the downlink beamforming determination order, determine the downlink beamforming support information corresponding to the current network mode of the current resident cell.

[0586] According to some embodiments, when the set obtaining unit 1101 is configured to determine the downlink beamforming support information corresponding to the current network mode of the current resident cell in response to the network mode information corresponding to the current resident cell and the downlink beamforming determination order, it is specifically configured to:

[0587] Obtain the network mode information corresponding to the current resident cell;

[0588] In response to the network mode information corresponding to the current resident cell being the first network mode, determine that the communication device is in the radio resource control connected state;

[0589] In response to the dedicated configuration signaling indicating that the communication device is in the preset transmission mode, obtain the first scenario information corresponding to the current resident cell;

[0590] In response to the first scenario information being the preset scenario information, determine that the downlink beamforming support information corresponding to the first network mode is that the first network mode supports downlink dynamic beamforming.

[0591] According to some embodiments, when the set obtaining unit 1101 is configured to determine the downlink beamforming support information corresponding to the current network mode of the current resident cell in response to the network mode information corresponding to the current resident cell and the downlink beamforming determination order, it includes:

[0592] Obtain the network mode information corresponding to the current resident cell;

[0593] In response to the network mode information corresponding to the current resident cell being the first network mode, determine that the communication device is in the radio resource control connected state;

[0594] In response to the dedicated configuration signaling indicating that the communication device is not in the preset transmission mode, or the first scenario information is not the preset scenario information, determine that the downlink beamforming support information corresponding to the first network mode is that the first network mode does not support downlink dynamic beamforming.

[0595] According to some embodiments, the set acquisition unit 1101 is configured to determine the downlink beamforming support information corresponding to the current network mode of the current resident cell in response to the network mode information corresponding to the current resident cell and the downlink beamforming determination sequence, including:

[0596] In response to the network mode information corresponding to the current resident cell not being the first network mode, determine that the network mode information corresponding to the current resident cell is the second network mode;

[0597] In response to the frequency range information of the current resident cell being the first frequency range, the communication mode of the current resident cell being time division duplex, and the second scenario information corresponding to the current resident cell being the preset scenario information, determine that the downlink beamforming support information corresponding to the second network mode is that the second network mode supports downlink dynamic beamforming.

[0598] According to some embodiments, when the set acquisition unit 1101 is configured to determine the downlink beamforming support information corresponding to the current network mode of the current resident cell in response to the network mode information corresponding to the current resident cell and the downlink beamforming determination sequence, it is specifically configured to:

[0599] In response to the network mode information corresponding to the current resident cell not being the first network mode, determine that the network mode information corresponding to the current resident cell is the second network mode;

[0600] In response to the frequency range information corresponding to the current resident cell not being the first frequency range, or the communication mode of the current resident cell not being time division duplex, or the second scenario information corresponding to the current resident cell not being the preset scenario information, determine that the downlink beamforming support information corresponding to the second network mode is that the second network mode does not support downlink dynamic beamforming.

[0601] According to some embodiments, when the set acquisition unit 1101 is configured to determine the downlink beamforming support information corresponding to the current network mode of the current resident cell in response to the network mode information corresponding to the current resident cell and the downlink beamforming determination sequence, it is specifically configured to:

[0602] In response to the network mode information corresponding to the current resident cell not being the second network mode, determine whether the network mode information corresponding to the current resident cell is the third network mode;

[0603] In response to determining that the network mode information corresponding to the current resident cell is the third network mode, use the determination method corresponding to the third network mode to determine the downlink beamforming support information corresponding to the current network mode of the current resident cell.

[0604] According to some embodiments, the set acquisition unit 1101 is further configured to:

[0605] In response to radio resource control (RRC) signaling reconfiguration occurring in the RRC connected state, re-determine the downlink beamforming support information corresponding to the current network mode of the current resident cell.

[0606] Regarding the apparatus in the above embodiments, the specific manner in which each module performs operations has been described in detail in the embodiments related to the method, and will not be elaborated here.

[0607] In some or related embodiments, a set acquisition unit is configured to acquire a first beam feature set and a second beam feature set related to the current network mode; a source determination unit is configured to select the first beam feature set or the second beam feature set as the acquisition source of the radio channel state information in response to at least one first parameter of the first beam feature set and at least one second parameter of the second beam feature set satisfying a preset condition, where the first beam feature set is related to at least one first parameter, and the second beam feature set is related to at least one second parameter. Therefore, a beam sensing mechanism can be provided, and the acquisition source corresponding to the radio channel state information can be determined by whether at least one first parameter of the first beam feature set and at least one second parameter of the second beam feature set satisfy the preset condition, which can improve the accuracy of determining the acquisition source corresponding to the radio channel state information, reduce the situation where the radio channel state information determined is inaccurate due to the mismatch between the radio channel state information required for channel estimation and the acquisition source, improve the accuracy of acquiring the radio channel state information, improve the receiving state of the communication device, and improve the communication quality of the communication device.

[0608] Figure 12 FIG. shows a schematic block diagram of an exemplary communication device 1200 that can be used to implement the embodiments of the present disclosure. The communication device is intended to represent various forms of digital computers, such as, for example, laptop computers, desktop computers, workstations, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. The communication device can also represent various forms of mobile devices, such as, for example, personal digital assistants, cellular telephones, smart phones, wearable communication devices, and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely illustrative and are not intended to limit the implementation of the present disclosure described and / or claimed herein.

[0609] As Figure 12As shown, the communication device 1200 includes a computing unit 1201, which can perform various appropriate actions and processes according to a computer program stored in a read-only memory (ROM) 1202 or a computer program loaded from a storage unit 1208 into a random access memory (RAM) 1203. In the RAM 1203, various programs and data required for the operation of the communication device 1200 can also be stored. The computing unit 1201, the ROM 1202, and the RAM 1203 are connected to each other via a bus 1204. An input / output (I / O) interface 1205 is also connected to the bus 1204.

[0610] Multiple components in the communication device 1200 are connected to the I / O interface 1205, including: an input unit 1206, such as a keyboard, a mouse, etc.; an output unit 1207, such as various types of displays, speakers, etc.; a storage unit 1208, such as a magnetic disk, an optical disk, etc.; and a communication unit 1209, such as a network card, a modem, a wireless communication transceiver, etc. The communication unit 1209 allows the communication device 1200 to exchange information / data with other communication devices via a computer network such as the Internet and / or various telecommunication networks.

[0611] The computing unit 1201 can be various general-purpose and / or special-purpose processing components with processing and computing capabilities. Some examples of the computing unit 1201 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various dedicated artificial intelligence (AI) computing chips, various computing units running machine learning model algorithms, a digital signal processor (DSP), and any appropriate processor, controller, microcontroller, etc. The computing unit 1201 executes the various methods and processes described above, such as beam sensing or model training methods. For example, in some embodiments, the beam sensing or model training method can be implemented as a computer software program, which is tangibly contained in a machine-readable medium, such as the storage unit 1208. In some embodiments, part or all of the computer program can be loaded and / or installed onto the communication device 1200 via the ROM 1202 and / or the communication unit 1209. When the computer program is loaded into the RAM 1203 and executed by the computing unit 1201, one or more steps of the beam sensing or model training method described above can be executed. Alternatively, in other embodiments, the computing unit 1201 can be configured to execute the beam sensing method by any other appropriate means (e.g., by means of firmware).

[0612] Please refer to Figure 13 is a block diagram of a chip shown according to an exemplary embodiment. As Figure 13The chip 1300 shown includes a processor 1301 and an interface 1302. Optionally, a memory 1303 may also be included. Among them, the number of processors 1301 can be one or more, and the number of interfaces 1302 can be multiple.

[0613] The various embodiments of the systems and techniques described above in this document can be implemented in digital electronic circuitry, integrated circuit systems, field programmable gate arrays (FPGA), application specific integrated circuits (ASIC), application specific standard products (ASSP), systems on a chip (SOC), complex programmable logic devices (CPLD), computer hardware, firmware, software, and / or combinations thereof. These various embodiments can include: being implemented in one or more computer programs that can be executed and / or interpreted on a programmable system including at least one programmable processor, where the programmable processor can be a dedicated or general-purpose programmable processor, and can receive data and instructions from a storage system, at least one input device, and at least one output device, and transmit the data and instructions to the storage system, the at least one input device, and the at least one output device.

[0614] The program code for implementing the methods of the present disclosure can be written in any combination of one or more programming languages. These program codes can be provided to a processor or controller of a general-purpose computer, a dedicated computer, or other programmable data processing devices, such that when the program codes are executed by the processor or controller, the functions / operations specified in the flowcharts and / or block diagrams are implemented. The program codes can be executed entirely on the machine, partially on the machine, executed partially on the machine and partially on a remote machine as an independent software package, or executed entirely on a remote machine or server.

[0615] In the context of the present disclosure, a machine-readable medium can be a tangible medium that can contain or store a program for use by or in connection with an instruction execution system, apparatus, or device. A machine-readable medium can be a machine-readable signal medium or a machine-readable storage medium. A machine-readable medium can include, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, apparatus, or devices, or any suitable combination of the foregoing. More specific examples of machine-readable storage media would include electrical connections based on one or more wires, portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fibers, portable compact disk read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination of the foregoing.

[0616] To provide interaction with a user, the systems and techniques described herein can be implemented on a computer having: a display device for displaying information to the user (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor); and a keyboard and a pointing device (e.g., a mouse or a trackball), by which the user can provide input to the computer. Other kinds of devices can also be used to provide interaction with the user; for example, the feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user can be received in any form (including acoustic input, voice input, or tactile input).

[0617] The systems and techniques described herein can be implemented in a computing system including backend components (e.g., as a data server), or a computing system including middleware components (e.g., an application server), or a computing system including frontend components (e.g., a user computer having a graphical user interface or a web browser through which the user can interact with an implementation of the systems and techniques described herein), or a computing system including any combination of such backend components, middleware components, or frontend components. The components of the system can be interconnected to each other by digital data communication in any form or medium (e.g., a communication network). Examples of communication networks include: local area network (LAN), wide area network (WAN), the Internet, and blockchain networks.

[0618] A computer system can include a client and a server. The client and the server are generally far from each other and usually interact through a communication network. The relationship between the client and the server is generated by computer programs running on the respective computers and having a client-server relationship with each other. The server can be a cloud server, also known as a cloud computing server or a cloud host, which is a host product in the cloud computing service system, solving the defects of difficult management and weak business scalability existing in traditional physical hosts and VPS services ("Virtual Private Server", or simply "VPS"). The server can also be a server of a distributed system, or a server combined with blockchain.

[0619] It should be understood that various forms of the processes shown above can be used, with steps reordered, added, or deleted. For example, the steps recited in the present disclosure can be executed in parallel, sequentially, or in a different order, as long as the desired results of the technical solutions disclosed in the present disclosure can be achieved, and no limitation is imposed herein.

[0620] The above specific embodiments do not constitute a limitation on the scope of protection of the present disclosure. Those skilled in the art should understand that various modifications, combinations, sub-combinations, and substitutions can be made according to design requirements and other factors. Any modifications, equivalent substitutions, and improvements made within the spirit and principle of the present disclosure shall be included within the scope of protection of the present disclosure.

Claims

1. A beam sensing method, characterized in that, Including: Obtaining a first beam feature set and a second beam feature set related to the current network mode; Obtaining a feature recognition result in response to an operation result between at least one first parameter of the first beam feature set and at least one second parameter of the second beam feature set and at least one threshold information, where the feature recognition result is used to indicate whether at least one first parameter of the first beam feature set and at least one second parameter of the second beam feature set meet a preset condition; Selecting the first beam feature set or the second beam feature set as a source for obtaining wireless channel state information in response to at least one first parameter of the first beam feature set and at least one second parameter of the second beam feature set meeting the preset condition, where the first beam feature set is related to the at least one first parameter and the second beam feature set is related to the at least one second parameter.

2. The method according to claim 1, wherein The obtaining the feature recognition result in response to an operation result between at least one first parameter of the first beam feature set and at least one second parameter of the second beam feature set and at least one threshold information includes: Comparing a difference result and / or a ratio result between at least one first parameter of the first beam feature set and at least one second parameter of the second beam feature set with at least one threshold information to obtain the feature recognition result.

3. The method according to claim 1 or 2, characterized in that, The obtaining the feature recognition result in response to an operation result between at least one first parameter of the first beam feature set and at least one second parameter of the second beam feature set and at least one threshold information includes: Determining that the feature recognition result is a preset result in response to a first difference between any second parameter and any first parameter being greater than a first threshold, where the first threshold represents a relative SINR index threshold, and the preset result is used to indicate that at least one first parameter of the first beam feature set and at least one second parameter of the second beam feature set meet the preset condition.

4. The method according to claim 3, wherein Wherein, The at least one first parameter includes at least one of the following: cell-specific reference signal-signal to interference plus noise ratio CRS-SINR, primary synchronization signal-signal to interference plus noise ratio PSS-SINR, and secondary synchronization signal-signal to interference plus noise ratio SSS-SINR; the at least one second parameter includes at least one of the following: physical downlink shared channel-signal to interference plus noise ratio PDSCH-SINR; Or, wherein, the at least one first parameter includes at least one of the following: time-frequency tracking reference signal channel state information-signal to interference plus noise ratio TRS CSI-SINR and synchronization signal-signal to interference plus noise ratio SS-SINR; the at least one second parameter includes at least one of the following: physical downlink shared channel-time-frequency tracking reference signal PDSCH-SINR and physical downlink control channel-signal to interference plus noise ratio PDCCH-SINR.

5. The method according to claim 1 or 2, characterized in that, Obtaining a feature recognition result according to an operation result between at least one first parameter corresponding to the first beam feature set and at least one second parameter corresponding to the second beam feature set and at least one threshold information, includes: When a first ratio of any one of the first parameters and any one of the second parameters is greater than a second threshold, determining that the feature recognition result is a preset result, where the second threshold represents a relative maximum delay spread metric threshold, and the preset result is used to indicate that at least one first parameter of the first beam feature set and at least one second parameter of the second beam feature set satisfy the preset condition.

6. The method according to claim 5, wherein Wherein, The at least one first parameter includes at least one of the following: cell-specific reference signal - maximum delay spread CRS-Tmax, and the at least one second parameter includes at least one of the following: physical downlink shared channel - maximum delay spread PDSCH-Tmax; Or The at least one first parameter includes at least one of the following: time-frequency tracking reference signal - maximum delay spread TRS-Tmax, and the at least one second parameter includes at least one of the following: physical downlink shared channel - maximum delay spread PDSCH-Tmax and physical downlink control channel - maximum delay spread PDCCH-Tmax.

7. The method according to claim 1 or 2, characterized in that, Obtaining a feature recognition result according to an operation result between at least one first parameter corresponding to the first beam feature set and at least one second parameter corresponding to the second beam feature set and at least one threshold information, includes: When a second ratio of any one of the first parameters and any one of the second parameters is greater than a third threshold, determining that the feature recognition result is a preset result, where the third threshold represents a relative root mean square delay spread metric threshold, and the preset result is used to indicate that at least one first parameter of the first beam feature set and at least one second parameter of the second beam feature set satisfy the preset condition.

8. The method according to claim 7, wherein Wherein, The at least one first parameter includes at least one of the following: cell-specific reference signal - root mean square delay spread CRS-Trms, and the at least one second parameter includes at least one of the following: physical downlink shared channel - root mean square delay spread PDSCH-Trms; Or The at least one first parameter includes at least one of the following: time-frequency tracking reference signal - root mean square delay spread TRS-Trms, and the at least one second parameter includes at least one of the following: physical downlink shared channel - root mean square delay spread PDSCH-Trms and physical downlink control channel - root mean square delay spread PDCCH-Trms.

9. The method according to claim 1 or 2, characterized in that, Obtaining a feature recognition result according to an operation result between at least one first parameter corresponding to the first beam feature set and at least one second parameter corresponding to the second beam feature set and at least one threshold information, includes: In response to a second difference between any signal-to-interference-plus-noise ratio (SINR) in the at least one second parameter and any SINR in the at least one first parameter being greater than a fourth threshold, and a third ratio between any maximum Doppler in the at least one second parameter and any maximum Doppler in the at least one first parameter being less than a fifth threshold, determine that the feature recognition result is a preset result, where the fourth threshold represents a relative SINR metric threshold, the fifth threshold represents a relative maximum Doppler metric threshold, and the preset result is used to indicate that at least one first parameter of the first beam feature set and at least one second parameter of the second beam feature set meet the preset conditions.

10. The method according to claim 9, wherein Wherein, the at least one first parameter includes at least one of the following: CRS-SINR, PSS-SINR, and SSS-SINR, and cell-specific reference signal - maximum Doppler (CRS-Doppler), and the at least one second parameter includes at least one of the following: PDSCH-SINR, physical downlink shared channel - maximum Doppler (PDSCH-Doppler); Or, the at least one first parameter includes at least one of the following: TRS CSI-SINR, SS-SINR, and time-frequency tracking reference signal - maximum Doppler (TRS-Doppler), and the at least one second parameter includes at least one of the following: PDSCH-SINR, PDCCH-SINR, physical downlink control channel - maximum Doppler (PDCCH-Doppler), and physical downlink shared channel - maximum Doppler (PDSCH-Doppler).

11. The method according to claim 1 or 2, characterized in that, The obtaining of the feature recognition result in response to an operation result between at least one first parameter of the first beam feature set and at least one second parameter of the second beam feature set and at least one threshold information includes: In response to a fourth ratio between any maximum delay spread (Tmax) in the at least one second parameter and any Tmax in the at least one first parameter being greater than a sixth threshold, and a fifth ratio between any maximum Doppler in the at least one second parameter and any maximum Doppler in the at least one first parameter being less than a seventh threshold, determine that the feature recognition result is a preset result, where the sixth threshold represents a relative maximum delay spread metric threshold, the seventh threshold represents a relative maximum Doppler metric threshold, and the preset result is used to indicate that at least one first parameter of the first beam feature set and at least one second parameter of the second beam feature set meet the preset conditions.

12. The method according to claim 11, wherein Wherein, the at least one first parameter includes at least one of the following: CRS-Tmax and cell-specific reference signal - maximum Doppler (CRS-Doppler), and the at least one second parameter includes at least one of the following: PDSCH-Doppler and PDCCH-Tmax; Or, The at least one first parameter includes at least one of the following: TRS-Tmax and TRS-Doppler, and the at least one second parameter includes at least one of the following: PDSCH-Tmax, PDCCH-Tmax, PDSCH-Doppler, and PDCCH-Doppler.

13. The method according to claim 1 or 2, characterized in that, Obtaining a feature recognition result based on an operation result between at least one first parameter of the first beam feature set and at least one second parameter of the second beam feature set, and at least one threshold information, includes: Determining that the feature recognition result is a preset result in response to a sixth ratio of any root mean square delay spread Trms in the at least one second parameter to any root mean square delay spread Trms in the at least one first parameter being greater than an eighth threshold, and a seventh ratio of any maximum Doppler Doppler in the at least one second parameter to any maximum Doppler Doppler in the at least one first parameter being less than a ninth threshold, where the eighth threshold represents a relative root mean square delay spread threshold, the ninth threshold represents a relative maximum Doppler index threshold, and the preset result is used to indicate that at least one first parameter of the first beam feature set and at least one second parameter of the second beam feature set satisfy the preset condition.

14. The method according to claim 13, wherein Wherein, The at least one first parameter includes at least one of the following: CRS-Trms and CRS-Dopple, and the at least one second parameter includes at least one of the following: PDSCH-Trms and PDSCH-Doppler; or The at least one first parameter includes at least one of the following: TRS-Trms and TRS-Doppler, and the at least one second parameter includes at least one of the following: PDSCH-Trms, PDCCH-Trms, PDSCH-Doppler, and PDCCH-Doppler.

15. The method according to claim 1 or 2, characterized in that, Obtaining a feature recognition result based on an operation result between at least one first parameter of the first beam feature set and at least one second parameter of the second beam feature set, and at least one threshold information, includes: Determining that the feature recognition result is a preset result in response to a third difference between any SINR in the at least one second parameter and any SINR in the at least one first parameter being greater than a tenth threshold, and an eighth ratio of any maximum delay spread Tmax in the at least one second parameter to any maximum delay spread Tmax in the at least one first parameter being greater than an eleventh threshold, where the tenth threshold represents a relative SINR index threshold, the eleventh threshold represents a relative maximum delay spread index threshold, and the preset result is used to indicate that at least one first parameter of the first beam feature set and at least one second parameter of the second beam feature set satisfy the preset condition.

16. The method according to claim 15, wherein Wherein, The at least one first parameter includes at least one of the following: CRS-SINR, PSS-SINR, SSS-SINR, and CRS-Tmax, and the at least one second parameter includes at least one of the following: PDSCH-SINR and PDSCH-Tmax; Or, The at least one first parameter includes at least one of the following: TRS CSI-SINR, SS-SINR, and TRS-Tmax, and the at least one second parameter includes at least one of the following: PDSCH-SINR, PDCCH-SINR, PDSCH-Tmax, and PDCCH-Tmax.

17. The method according to claim 1 or 2, characterized in that, Obtaining a feature recognition result according to an operation result between at least one first parameter of the first beam feature set and at least one second parameter of the second beam feature set and at least one threshold information includes: In response to a fourth difference between any SINR in the at least one second parameter and any SINR in the at least one first parameter being greater than a twelfth threshold, and a ninth ratio between any maximum root mean square delay spread Trms in the at least one second parameter and any maximum root mean square delay spread Trms in the at least one first parameter being greater than a thirteenth threshold, determining that the feature recognition result is a preset result, where the twelfth threshold represents a relative SINR index threshold, the thirteenth threshold represents a relative maximum root mean square delay spread, and the preset result is used to indicate that at least one first parameter of the first beam feature set and at least one second parameter of the second beam feature set satisfy the preset condition.

18. The method according to claim 17, wherein Wherein, The at least one first parameter includes at least one of the following: CRS-SINR, PSS-SINR, SSS-SINR, and CRS-Trms, and the at least one second parameter includes at least one of the following: PDSCH-SINR and PDSCH-Tmax; Or, The at least one first parameter includes at least one of the following: TRS CSI-SINR, SS-SINR, and TRS-Trms, and the at least one second parameter includes at least one of the following: PDSCH-SINR, PDCCH-SINR, PDSCH-Trms, and PDCCH-Trms.

19. The method according to claim 1 or 2, characterized in that, Obtaining a feature recognition result according to an operation result between at least one first parameter of the first beam feature set and at least one second parameter of the second beam feature set and at least one threshold information includes: In response to that any fifth difference between any SINR among the at least one second parameter and any SINR among the at least one first parameter is greater than a fourteenth threshold, any tenth ratio between any maximum delay spread Tmax among the at least one second parameter and any maximum delay spread Tmax among the at least one first parameter is greater than a fifteenth threshold, and any eleventh ratio between any maximum root-mean-square delay spread Trms among the at least one second parameter and any maximum root-mean-square delay spread Trms among the at least one first parameter is greater than a sixteenth threshold, determine that the feature recognition result is a preset result, where the fourteenth threshold represents a relative SINR metric threshold, the fifteenth threshold represents a relative maximum delay spread metric threshold, the sixteenth threshold represents a relative maximum root-mean-square delay spread, and the preset result is used to indicate that at least one first parameter of the first beam feature set and at least one second parameter of the second beam feature set meet the preset conditions.

20. The method according to claim 19, wherein Wherein, the at least one first parameter includes at least one of the following: CRS-SINR, PSS-SINR, SSS-SINR, CRS-Tmax, and CRS-Trms, and the at least one second parameter includes at least one of the following: PDSCH-SINR, PDSCH-Tmax, and PDSCH-Trms; Or, the at least one first parameter includes at least one of the following: TRS CSI-SINR, SS-SINR, TRS-Tmax, and TRS-Trms, and the at least one second parameter includes at least one of the following: PDSCH-SINR, PDCCH-SINR, PDSCH-Tmax, PDCCH-Tmax, PDSCH-Trms, and PDCCH-Trms.

21. The method according to claim 1, wherein The selection of the first beam feature set or the second beam feature set as the acquisition source of the radio channel state information includes: In response to that the feature recognition result corresponding to the first time information meets the first result requirement, and the radio resource control connection of the communication device has not been reconfigured or released, determine that the acquisition source corresponding to the radio channel state information within the second time information is a dynamic beam feature acquisition source, where the first time information is any moment of the current period in a continuous observation preset period, the second time information is the next preset period adjacent to the current period, and the first result requirement includes the result requirement that the feature recognition results corresponding to the first time information are all preset results or the result requirement that the first quantity of the preset results in the feature recognition results corresponding to the first time information meets the quantity requirement.

22. The method according to claim 1, wherein The selection of the first beam feature set or the second beam feature set as the acquisition source of the radio channel state information includes: In response to the feature recognition result corresponding to the first time information meeting the second result requirement, determine that the acquisition source corresponding to the wireless channel state information within the second time information is a static beam feature acquisition source, where the first time information is any moment of the current period in a continuous observation preset period, and the second result requirement includes the result requirement that the feature recognition results corresponding to the first time information are not all preset results or the result requirement that the first quantity of the preset results in the feature recognition results corresponding to the first time information does not meet the quantity requirement.

23. The method according to claim 1, wherein The selecting the first beam feature set or the second beam feature set as the acquisition source of the wireless channel state information includes: In response to the feature recognition result corresponding to the first time information meeting the first result requirement and the radio resource control connection of the communication device not undergoing reconfiguration or release, determine that the acquisition source corresponding to the wireless channel state information within the second time information is a dynamic beam feature acquisition source, where the first time information is any moment of the current period in a continuous observation sliding period, the second time information is the time information before the next feature recognition result is not obtained, and the first result requirement includes the result requirement that the feature recognition results corresponding to the first time information are all preset results or the result requirement that the second quantity of the preset results in the feature recognition results corresponding to the first time information meets the quantity requirement.

24. The method according to claim 1, characterized in that, The selecting the first beam feature set or the second beam feature set as the acquisition source of the wireless channel state information includes: In response to the feature recognition result corresponding to the first time information meeting the second result requirement, determine that the acquisition source corresponding to the wireless channel state information within the second time information is a static beam feature acquisition source, where the first time information is any moment of the current period in a continuous observation sliding period, the second time information is the time information before the next feature recognition result is not obtained, and the second result requirement includes the result requirement that the feature recognition results corresponding to the first time information are not all preset results or the result requirement that the second quantity of the preset results in the feature recognition results corresponding to the first time information does not meet the quantity requirement; Before the feature recognition result corresponding to the second time information is not obtained, observe the update information corresponding to the first time information, and use the updated first time information as the first time information to re-determine the acquisition source corresponding to the wireless channel state information within the second time information.

25. The method according to any one of claims 21 to 24, characterized in that Wherein, The first beam feature set includes a downlink static beam feature set, and the second beam feature set includes a downlink dynamic beam feature set.

26. The method according to claim 1, characterized in that, Wherein, The first beam feature set includes a downlink static beam feature set, and the second beam feature set includes a downlink dynamic beam feature set. The obtaining the first beam feature set and the second beam feature set related to the current network mode includes: Extract features from the synchronization signal and / or reference signal of the broadband wireless communication system with downlink beamforming enabled to obtain the downlink static beam feature set related to the current network mode; Extract the features of the demodulation reference signal of a broadband wireless communication system with downlink dynamic beamforming enabled, and obtain the set of downlink dynamic beam features related to the current network mode.

27. The method according to claim 1, wherein The method further includes: Obtain the current resident cell of the communication device; In response to the network mode information corresponding to the current resident cell and the downlink beamforming determination order, determine the downlink beamforming support information corresponding to the current network mode of the current resident cell.

28. The method according to claim 27, wherein The determining the downlink beamforming support information corresponding to the current network mode of the current resident cell in response to the network mode information corresponding to the current resident cell and the downlink beamforming determination order includes: Obtain the network mode information corresponding to the current resident cell; In response to the network mode information corresponding to the current resident cell being the first network mode, determine that the communication device is in the radio resource control connected state; In response to the dedicated configuration signaling indicating that the communication device is in the preset transmission mode, obtain the first scenario information corresponding to the current resident cell; In response to the first scenario information being the preset scenario information, determine that the downlink beamforming support information corresponding to the first network mode is that the first network mode supports downlink dynamic beamforming.

29. The method according to claim 27, wherein The determining the downlink beamforming support information corresponding to the current network mode of the current resident cell in response to the network mode information corresponding to the current resident cell and the downlink beamforming determination order includes: Obtain the network mode information corresponding to the current resident cell; In response to the network mode information corresponding to the current resident cell being the first network mode, determine that the communication device is in the radio resource control connected state; In response to the dedicated configuration signaling indicating that the communication device is not in the preset transmission mode, or the first scenario information corresponding to the current resident cell is not the preset scenario information, determine that the downlink beamforming support information corresponding to the first network mode is that the first network mode does not support downlink dynamic beamforming.

30. The method according to claim 27, wherein The determining the downlink beamforming support information corresponding to the current network mode of the current resident cell in response to the network mode information corresponding to the current resident cell and the downlink beamforming determination order includes: In response to the network mode information corresponding to the current resident cell not being the first network mode, determine that the network mode information corresponding to the current resident cell is the second network mode; In response to the frequency range information of the current resident cell being the first frequency range, the communication mode of the current resident cell being time division duplex, and the second scenario information corresponding to the current resident cell being the preset scenario information, determine that the downlink beamforming support information corresponding to the second network mode is that the second network mode supports downlink dynamic beamforming.

31. The method according to claim 27, characterized in that, The determining the downlink beamforming support information corresponding to the current network mode of the current resident cell in response to the network mode information corresponding to the current resident cell and the downlink beamforming determination order includes: In response to the network mode information corresponding to the current resident cell not being the first network mode, determine that the network mode information corresponding to the current resident cell is the second network mode; In response to the frequency range information corresponding to the current serving cell not being the first frequency range, or the communication mode of the current serving cell not being time division duplex, or the second scenario information corresponding to the current serving cell not being the preset scenario information, it is determined that the downlink beamforming support information corresponding to the second network mode is that the second network mode does not support downlink dynamic beamforming.

32. The method according to claim 27, wherein The determining the downlink beamforming support information corresponding to the current network mode of the current serving cell in response to the network mode information corresponding to the current serving cell and the downlink beamforming determination sequence includes: In response to the network mode information corresponding to the current serving cell not being the second network mode, determining whether the network mode information corresponding to the current serving cell is the third network mode; In response to determining that the network mode information corresponding to the current serving cell is the third network mode, using the determination method corresponding to the third network mode to determine the downlink beamforming support information corresponding to the current network mode of the current serving cell.

33. The method according to any one of claims 28 and 29, characterized in that, The method further includes: In response to a radio resource control signaling reconfiguration occurring in the radio resource control connected state, re-determining the downlink beamforming support information corresponding to the current network mode of the current serving cell.

34. A beam sensing device, characterized in that, It includes: An aggregation acquisition unit, configured to acquire a first beam feature set and a second beam feature set related to the current network mode; A source determination unit, configured to acquire a feature recognition result in response to an operation result between at least one first parameter of the first beam feature set and at least one second parameter of the second beam feature set and at least one threshold information, where the feature recognition result is used to indicate whether at least one first parameter of the first beam feature set and at least one second parameter of the second beam feature set meet a preset condition; The source determination unit is further configured to, in response to at least one first parameter of the first beam feature set and at least one second parameter of the second beam feature set meeting the preset condition, select the first beam feature set or the second beam feature set as the acquisition source of the radio channel state information, where the first beam feature set is related to the at least one first parameter, and the second beam feature set is related to the at least one second parameter.

35. The device according to claim 34, characterized in that, The source determination unit is further configured to: Compare the difference result and / or ratio result between at least one first parameter of the first beam feature set and at least one second parameter of the second beam feature set with at least one threshold information to acquire a feature recognition result.

36. The device according to claim 34 or 35, characterized in that, The source determination unit is further configured to: In response to a first difference between any second parameter and any first parameter being greater than a first threshold, determining that the feature recognition result is a preset result, where the first threshold represents a relative SINR index threshold, and the preset result is used to indicate that at least one first parameter of the first beam feature set and at least one second parameter of the second beam feature set meet the preset condition.

37. The device according to claim 36, characterized in that Wherein, The at least one first parameter includes at least one of the following: cell-specific reference signal - signal to interference plus noise ratio (CRS-SINR), primary synchronization signal - signal to interference plus noise ratio (PSS-SINR), and secondary synchronization signal - signal to interference plus noise ratio (SSS-SINR); the at least one second parameter includes at least one of the following: physical downlink shared channel - signal to interference plus noise ratio (PDSCH-SINR). Alternatively, wherein the at least one first parameter includes at least one of the following: time-frequency tracking reference signal channel state information - signal to interference plus noise ratio (TRS CSI-SINR) and synchronization signal - signal to interference plus noise ratio (SS-SINR); the at least one second parameter includes at least one of the following: physical downlink shared channel - time-frequency tracking reference signal (PDSCH-SINR) and physical downlink control channel - signal to interference plus noise ratio (PDCCH-SINR).

38. The device according to claim 34 or 35, characterized in that, The source determination unit is further configured to: In response to a first ratio of any one of the first parameters and any one of the second parameters being greater than a second threshold, determine that the feature recognition result is a preset result, where the second threshold represents a relative maximum delay spread metric threshold, and the preset result is used to indicate that at least one first parameter of the first beam feature set and at least one second parameter of the second beam feature set satisfy the preset condition.

39. The device according to claim 38, wherein Wherein, The at least one first parameter includes at least one of the following: cell-specific reference signal - maximum delay spread (CRS-Tmax), and the at least one second parameter includes at least one of the following: physical downlink shared channel - maximum delay spread (PDSCH-Tmax). Or The at least one first parameter includes at least one of the following: time-frequency tracking reference signal - maximum delay spread (TRS-Tmax), and the at least one second parameter includes at least one of the following: physical downlink shared channel - maximum delay spread (PDSCH-Tmax) and physical downlink control channel - maximum delay spread (PDCCH-Tmax).

40. The device according to claim 34 or 35, characterized in that, The source determination unit is further configured to: In response to a second ratio of any one of the first parameters and any one of the second parameters being greater than a third threshold, determine that the feature recognition result is a preset result, where the third threshold represents a relative root mean square delay spread metric threshold, and the preset result is used to indicate that at least one first parameter of the first beam feature set and at least one second parameter of the second beam feature set satisfy the preset condition.

41. The device according to claim 40, wherein Wherein, The at least one first parameter includes at least one of the following: cell-specific reference signal - root mean square delay spread (CRS-Trms), and the at least one second parameter includes at least one of the following: physical downlink shared channel - root mean square delay spread (PDSCH-Trms). Or The at least one first parameter includes at least one of the following: time-frequency tracking reference signal - root mean square delay spread (TRS-Trms), and the at least one second parameter includes at least one of the following: physical downlink shared channel - root mean square delay spread (PDSCH-Trms) and physical downlink control channel - root mean square delay spread (PDCCH-Trms).

42. The device according to claim 34 or 35, characterized in that, The source determination unit is further configured to: In response to a second difference between any signal-to-interference-plus-noise ratio (SINR) in the at least one second parameter and any SINR in the at least one first parameter being greater than a fourth threshold, and a third ratio between any maximum Doppler in the at least one second parameter and any maximum Doppler in the at least one first parameter being less than a fifth threshold, determine that the feature recognition result is a preset result, where the fourth threshold represents a relative SINR metric threshold, the fifth threshold represents a relative maximum Doppler metric threshold, and the preset result is used to indicate that at least one first parameter in the first beam feature set and at least one second parameter in the second beam feature set meet the preset conditions.

43. The device according to claim 42, characterized in that, Wherein, The at least one first parameter includes at least one of the following: CRS-SINR, PSS-SINR, and SSS-SINR, and cell-specific reference signal - maximum Doppler (CRS-Doppler), and the at least one second parameter includes at least one of the following: PDSCH-SINR, physical downlink shared channel - maximum Doppler (PDSCH-Doppler); Or, The at least one first parameter includes at least one of the following: TRS CSI-SINR, SS-SINR, and time-frequency tracking reference signal - maximum Doppler (TRS-Doppler), and the at least one second parameter includes at least one of the following: PDSCH-SINR, PDCCH-SINR, physical downlink control channel - maximum Doppler (PDCCH-Doppler), and physical downlink shared channel - maximum Doppler (PDSCH-Doppler).

44. The device according to claim 34 or 35, characterized in that, The source determination unit is further configured to: In response to a fourth ratio between any maximum delay spread (Tmax) in the at least one second parameter and any Tmax in the at least one first parameter being greater than a sixth threshold, and a fifth ratio between any maximum Doppler in the at least one second parameter and any maximum Doppler in the at least one first parameter being less than a seventh threshold, determine that the feature recognition result is a preset result, where the sixth threshold represents a relative maximum delay spread metric threshold, the seventh threshold represents a relative maximum Doppler metric threshold, and the preset result is used to indicate that at least one first parameter in the first beam feature set and at least one second parameter in the second beam feature set meet the preset conditions.

45. The device according to claim 44, characterized in that, Wherein, The at least one first parameter includes at least one of the following: CRS-Tmax and cell-specific reference signal - maximum Doppler (CRS-Doppler), and the at least one second parameter includes at least one of the following: PDSCH-Doppler and PDCCH-Tmax; Or, The at least one first parameter includes at least one of the following: TRS-Tmax and TRS-Doppler, and the at least one second parameter includes at least one of the following: PDSCH-Tmax, PDCCH-Tmax, PDSCH-Doppler, and PDCCH-Doppler.

46. The device according to claim 34 or 35, characterized in that, The source determination unit is further configured to: In response to a sixth ratio of any root mean square delay spread Trms in the at least one second parameter to any root mean square delay spread Trms in the at least one first parameter being greater than an eighth threshold, and a seventh ratio of any maximum Doppler Doppler in the at least one second parameter to any maximum Doppler Doppler in the at least one first parameter being less than a ninth threshold, determining that the feature recognition result is a preset result, where the eighth threshold represents a relative root mean square delay spread threshold, the ninth threshold represents a relative maximum Doppler index threshold, and the preset result is used to indicate that at least one first parameter of the first beam feature set and at least one second parameter of the second beam feature set meet the preset conditions.

47. The device according to claim 46, wherein, Wherein, The at least one first parameter includes at least one of the following: CRS-Trms and CRS-Dopple, and the at least one second parameter includes at least one of the following: PDSCH-Trms and PDSCH-Doppler; or The at least one first parameter includes at least one of the following: TRS-Trms and TRS-Doppler, and the at least one second parameter includes at least one of the following: PDSCH-Trms, PDCCH-Trms, PDSCH-Doppler, and PDCCH-Doppler.

48. The device according to claim 34 or 35, characterized in that, The source determination unit is further configured to: In response to a third difference between any SINR in the at least one second parameter and any SINR in the at least one first parameter being greater than a tenth threshold, and an eighth ratio of any maximum delay spread Tmax in the at least one second parameter to any maximum delay spread Tmax in the at least one first parameter being greater than an eleventh threshold, determining that the feature recognition result is a preset result, where the tenth threshold represents a relative SINR index threshold, the eleventh threshold represents a relative maximum delay spread index threshold, and the preset result is used to indicate that at least one first parameter of the first beam feature set and at least one second parameter of the second beam feature set meet the preset conditions.

49. The device according to claim 48, characterized in that, Wherein, The at least one first parameter includes at least one of the following: CRS-SINR, PSS-SINR, SSS-SINR, and CRS-Tmax, and the at least one second parameter includes at least one of the following: PDSCH-SINR and PDSCH-Tmax; Or, The at least one first parameter includes at least one of the following: TRS CSI-SINR, SS-SINR, and TRS-Tmax, and the at least one second parameter includes at least one of the following: PDSCH-SINR, PDCCH-SINR, PDSCH-Tmax, and PDCCH-Tmax. The device according to claim 34 or 35, characterized in that, The source determination unit is further configured to: In response to a fourth difference between any SINR in the at least one second parameter and any SINR in the at least one first parameter being greater than a twelfth threshold, and a ninth ratio of any maximum root mean square delay spread Trms in the at least one second parameter to any maximum root mean square delay spread Trms in the at least one first parameter being greater than a thirteenth threshold, determine that the feature recognition result is a preset result, where the twelfth threshold represents a relative SINR metric threshold, the thirteenth threshold represents a relative maximum root mean square delay spread, and the preset result is used to indicate that at least one first parameter of the first beam feature set and at least one second parameter of the second beam feature set satisfy the preset condition.

51. The device according to claim 50, characterized in that, Wherein, The at least one first parameter includes at least one of the following: CRS-SINR, PSS-SINR, SSS-SINR, and CRS-Trms, and the at least one second parameter includes at least one of the following: PDSCH-SINR and PDSCH-Tmax; Or, The at least one first parameter includes at least one of the following: TRS CSI-SINR, SS-SINR, and TRS-Trms, and the at least one second parameter includes at least one of the following: PDSCH-SINR, PDCCH-SINR, PDSCH-Trms, and PDCCH-Trms. The device according to claim 34 or 35, characterized in that, The source determination unit is further configured to: In response to a fifth difference between any SINR in the at least one second parameter and any SINR in the at least one first parameter being greater than a fourteenth threshold, a tenth ratio of any maximum delay spread Tmax in the at least one second parameter to any maximum delay spread Tmax in the at least one first parameter being greater than a fifteenth threshold, and an eleventh ratio of any maximum root mean square delay spread Trms in the at least one second parameter to any maximum root mean square delay spread Trms in the at least one first parameter being greater than a sixteenth threshold, determine that the feature recognition result is a preset result, where the fourteenth threshold represents a relative SINR metric threshold, the fifteenth threshold represents a relative maximum delay spread metric threshold, the sixteenth threshold represents a relative maximum root mean square delay spread, and the preset result is used to indicate that at least one first parameter of the first beam feature set and at least one second parameter of the second beam feature set satisfy the preset condition.

53. The device according to claim 52, characterized in that, Wherein, The at least one first parameter includes at least one of the following: CRS - SINR, PSS - SINR, SSS - SINR, CRS - Tmax, and CRS - Trms, and the at least one second parameter includes at least one of the following: PDSCH - SINR, PDSCH - Tmax, and PDSCH - Trms; Alternatively, The at least one first parameter includes at least one of the following: TRS CSI - SINR, SS - SINR, TRS - Tmax, and TRS - Trms, and the at least one second parameter includes at least one of the following: PDSCH - SINR, PDCCH - SINR, PDSCH - Tmax, PDCCH - Tmax, PDSCH - Trms, and PDCCH - Trms.

54. The device according to claim 34, characterized in that, The source determination unit is further configured to: In response to the feature recognition result corresponding to the first time information satisfying the first result requirement and the radio resource control connection of the communication device not being re - configured or released, determine that the acquisition source corresponding to the wireless channel state information within the second time information is the dynamic beam feature acquisition source, where the first time information is any moment in the current period of a continuous observation preset period, the second time information is the next preset period adjacent to the current period, and the first result requirement includes the result requirement that the feature recognition results corresponding to the first time information are all preset results or the result requirement that the first quantity of preset results in the feature recognition results corresponding to the first time information meets the quantity requirement.

55. The device according to claim 34, characterized in that, The source determination unit is further configured to: In response to the feature recognition result corresponding to the first time information satisfying the second result requirement, determine that the acquisition source corresponding to the wireless channel state information within the second time information is the static beam feature acquisition source, where the first time information is any moment in the current period of a continuous observation preset period, and the second result requirement includes the result requirement that the feature recognition results corresponding to the first time information are not all preset results or the result requirement that the first quantity of preset results in the feature recognition results corresponding to the first time information does not meet the quantity requirement.

56. The device according to claim 34, characterized in that The source determination unit is further configured to: In response to the feature recognition result corresponding to the first time information satisfying the first result requirement and the radio resource control connection of the communication device not being re - configured or released, determine that the acquisition source corresponding to the wireless channel state information within the second time information is the dynamic beam feature acquisition source, where the first time information is any moment in the current period of a continuous observation sliding period, the second time information is the time information before the next feature recognition result is not obtained, and the first result requirement includes the result requirement that the feature recognition results corresponding to the first time information are all preset results or the result requirement that the second quantity of preset results in the feature recognition results corresponding to the first time information meets the quantity requirement.

57. The device according to claim 34, characterized in that, The source determination unit is further configured to: In response to the feature recognition result corresponding to the first time information meeting the second result requirement, determine that the acquisition source corresponding to the wireless channel state information within the second time information is the static beam feature acquisition source, where the first time information is any moment in the current period of the continuous observation sliding period, the second time information is the time information before the next feature recognition result is not obtained, and the second result requirement includes the result requirement that the feature recognition results corresponding to the first time information are not all preset results or the result requirement that the second quantity of the preset results in the feature recognition results corresponding to the first time information does not meet the quantity requirement; Before the feature recognition result corresponding to the second time information is not obtained, observe the update information corresponding to the first time information, and use the updated first time information as the first time information to re-determine the acquisition source corresponding to the wireless channel state information within the second time information.

58. The device according to any one of claims 54 to 57, characterized in that Wherein, The first beam feature set includes a downlink static beam feature set, and the second beam feature set includes a downlink dynamic beam feature set.

59. The device according to claim 34, characterized in that, Wherein, The first beam feature set includes a downlink static beam feature set, the second beam feature set includes a downlink dynamic beam feature set, and the set acquisition unit is further configured to: Extract features from the synchronization signal and / or reference signal of the broadband wireless communication system with downlink beamforming enabled to obtain the downlink static beam feature set related to the current network mode; Extract features from the demodulation reference signal of the broadband wireless communication system with downlink dynamic beamforming enabled to obtain the downlink dynamic beam feature set related to the current network mode.

60. The device according to claim 34, characterized in that, The set acquisition unit is further configured to: Obtain the current resident cell of the communication device; In response to the network mode information corresponding to the current resident cell and the downlink beamforming determination order, determine the downlink beamforming support information corresponding to the current network mode of the current resident cell.

61. The device according to claim 60, characterized in that, The set acquisition unit is further configured to: Obtain the network mode information corresponding to the current resident cell; In response to the network mode information corresponding to the current resident cell being the first network mode, determine that the communication device is in the radio resource control connected state; In response to the dedicated configuration signaling indicating that the communication device is in the preset transmission mode, obtain the first scenario information corresponding to the current resident cell; In response to the first scenario information being the preset scenario information, determine that the downlink beamforming support information corresponding to the first network mode is that the first network mode supports downlink dynamic beamforming. The device according to claim 60, wherein, The set acquisition unit is further configured to: Obtain the network mode information corresponding to the current resident cell; In response to the network mode information corresponding to the current resident cell being the first network mode, determine that the communication device is in the radio resource control connected state; In response to the dedicated configuration signaling indicating that the communication device is not in the preset transmission mode, or the first scenario information corresponding to the current resident cell is not the preset scenario information, determine that the downlink beamforming support information corresponding to the first network mode is that the first network mode does not support downlink dynamic beamforming.

63. The device according to claim 60, characterized in that, The set acquisition unit is further configured to: In response to the network mode information corresponding to the current resident cell not being the first network mode, determine that the network mode information corresponding to the current resident cell is the second network mode; In response to the frequency range information of the current resident cell being the first frequency range, the communication mode of the current resident cell being time division duplex, and the second scenario information corresponding to the current resident cell being the preset scenario information, determine that the downlink beamforming support information corresponding to the second network mode is that the second network mode supports downlink dynamic beamforming.

64. The device according to claim 60, characterized in that, The set obtaining unit is further configured to: In response to the network mode information corresponding to the current resident cell not being the first network mode, determine that the network mode information corresponding to the current resident cell is the second network mode; In response to the frequency range information corresponding to the current resident cell not being the first frequency range, or the communication mode of the current resident cell not being time division duplex, or the second scenario information corresponding to the current resident cell not being the preset scenario information, determine that the downlink beamforming support information corresponding to the second network mode is that the second network mode does not support downlink dynamic beamforming. The device according to claim 60, wherein, The set obtaining unit is further configured to: In response to the network mode information corresponding to the current resident cell not being the second network mode, determine whether the network mode information corresponding to the current resident cell is the third network mode; In response to determining that the network mode information corresponding to the current resident cell is the third network mode, adopt the determination method corresponding to the third network mode to determine the downlink beamforming support information corresponding to the current network mode of the current resident cell.

66. The device according to any one of claims 61 and 62, characterized in that, The set obtaining unit is further configured to: In response to a radio resource control signaling reconfiguration occurring in the radio resource control connected state, re-determine the downlink beamforming support information corresponding to the current network mode of the current resident cell.

67. A communication device, characterized in that, Comprising: A processor; A memory for storing instructions executable by the processor; Wherein, the processor is configured to execute the instructions to implement the method according to any one of claims 1 to 33.

68. A storage medium, when the instructions in the storage medium are executed by a processor of a communication device, enabling the communication device to execute the method according to any one of claims 1 to 33.

69. A chip, characterized in that, Comprising a processor and an interface; the processor is configured to read instructions to execute the method according to any one of claims 1 to 33.

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