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

Abstract

The present disclosure relates to the field of communication technology, and in particular to a beam sensing method, apparatus, communication equipment, storage medium and chip. The beam sensing method includes: obtaining a first beam feature set and a second beam feature set related to the current network standard; 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, wherein 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 use of the present disclosure can improve the receiving state of the communication device and improve the communication quality of the communication device.

Description

Technical Field

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

[0002] With the development of communication technology, beamforming, as a key technology of medium and high frequency broadband wireless communication systems, has been widely used in cellular mobile communication systems including New Radio (NR, commonly known as 5G). Among them, beamforming technology can be, for example, adjusting the parameters of the basic unit of the phase array so that signals at certain angles obtain constructive interference and signals at other angles obtain destructive interference, thereby generating a beam. Summary of the invention

[0003] The present disclosure provides a beam sensing method, device, communication device, storage medium and chip to improve the reception state of the communication device and improve 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] Obtain a first beam feature set and a second beam feature set related to the current network standard;

[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, the first beam feature set or the second beam feature set is selected as a source for acquiring wireless channel state information, wherein 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 device is provided, including:

[0008] A set acquisition unit, used to acquire a first beam feature set and a second beam feature set related to the current network standard;

[0009] A source determination unit, configured to select the first beam feature set or the second beam feature set as a source for acquiring 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 satisfying a preset condition, wherein 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 an embodiment of the present disclosure, a communication device is provided, including:

[0011] processor;

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

[0013] The processor is configured to execute the instructions to implement the beam sensing method described in any one of the aforementioned aspects.

[0014] According to a fourth aspect of an embodiment of the present disclosure, a storage medium is provided. When instructions in the storage medium are executed by a processor of a communication device, the communication device is enabled to perform the beam sensing method described in any one of the preceding aspects.

[0015] According to a fifth aspect of an embodiment of the present disclosure, a computer program product is provided, including a computer program, wherein the computer program implements any one of the methods described in the preceding aspects when executed by a processor.

[0016] According to a sixth aspect of an embodiment of the present disclosure, a chip is provided, comprising: a processor and an interface; the processor is used to read instructions to implement any one of the methods described in the preceding aspects.

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

[0018] In some or related embodiments, by acquiring a first beam feature set and a second beam feature set related to the current network standard; 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 a source for obtaining wireless channel state information, wherein 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 corresponding acquisition source of wireless channel state information 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 meet the preset condition, which can improve the accuracy of determining the corresponding acquisition source of wireless channel state information, reduce the situation where the wireless channel state information required for channel estimation does not match the acquisition source, resulting in inaccurate determination of the wireless channel state information, improve the accuracy of obtaining wireless channel state information, improve the receiving state of the communication device, and improve the communication quality of the communication device.

[0019] It is to be understood that the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the present disclosure. BRIEF DESCRIPTION OF THE DRAWINGS

[0020] The drawings herein are incorporated into and constitute a part of the specification, illustrate embodiments consistent with the present disclosure, and together with the description are used to explain the principles of the present disclosure, and do not constitute improper limitations on the present disclosure.

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

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

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

[0024] Figure 4 It is a schematic diagram of an example of a time-frequency tracking reference signal (Tracking Reference Signal, TRS) static wide beam and a physical downlink control channel (Physical Downlink Control Channel, PDSCH) dynamic narrow beam according to an exemplary embodiment;

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

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

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

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

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

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

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

[0032] Fig. 9 is a schematic diagram showing an example of first time information and second time information according to an exemplary embodiment;

[0033] Fig.10 is a schematic diagram showing an example of first time information and second time information according to an exemplary embodiment;

[0034] Fig.11 is a block diagram of a beam sensing device according to an exemplary embodiment;

[0035] Fig.12 is a block diagram of a communication device according to an exemplary embodiment;

[0036] Fig.13 is a block diagram of a chip according to an exemplary embodiment. DETAILED DESCRIPTION

[0037] In order to enable ordinary persons 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 in conjunction with the accompanying drawings.

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

[0039] The embodiments of the present disclosure are not exhaustive, but are only illustrative of some embodiments, and are not intended to be a specific limitation on the scope of protection of the present disclosure. In the absence of contradiction, each step in a certain embodiment can be implemented as an independent embodiment, and the steps can be arbitrarily combined. For example, a solution after removing some steps in a certain embodiment can also be implemented as an independent embodiment, and the order of the steps in a certain embodiment can be arbitrarily exchanged. In addition, the optional implementation methods in a certain embodiment can be arbitrarily combined; in addition, the embodiments can be arbitrarily combined, for example, some or all of the steps of different embodiments can be arbitrarily combined, and a certain embodiment can be arbitrarily combined with the optional implementation methods of other embodiments.

[0040] In each embodiment of the present disclosure, unless otherwise specified or there is a logical conflict, the terms and / or descriptions between the embodiments are consistent and can be referenced to each other, and the technical features in different embodiments can be combined to form a new embodiment based on their internal logical relationships.

[0041] The terms used in the embodiments of the present disclosure are only for the purpose of describing specific embodiments and are not intended to limit 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", "aforementioned", "this", etc., may mean "one and only one", or "one or more", "at least one", etc. For example, when using articles such as "a", "an", "the" in English in translation, the noun after the article may be understood as a singular expression or a plural expression.

[0043] In the embodiments of the present disclosure, “plurality” refers to two or more.

[0044] In some embodiments, the terms “at least one,” “one or more,” “a plurality of,” “multiple,” etc. may be used interchangeably.

[0045] In some embodiments, "at least one of A and B", "A and / or B", "A in one case, B in another case", "in response to one case A, in response to another case B", etc., may include the following technical solutions according to the situation: in some embodiments, A (A is executed independently of B); in some embodiments, B (B is executed independently of A); in some embodiments, execution is selected from A and B (A and B are selectively executed); in some embodiments, A and B (both A and B are executed). When there are more branches such as A, B, C, etc., the above is also similar.

[0046] In some embodiments, the recording method of "A or B" may include the following technical solutions according to the situation: in some embodiments, A (A is executed independently of B); in some embodiments, B (B is executed independently of A); in some embodiments, execution is selected from A and B (A and B are selectively executed). When there are more branches such as A, B, C, etc., the above is also similar.

[0047] The prefixes such as "first" and "second" in the embodiments of the present disclosure are only used to distinguish different description objects, and do not constitute restrictions on the position, order, priority, quantity or content of the description objects. The statement of the description object refers to the description in the context of the claims or embodiments, and should not constitute unnecessary restrictions due to the use of prefixes. For example, if the description object is a "field", the ordinal number before the "field" in the "first field" and the "second field" does not limit the position or order between the "fields", and the "first" and "second" do not limit whether the "fields" they modify are in the same message, nor do they limit the order of the "first field" and the "second field". For another example, if the description object is a "level", the ordinal number before the "level" in the "first level" and the "second level" does not limit the priority between the "levels". For another example, the number of description objects is not limited by the ordinal number, and can be one or more. Taking the "first device" as an example, the number of "devices" can be one or more. In addition, the objects modified by different prefixes may be the same or different. For example, if the description object is "device", then the "first device" and the "second device" may be the same device or different devices, and their types may be the same or different. For another example, if the description object is "information", then the "first information" and the "second information" may be the same information or different information, and their contents may be the same or different.

[0048] In some embodiments, “including A”, “comprising A”, “used to indicate A”, and “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 ...", "at the time of ...", "when ...", "if ...", "if ...", etc. can be used interchangeably.

[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", and "above" can be replaced with each other, and terms such as "less than", "less than or equal to", "not greater than", "less than", "less than or equal to", "no more than", "lower than", "lower than or equal to", "not higher than", and "below" can be replaced with each other.

[0051] In some embodiments, devices and equipment may be interpreted as physical or virtual, and their names are not limited to the names recorded in the embodiments. In some cases, they may 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, "network" can be interpreted as devices included in the network, such as access network equipment, core network equipment, etc.

[0053] In some embodiments, "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. may be obtained with the user's consent.

[0055] It should be noted that the terms "first", "second", etc. in the specification and claims of the present disclosure and the above-mentioned drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence. It should be understood that the data used in this way can be interchanged where appropriate, 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. Instead, 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 flow chart of a beamforming method according to an exemplary embodiment. Figure 1 As shown, the beamforming technology adjusts the parameters of the basic units of the phase array so that signals at certain angles obtain constructive interference and signals at other angles obtain destructive interference, thereby generating a beam.

[0057] According to some embodiments, Figure 2 is a schematic diagram showing an example of a beamforming application according to an exemplary embodiment. Figure 2 As shown, taking the new air interface NR 5G downlink application as an example: the base station node B (gNodeB, gNB) sends the synchronization signal / PBCH (SSB) and the system information block (SIB) to ensure the service quality of all user equipment (UE) in the coverage area using a static beam method.

[0058] According to some embodiments, Figure 3 is a schematic diagram showing an example of a beamforming application according to an exemplary embodiment. Figure 3 As shown, taking the typical static beam design of the first frequency range of NR 5G (Frequency Range 1, referred to as FR1, 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 SSB / SIB message reception, the random access process is initiated to complete the residence, and the gNB continues to use when sending message 2 (referred to as Msg2, for random access request) and message 4 (referred to as Msg4, for contention resolution). Figure 3 Broadcast static beam shown.

[0060] Entering the Radio Resource Control (RRC) connection state, in order to achieve the best dedicated user service quality, the gNB's physical downlink shared channel (PDSCH) adopts dynamic beam transmission based on the sounding reference signal (SRS) estimation and precoding matrix indicator (PMI) reporting; in particular, when the SRS / PMI information is not timely or unreliable, it will switch to a static beam to ensure the basic service quality of the user. The physical downlink control channel (PDCCH) and channel state information signal (CSI-RS) are similarly sent using dynamic beams / static beams.

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

[0062] The method of characterizing the corresponding association is to indicate the type of quasi co-located information (QCL), 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 type in existing network deployment, as an example, the TCI status indication informs that the corresponding reference signal and the propagation status of the PDSCH radio channel are the same in 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 status required for the radio channel estimation (CE) for PDSCH / PDCCH reception.

[0068] According to some embodiments, TRS, as a long-period static beam, cannot be completely consistent with the actual beam used by the physical downlink shared channel PDSCH in the time domain. And TRS cannot perform beamforming at the precoding resource block group (PRG) or subband granularity according to the protocol, so it cannot be completely consistent with the parallel data system (PDS) beam in the frequency domain. In order to cover the beam changes of PDS as much as possible, gNB generally configures wider and more robust static beams for TRS. Figure 4 As shown in the figure, the beam used by gNB to send TRS is a static wide beam and remains unchanged for 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.) and UE transmission or feedback status in the time domain.

[0069] Figure 4 In Slot1, the gNB configures the service channel PDSCH in the single-user multiple-input multiple-output mode (SU-MIMO for short), with 3 service streams, each of which is configured with the best dedicated dynamic beam at the current moment; in Slot2, the gNB configures the service channel PDSCH in the multi-user multiple-input multiple-output mode (MU-MIMO for short), with 2 service streams, each of which is configured with the best dedicated dynamic beam at the current moment; but in Slot1 and 2, the TRS corresponding to the TCIQCL 'typeA' state remains unchanged. Among them, for example, the non-ideal effect brought about by the above static wide beam guiding the dynamic narrow beam reception can be called the "wide and narrow beam" effect. The "wide and narrow beam" effect can be used, for example, to indicate the influence of the beam width of the transmitting and receiving antennas on the signal transmission in wireless communication. The "wide and narrow beam" effect can, for example, include the situation where the static wide beam guides the dynamic narrow beam reception signal, so that the wireless channel state information does not meet the requirements.

[0070] According to some embodiments, although the QCL'typeA' carried by the TCI status indication informs that the reference signal (TRS and / or SSB) static wide beam can provide the radio channel state information (Channel State Information, CSI for short) available for PDSCH CE, the CSI message may be, for example, Doppler shift, Doppler spread, average delay, delay spread, etc., in fact, due to the "wide and narrow beam" effect, the radio channel state information is inaccurate, including:

[0071] Average delay spread. Static wide beams and dynamic narrow beams experience different scattering and diffraction paths. Static wide beams usually have larger delay spread.

[0072] Maximum delay spread: static wide beams and dynamic narrow beams experience different scattering and diffraction paths, and static wide beams usually have larger maximum delay spread;

[0073] Doppler shift, static wide beam and dynamic narrow beam experience different scattering and diffraction paths, and the Doppler shift is different;

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

[0075] According to some embodiments, 5G PDSCH / PDCCH service channel reception, for example, can obtain wireless channel state information (Doppler shift, Doppler spread, average delay, delay spread) by strictly following the QCL reference signal indicated by the TCI state by default; 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 in the middle and far point of the base station coverage, the more significant the "wide and narrow beam" effect, and the wireless channel state information obtained by the corresponding static wide beam is less accurate than that of the dynamic narrow beam.

[0076] In some embodiments, the 4th generation mobile communication technology (4G) PDSCH TM7 / 8 / 9 service channel reception, for example, can use the cell-specific reference signal (CRS) by default to obtain 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 in the coverage of the base station, the more significant the "wide and narrow beam" effect, and the wireless channel state information obtained by the corresponding static wide beam is less accurate than that of the dynamic narrow beam.

[0077] Figure 5 is a flow chart of a beam sensing method according to an exemplary embodiment. Figure 5 As shown, the beam sensing method can be used in a broadband wireless communication system supporting beamforming, such as a long term evolution (LTE) system, a NR system, a sixth generation mobile communication technology (6-Generation, 6G) system, etc., and includes the following steps:

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

[0079] According to some embodiments, the network standard may be, for example, a communication standard and protocol for indicating different mobile communication networks. The current network standard of the embodiment of the present disclosure may be, for example, one of the network standards supported by the communication device, and is not a narrowly understood network standard that is currently in use. The current network standard does not specifically refer to a certain fixed network standard. For example, when the specific network standard corresponding to the current network standard changes, the current network standard may also change accordingly. For example, when the execution time point of the beam sensing method changes, the current network standard may also change accordingly.

[0080] In some embodiments, the network standard can be a second-generation mobile communication technology specification (2-Generation wireless telephone technology, 2G) network standard represented by the global system for mobile communication (global system for mobile communication, GSM), a third-generation mobile communication technology (3rd-Generation, 3G) network standard represented by wideband code division multiple access (wideband code division multiple access, WCDMA), a fourth-generation mobile communication technology (4G) network standard represented by long term evolution (long term evolution, LTE), a 5G network standard represented by new radio (newradio, NR), and the like.

[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, for example, a set including at least one beam feature. The embodiment of the present disclosure does not limit the number 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. Among them, the downlink static beam feature set may include, for example, at least one downlink static beam feature convergence. The downlink static beam feature set does not specifically refer to a 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, for example, a set including at least one beam feature. The embodiment of the present disclosure does not limit the number corresponding to the second beam feature set. The name of the second beam feature set is also not limited. For example, it may also be at least one second beam feature. Among them, the downlink dynamic beam feature set may include, for example, at least one downlink dynamic beam feature. The downlink dynamic beam feature set does not specifically refer to a 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 the current network standard supports downlink dynamic beamforming, a first beam feature set and a second beam feature set related to the current network standard may be obtained. The order in which the first beam feature set and the second beam feature set are obtained is not limited. For example, the first beam feature set may be obtained first, and then the second beam feature set may be obtained. For example, the second beam feature set may be obtained first, and then the first beam feature set may be obtained. For example, the first beam feature set and the second beam feature set may be obtained at the same time.

[0084] According to some embodiments, when it is determined that the current network standard supports downlink dynamic beam forming, a downlink static beam feature set and a downlink dynamic beam feature set related to the current network standard can be obtained. Among them, the downlink static beam feature set and the downlink dynamic beam feature set are obtained in no particular order, for example, the downlink static beam feature set and the downlink dynamic beam feature set can be obtained at the same time, 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. Among them, because the downlink static beam feature set and the downlink dynamic beam feature set both include at least one beam feature, it is also possible to first obtain a downlink static beam feature, then obtain a downlink dynamic beam feature, and then obtain a downlink static beam feature, etc. For example, the two sets can be obtained alternately or non-alternatingly. The embodiments of the present disclosure do not limit the specific process of obtaining the downlink static beam feature set and the downlink dynamic beam feature set corresponding to the current network standard.

[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 a source for obtaining wireless channel state information, wherein 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.

[0086] In some embodiments, the preset condition may be used, for example, to determine the condition of the acquisition source corresponding to the wireless channel state information, wherein different preset conditions may correspond to different acquisition sources, for example. The preset condition does not specifically refer to a fixed condition. For example, when a condition modification instruction for a preset condition is received, the preset condition may also change accordingly. For example, when a parameter in the preset condition changes, the preset condition may also change accordingly. The preset condition may, for example, include whether the RRC connection of the terminal is 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, the wireless channel state information (CSI) may be used to describe the channel properties of the communication link, for example, wherein when the acquisition time point of the wireless channel state information changes, the wireless channel state information may also change accordingly.

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

[0089] In some or related embodiments, by acquiring a first beam feature set and a second beam feature set related to the current network standard; 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 wireless channel state information, wherein 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 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 meet the preset condition, which can improve the accuracy of determining the acquisition source corresponding to the wireless channel state information, reduce the situation where the wireless channel state information required for channel estimation does not match the acquisition source, resulting in inaccurate determination of the wireless channel state information, improve the accuracy of acquiring the wireless channel state information, improve the receiving state of the communication device, and improve the communication quality of the communication device.

[0090] Figure 6 is a flow chart of a beam sensing method according to an exemplary embodiment. Figure 6 As shown, the beam sensing method can be used in a wireless communication scenario, including the following steps:

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

[0092] According to some embodiments, for example, the current resident cell of the communication device may be obtained. For example, the current resident cell of the communication device may be cell A. The communication device may also be called a terminal, and the embodiments of the present disclosure do not limit the name of the communication device.

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

[0094] According to some embodiments, the network standard information is used to indicate the type of the network standard, and the network standard information corresponding to the current resident cell may be, for example, a 4G network standard.

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

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

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

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

[0099] Obtain the network standard information corresponding to the current resident cell;

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

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

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

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

[0104] Obtain the network standard information corresponding to the current resident cell;

[0105] In response to the network standard information corresponding to the current camping cell being the first network standard, determining that the communication device is in a radio resource control connection state;

[0106] 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, the downlink beamforming support information corresponding to the first network standard is determined to be that the first network standard does not support downlink dynamic beamforming. Therefore, in the first network standard, 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 standard may be, for example, a 4G network standard.

[0108] According to some embodiments, the preset transmission mode may 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 current camping cell may be acquired.

[0109] In some embodiments, the first scene information may be used to indicate the scene information corresponding to the current resident cell. The first scene information does not specifically refer to a fixed information. For example, the first scene information may be obtained by using a scene recognition method. The embodiments of the present disclosure do not limit this.

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

[0111] When the network standard information corresponding to the current resident cell is the 4G network standard, it is determined that the communication device is in a wireless resource control connection state (RRC_CONNECTED). When the dedicated configuration signaling indicates that the communication device is not in a preset transmission mode, it is determined that the downlink beamforming support information corresponding to the 4G network standard is not supporting downlink dynamic beamforming.

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

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

[0114] In response to a radio resource control signaling reconfiguration in the radio resource control connection state, the downlink beamforming support information corresponding to the current network standard of the current resident cell is re-determined. Among them, the re-determination of the downlink beamforming support information corresponding to the current network standard of the current resident cell is applicable to the case where the current network standard is the first network standard or the second network standard. The embodiments of the present disclosure are not limited to this. Therefore, when the radio resource control signaling reconfiguration occurs, the downlink beamforming support information can be re-determined to improve the accuracy of the determination of the downlink beamforming support information and the accuracy of the determination of the acquisition source.

[0115] According to some embodiments, when RRC signaling reconfiguration occurs in the wireless resource control connection state, it can be determined whether the communication device is in the wireless resource control connection state, and when it is determined that the communication device is in the wireless resource control connection state, the downlink beamforming support information corresponding to the current network standard of the current resident cell can be re-determined based on the dedicated configuration signaling and the first scenario information.

[0116] According to some embodiments, in response to network standard information corresponding to a currently camped cell and a downlink beamforming determination order, determining downlink beamforming support information corresponding to a current network standard of a currently camped cell includes:

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

[0118] In response to the frequency range information of the current cell being the first frequency range, the communication mode of the current cell being time division duplex, and the second scene information corresponding to the current cell being the preset scene information, the downlink beamforming support information corresponding to the second network standard is determined to be the second network standard supporting downlink dynamic beamforming.

[0119] For example, in one embodiment of the present disclosure, in response to the network standard information corresponding to the current camping cell and the downlink beam forming determination order, determining the downlink beam forming support information corresponding to the current network standard of the current camping cell includes:

[0120] When the network standard information corresponding to the current resident cell is not the first network standard, determining that the network standard information corresponding to the current resident cell is the second network standard;

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

[0122] In response to the frequency range information being a first frequency range (Frequency range 1, FR1), acquiring a communication mode of a currently resident cell;

[0123] In response to the communication mode being time division duplex, obtaining second scenario information corresponding to the current resident cell;

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

[0125] According to some embodiments, in response to network standard information corresponding to a currently camped cell and a downlink beamforming determination order, determining downlink beamforming support information corresponding to a current network standard of a currently camped cell includes:

[0126] In response to the network standard information corresponding to the current resident cell not being the first network standard, determining that the network standard information corresponding to the current resident cell is the second network standard;

[0127] 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, it is determined that the downlink beamforming support information corresponding to the second network standard is that the second network standard does not support downlink dynamic beamforming. Therefore, in the second network standard, the downlink beamforming support information can be determined based on the frequency range information and the communication mode, and the downlink beamforming support information can be determined based on different information in different network standards, which can improve the accuracy of determining the downlink beamforming support information and the accuracy of determining the acquisition source.

[0128] According to some embodiments, the second network standard may be, for example, a 5G network standard.

[0129] According to some embodiments, the frequency range information may be used to indicate the frequency range of the current camped cell, for example. The frequency range information may include, for example, a first frequency range, namely, frequency range 1, frequency range 2, and the like.

[0130] According to some embodiments, the communication method may include, for example, time division duplex and frequency division duplex.

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

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

[0133] In some embodiments, in response to the network standard information corresponding to the current camping cell and the downlink beamforming determination order, determining the downlink beamforming support information corresponding to the current network standard of the current camping cell includes:

[0134] In response to the network standard information corresponding to the current resident cell not being the second network standard, determining whether the network standard information corresponding to the current resident cell is a third network standard;

[0135] In response to determining that the network standard information corresponding to the current resident cell is the third network standard, a determination method corresponding to the third network standard is adopted to determine the downlink beamforming support information corresponding to the current network standard of the current resident cell. The third network standard can be, for example, a 6G or higher network standard.

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

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

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

[0139] In some embodiments, it is determined that the network standard information corresponding to the current resident cell is the 5G network standard, 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 standard is that the 5G network standard does not support downlink dynamic beamforming.

[0140] In some embodiments, it is determined that the network standard information corresponding to the current resident cell is the 5G network standard, 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 scene information corresponding to the current resident cell is obtained. When the second scene information is a subway scene or a high-speed rail scene, it is determined that the downlink beamforming support information corresponding to the 5G network standard is that the 5G network standard does not support downlink dynamic beamforming.

[0141] In some embodiments, it is determined that the network standard information corresponding to the current resident cell is the 5G network standard, 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 scene information corresponding to the current resident cell is obtained. When the second scene information is not a subway scene or a high-speed rail scene, it is determined that the downlink beamforming support information corresponding to the 5G network standard is that the 5G network standard supports downlink dynamic beamforming.

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

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

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

[0145] According to some embodiments, 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 obtaining the first beam feature set and the second beam feature set related to the current network standard includes:

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

[0147] Feature extraction is performed on a demodulation reference signal of a broadband wireless communication system with downlink dynamic beamforming enabled to obtain a downlink dynamic beam feature set related to the current network standard.

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

[0149] Primary Synchronization Signal (PSS) under the first network standard;

[0150] Secondary Synchronization Signal (SSS) under the first network standard;

[0151] A cell-specific reference signal (CRS) under the first network standard;

[0152] SSB under the second network standard;

[0153] TRS under the second network standard.

[0154] The downlink static beam feature set 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 Doppler, and may specifically 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] The demodulation reference signal includes at least one of the following:

[0159] PDSCH demodulation reference signal (Demodulation Reference Signal, DMRS) under the first network standard or the second network standard;

[0160] PDCCH DMRS under the second network standard.

[0161] The downlink dynamic beam feature set 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 Doppler, and may specifically include:

[0162] 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-maximum Doppler (PDCCH-Doppler) corresponding to the first network standard or the second network standard;

[0163] The second network standard corresponds to the physical downlink control channel-signal to interference plus noise ratio (Physical downlink control channel-Signal to Interference plus Noise Ratio, PDCCH-SINR), physical downlink control channel-maximum delay spread (Physical downlink control channel-maximum delay spread, PDCCH-Tmax), physical downlink control channel-root mean square delay spread (Physical downlink control channel-rms delay spread, PDCCH-Trms), and physical downlink control channel-maximum Doppler (Physical downlink control channel-Doppler, PDCCH-Doppler).

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

[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, a feature recognition result is obtained, wherein the feature recognition result is used to indicate whether the at least one first parameter of the first beam feature set and the 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 repeated 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, root mean square delay spread Trms, maximum Doppler Doppler, etc.

[0168] According to some embodiments, the obtaining a feature recognition result in response to a calculation 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] A difference result and / or a comparison 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 is compared with at least one threshold information to obtain a feature recognition result.

[0170] The feature recognition result may be, for example, a wide or narrow beam effect recognition result. The wide or narrow beam effect recognition result may be, for example, corresponding to a network standard, wherein different network standards may determine the wide or narrow beam effect recognition result according to different recognition methods.

[0171] The setting of each threshold in the at least one threshold information may be set, for example, based on experience or modulation effect. For example, it may be set based on the accuracy of the wide and narrow beam effect recognition result. This embodiment of the present disclosure is not limited to this.

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

[0173] According to some embodiments, in response to a calculation 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:

[0174] A feature recognition result is obtained in response to a calculation 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, wherein the any first parameter and the any second parameter correspond to the same beam feature.

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

[0176] Alternatively, 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.

[0177] In some embodiments, the beam characteristic is a maximum delay spread Tmax, wherein at least one first parameter includes at least one of the following: a cell-specific reference signal-maximum delay spread CRS-Tmax, and at least one second parameter includes at least one of the following: a physical downlink shared channel-maximum delay spread PDSCH-Tmax;

[0178] or

[0179] 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.

[0180] In some embodiments, the beam characteristic is a root mean square delay spread Trms, wherein at least one first parameter includes at least one of the following: a cell-specific reference signal-root mean square delay spread CRS-Trms, and at least one second parameter includes at least one of the following: a physical downlink shared channel-root mean square delay spread PDSCH-Trms;

[0181] or

[0182] 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.

[0183] In some embodiments, the beam characteristic is a maximum Doppler Doppler, wherein at least one first parameter includes CRS-SINR, PSS-SINR and SSS-SINR and a 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;

[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, in response to a calculation 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:

[0187] A feature recognition result is obtained in response to a calculation 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, wherein the two first parameters and the two second parameters correspond to two different beam features, and the calculation result is two results obtained by performing calculation processing on any first parameter and any second parameter of the same beam feature.

[0188] In some embodiments, 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;

[0189] or,

[0190] 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.

[0191] In some embodiments, 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;

[0192] or

[0193] 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.

[0194] In some embodiments, 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;

[0195] or,

[0196] 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.

[0197] In some embodiments, 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;

[0198] or,

[0199] 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.

[0200] According to some embodiments, in response to a calculation 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:

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

[0202] In some embodiments, 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;

[0203] or,

[0204] 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.

[0205] According to some embodiments, when determining a feature recognition result in response to a calculation 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-type 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 acquiring the feature recognition result, and can improve the accuracy of determining the acquisition source.

[0206] According to some embodiments, in response to a calculation 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:

[0207] 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, the first threshold characterizing a relative SINR indicator threshold, and the preset result indicating 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 second parameter and any first parameter may, for example, correspond to the same beam feature.

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

[0209] Alternatively, 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] For example, in one embodiment of the present disclosure, when the current network standard is the 4G network standard, when the difference between PDSCH-SINR and CRS-SINR (or PSS-SINR or SSS-SINR) is greater than the first threshold, it can be determined that the feature recognition result is a preset result, for example, it can be an indication that a wide or narrow beam effect occurs, and when the difference between PDSCH-SINR and CRS-SINR (or PSS-SINR or SSS-SINR) is not greater than the first threshold, it can be determined that the feature recognition result is not a preset result. For example, when the difference between PDSCH-SINR and CRS-SINR is greater than the first threshold, it can be determined that the wide or narrow beam effect recognition result is that a wide or narrow beam effect occurs, and when the difference between PDSCH-SINR and CRS-SINR is not greater than the first threshold, it can be determined that the wide or narrow beam effect recognition result is that a wide or narrow beam effect does not occur. Among them, the second threshold can, for example, characterize the relative SINR indicator threshold th-sinr-for-BF, and the value range can be, for example, 5 to 10 dB.

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

[0212] For example, in one embodiment of the present disclosure, when PDSCH-SINR (or PDCCH-SINR)-TRS CSI-SINR (or SS-SINR) is greater than a first threshold, it can be determined that the feature identification result is a preset result, for example, the wide and narrow beam effect identification result can be determined as the occurrence of a wide and narrow beam effect. When PDSCH-SINR (or PDCCH-SINR)-TRS CSI-SINR (or SS-SINR) is not greater than the first threshold, it can be determined that the feature identification result is not a preset result, for example, the wide and narrow beam effect identification result can be determined as the occurrence of a wide and narrow beam effect.

[0213] According to some embodiments, in response to a calculation 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:

[0214] In response to a first ratio of any first parameter to any second parameter being greater than a second threshold, the feature recognition result is determined to be a preset result, wherein the second 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 preset conditions.

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

[0216] or

[0217] 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. The second threshold can, for example, represent

[0218] The relative maximum delay spread indicator threshold th-tmax-for-BF may have a value range of, for example, 1.5 to 3.

[0219] For example, in one embodiment of the present disclosure, when the current network standard is the 4G network standard, when CRS-Tmax / PDSCH-Tmax is greater than the second threshold, it can be determined that the feature recognition result is a preset result, for example, the wide and narrow beam effect recognition result can be determined to be the occurrence of a wide and narrow beam effect; when CRS-Tmax / PDSCH-Tmax is not greater than the second threshold, it can be determined that the feature recognition result is not a preset result, for example, the wide and narrow beam effect recognition result can be determined to be the absence of a wide and narrow beam effect.

[0220] For example, in one embodiment of the present disclosure, when the current network standard is the 5G network standard, when TRS-Tmax / PDSCH-Tmax (or PDCCH-Tmax) is greater than the second threshold, it can be determined that the feature recognition result is a preset result, for example, the wide and narrow beam effect recognition result can be determined to be the occurrence of a wide and narrow beam effect; when 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 a preset result, for example, the wide and narrow beam effect recognition result can be determined to be the absence of a wide and narrow beam effect.

[0221] According to some embodiments, in response to a calculation 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:

[0222] In response to a second ratio of any first parameter to any second parameter being greater than a third threshold, the feature recognition result is determined to be a preset result, wherein 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 preset conditions.

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

[0224] or

[0225] 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. Among them, the third threshold value can, for example, represent the relative root mean square delay spread indicator threshold th-trms-for-BF, and the value range can be, for example, 2 to 4.

[0226] For example, in one embodiment of the present disclosure, when the current network standard is the 4G network standard, when CRS-Trms / PDSCH-Trms is greater than a third threshold, it can be determined that the feature recognition result is a preset result, for example, the wide and narrow beam effect recognition result can be determined to be the occurrence of a wide and narrow beam effect; when CRS-Trms / PDSCH-Trms is not greater than the third threshold, it can be determined that the feature recognition result is not a preset result, for example, the wide and narrow beam effect recognition result can be determined to be the absence of a wide and narrow beam effect.

[0227] For example, in one embodiment of the present disclosure, when the current network standard is the 5G network standard, when TRS-Trms / PDSCH-Trms (or PDCCH-Trms) is greater than a third threshold, it can be determined that the feature recognition result is a preset result, for example, the wide and narrow beam effect recognition result can be determined to be the occurrence of a wide and narrow beam effect; when 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 a preset result, for example, the wide and narrow beam effect recognition result can be determined to be the absence of a wide and narrow beam effect.

[0228] According to some embodiments, in response to a calculation 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 a second difference between a signal to interference plus noise ratio SING in at least one second parameter and a second difference between a signal to interference plus noise ratio SING in at least one first parameter being greater than a fourth threshold, and a third ratio between a maximum Doppler Doppler in at least one second parameter and a maximum Doppler Doppler in at least one first parameter being less than a fifth threshold, it is determined that the feature recognition result is a preset result, wherein the fourth threshold represents a relative SINR indicator threshold, the fifth threshold represents a relative maximum Doppler indicator 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.

[0230] According to some embodiments, wherein the at least one first parameter comprises 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 comprises 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] For example, in one embodiment of the present disclosure, when the current network standard is a 4G network standard, PDSCH-SINR-CRS-SINR (or PSS-SINR or SSS-SINR) and the fourth threshold, and

[0234] PDSCH-Doppler / CRS-Doppler and the fifth threshold value determine the feature recognition result. Among them, the fourth threshold value can, for example, represent the relative SINR indicator threshold th-sinr-for-BF, and the value range can be, for example, 5 to 10 dB; the fifth threshold value can, for example, represent the relative maximum Doppler indicator threshold th-doppler-for-BF, and the value range can be, for example, 0.7 to 1.3.

[0235] For example, in one embodiment of the present disclosure, when the current network standard is a 4G network standard, PDSCH-SINR-CRS-SINR (or PSS-SINR or SSS-SINR) is greater than th-sinr-for-BF and

[0236] When PDSCH-Doppler / CRS-Doppler is less than th-doppler-for-BF, the feature recognition result can be determined to be a preset result. For example, the wide and narrow beam effect recognition result can be determined to be the occurrence of a wide and narrow beam effect.

[0237] When PDSCH-SINR-CRS-SINR (or PSS-SINR or SSS-SINR) is not greater than th-sinr-for-BF and / or PDSCH-Doppler / CRS-Doppler is not less than th-doppler-for-BF, it can be determined that the feature recognition result is not a preset result. For example, the wide and narrow beam effect recognition result can be determined to be that no wide or narrow beam effect occurs.

[0238] In some embodiments, when the current network standard is a 5G network standard, PDSCH-SINR (or PDCCH-SINR)-TRS CSI-SINR (or SS-SINR) and the fourth threshold, as well as PDSCH-Doppler (or PDCCH-Doppler) / TRS-Doppler and the fifth threshold, 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.

[0239] For example, in one embodiment of the present disclosure, when the current network standard is the 5G network standard, when PDSCH-SINR (or PDCCH-SINR)-TRS CSI-SINR (or SS-SINR) is greater than th-sinr-for-BF and PDSCH-Doppler (or PDCCH-Doppler) / TRS-Doppler is less than th-doppler-for-BF, it can be determined that the feature identification result is a preset result, for example, it can be determined that the wide and narrow beam effect identification result is that a wide and narrow beam effect occurs, and 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, it can be determined that the feature identification result is not a preset result, for example, it can be determined that the wide and narrow beam effect identification result is that a wide and narrow beam effect does not occur.

[0240] In some embodiments, in response to a calculation 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:

[0241] In response to a fourth ratio of any maximum delay spread Tmax in at least one second parameter to any maximum delay spread Tmax in at least one first parameter being greater than a sixth threshold, and a fifth ratio of any maximum Doppler Doppler in at least one second parameter to any maximum Doppler Doppler in at least one first parameter being less than a seventh threshold, the feature recognition result is determined to be a preset result, wherein the sixth threshold represents a relative maximum delay spread indicator threshold, the seventh threshold represents a relative maximum Doppler indicator 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.

[0242] In some embodiments, 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;

[0243] or,

[0244] 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 value can, for example, represent the relative maximum delay spread indicator threshold th-tmax-for-BF, and the value range can be, for example, 1.5 to 3; the seventh threshold value can, for example, represent the relative maximum Doppler indicator threshold th-doppler-for-BF, and the value range can be, for example, 0.7 to 1.3.

[0245] For example, in one embodiment of the present disclosure, when the current network standard is the 4G network standard, when CRS-Tmax / PDSCH-Tmax is greater than th-tmax-for-BF and PDSCH-Doppler / CRS-Doppler is less than th-doppler-for-BF, it can be determined that the feature recognition result is a preset result, for example, the wide and narrow beam effect recognition result can be determined as the occurrence of a wide and narrow beam effect. When 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, it can be determined that the feature recognition result is not a preset result, for example, the wide and narrow beam effect recognition result can be determined as the absence of a wide and narrow beam effect.

[0246] In some embodiments, when the current network standard is a 4G network standard, TRS-Tmax / PDSCH-Tmax (or PDCCH-Tmax) and the sixth threshold, and

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

[0248] For example, 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 to be a preset result, for example, the wide and narrow beam effect recognition result can be determined to be the occurrence of a wide and narrow beam effect. When TRS-Tmax / PDSCH-Tmax (or PDCCH-Tmax) is not greater than th-tmax-for-BF and / or 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 a preset result, for example, the wide and narrow beam effect recognition result can be determined to be the absence of a wide and narrow beam effect.

[0249] In some embodiments, in response to a calculation 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:

[0250] In response to the sixth ratio of 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 an eighth threshold, and the seventh ratio of 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 ninth threshold, the feature recognition result is determined to be a preset result, wherein 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.

[0251] In some embodiments, 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;

[0252] or

[0253] 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.

[0254] In some embodiments, when the current network standard is the first network standard, the feature recognition result can be determined by CRS-Trms / PDSCH-Trms and the eighth threshold corresponding to at least one time point, 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 indicator 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 indicator threshold th-doppler-for-BF, and the value range can be, for example, 0.7 to 1.3.

[0255] For example, in one embodiment of the present disclosure, when the current network standard is the first network standard, when CRS-Trms / PDSCH-Trms is greater than th-trms-for-BF and PDSCH-Doppler / CRS-Doppler is less than th-doppler-for-BF, it can be determined that the feature recognition result is a preset result, for example, the wide and narrow beam effect recognition result can be determined to be the occurrence of a wide and narrow beam effect. When 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, it can be determined that the feature recognition result is not a preset result, for example, the wide and narrow beam effect recognition result can be determined to be the absence of a wide and narrow beam effect.

[0256] In some embodiments, when the current network standard is the second network standard, the TRS-Trms / PDSCH-Trms (or PDCCH-Trms) corresponding to at least one time point and the eighth threshold value may be used, and

[0257] PDSCH-Doppler (or PDCCH-Doppler) / TRS-Doppler and the ninth threshold value determine the feature recognition result. Among them, the eighth threshold value 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 value 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.

[0258] For example, in one embodiment of the present disclosure, when the current network standard is the second network standard, TRS-Trms / PDSCH-Trms (or PDCCH-Trms) is greater than th-trms-for-BF and

[0259] When PDSCH-Doppler (or PDCCH-Doppler) / TRS-Doppler is less than th-doppler-for-BF, the feature recognition result can be determined to be a preset result. For example, the wide and narrow beam effect recognition result can be determined to be the occurrence of a wide and narrow beam effect, when TRS-Trms / PDSCH-Trms (or PDCCH-Trms) is not greater than th-trms-for-BF and / or

[0260] 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 a preset result. For example, the wide and narrow beam effect recognition result can be determined to be that no wide and narrow beam effect occurs.

[0261] In some embodiments, in response to a calculation 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:

[0262] 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 of 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, the feature identification result is determined to be a preset result, wherein the tenth threshold represents the relative SINR indicator threshold, the eleventh threshold represents the relative maximum delay spread indicator 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.

[0263] In some embodiments, 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;

[0264] or,

[0265] 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.

[0266] In some embodiments, when the current network standard is the first network standard, PDSCH-SINR-CRS-SINR (or PSS-SINR or SSS-SINR) and the tenth threshold value, and

[0267] CRS-Tmax / PDSCH-Tmax and the eleventh threshold value determine the feature recognition result. Among them, the tenth threshold value can, for example, represent the relative SINR indicator threshold th-sinr-for-BF, and the value range can be, for example, 5 to 10 dB; the eleventh threshold value can, for example, represent the relative maximum delay spread indicator threshold th-tmax-for-BF, and the value range can be, for example, 1.5 to 3.

[0268] For example, in one embodiment of the present disclosure, when the current network standard is the first network standard, PDSCH-SINR-CRS-SINR (or PSS-SINR or SSS-SINR) is greater than th-sinr-for-BF and

[0269] When CRS-Tmax / PDSCH-Tmax is greater than th-tmax-for-BF, the feature recognition result can be determined to be a preset result. For example, the wide and narrow beam effect recognition result can be determined to be the occurrence of a wide and narrow beam effect.

[0270] When 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, it can be determined that the feature recognition result is not a preset result. For example, the wide and narrow beam effect recognition result can be determined to be that no wide or narrow beam effect occurs.

[0271] In some embodiments, when the current network standard is the second network standard, the feature recognition result can be determined by PDSCH-SINR (or PDCCH-SINR)-TRS CSI-SINR (or SS-SINR) and the tenth threshold, as well as TRS-Tmax / PDSCH-Tmax (or PDCCH-Tmax) and the eleventh threshold. Among them, the tenth threshold can, for example, represent the relative SINR index threshold th-sinr-for-BF, with a value range of 5 to 10 dB; the eleventh threshold can, for example, represent the relative maximum delay spread index threshold th-tmax-for-BF, with a value range of 1.5 to 3.

[0272] For example, in one embodiment of the present disclosure, when the current network standard is the second network standard, 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, it can be determined that the feature identification result is a preset result, for example, it can be determined that the wide and narrow beam effect identification result is that the wide and narrow beam effect occurs, and 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 identification result is not a preset result, for example, it can be determined that the wide and narrow beam effect identification result is that the wide and narrow beam effect does not occur.

[0273] In some embodiments, in response to a calculation 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:

[0274] 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 and any maximum root mean square delay spread Trms in at least one first parameter being greater than the thirteenth threshold, it is determined that the feature identification result is a preset result, the twelfth threshold represents the relative SINR indicator threshold, the thirteenth 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.

[0275] In some embodiments, 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;

[0276] or,

[0277] 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.

[0278] In some embodiments, when the current network standard is the first network standard, PDSCH-SINR-CRS-SINR (or PSS-SINR or SSS-SINR) and the twelfth threshold value, and

[0279] CRS-Trms / PDSCH-Trms and the thirteenth threshold value determine the feature recognition result. Among them, the twelfth threshold value can, for example, represent the relative SINR indicator threshold th-sinr-for-BF, and the value range can be, for example, 5 to 10 dB; the thirteenth threshold value can, for example, represent the relative root mean square delay spread indicator threshold th-trms-for-BF, and the value range can be, for example, 2 to 4.

[0280] For example, in one embodiment of the present disclosure, when the current network standard is the first network standard, PDSCH-SINR-CRS-SINR (or PSS-SINR or SSS-SINR) is greater than th-sinr-for-BF and

[0281] When CRS-Trms / PDSCH-Trms is greater than th-trms-for-BF, the feature recognition result can be determined to be a preset result. For example, the wide and narrow beam effect recognition result can be determined to be the occurrence of a wide and narrow beam effect.

[0282] 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, it can be determined that the feature recognition result is not a preset result. For example, the wide and narrow beam effect recognition result can be determined to be that no wide or narrow beam effect occurs.

[0283] In some embodiments, when the current network standard is the second network standard, the feature recognition result can be determined by PDSCH-SINR (or PDCCH-SINR)-TRS CSI-SINR (or SS-SINR) and the twelfth threshold, as well as TRS-Trms / PDSCH-Trms (or PDCCH-Trms) and the thirteenth threshold. Among them, the twelfth threshold can, for example, represent the relative SINR indicator 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 indicator threshold th-trms-for-BF, and the value range can be, for example, 2 to 4.

[0284] For example, in one embodiment of the present disclosure, when the current network standard is the second network standard, when PDSCH-SINR (or PDCCH-SINR)-TRSCSI-SINR (or SS-SINR) is greater than th-sinr-for-BF and TRS-Trms / PDSCH-Trms (or PDCCH-Trms) is greater than th-trms-for-BF, it can be determined that the feature identification result is a preset result, for example, it can be determined that the wide and narrow beam effect identification result is that the wide and narrow beam effect occurs, and 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 identification result is not a preset result, for example, it can be determined that the wide and narrow beam effect identification result is that the wide and narrow beam effect does not occur.

[0285] In some embodiments,

[0286] In response to a calculation 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:

[0287] In response to the fifth difference between any SINR in at least one second parameter and any SINR in at least one first parameter being greater than the fourteenth threshold, and the tenth 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 being greater than the fifteenth threshold, and the eleventh ratio of 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 the sixteenth threshold, it is determined that the feature identification result is a preset result, wherein the fourteenth threshold represents the relative SINR indicator threshold, the fifteenth threshold represents the relative maximum delay spread indicator threshold, and 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.

[0288] In some embodiments, the at least one first parameter includes at least one of the following:

[0289] CRS-SINR, PSS-SINR, SSS-SINR, CRS-Tmax and CRS-Trms, the at least one second parameter comprising at least one of the following: PDSCH-SINR, PDSCH-Tmax and PDSCH-Trms;

[0290] or,

[0291] The at least one first parameter includes at least one of the following: TRS

[0292] 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.

[0293] In some embodiments, when the current network standard is the first network standard, PDSCH-SINR-CRS-SINR (or PSS-SINR or SSS-SINR) and fourteen thresholds, and

[0294] CRS-Tmax / PDSCH-Tmax and the fifteenth threshold, as well as CRS-Trms / PDSCH-Trms and the sixteenth threshold, determine the feature recognition result. Among them, the fourteenth threshold can, for example, represent the relative SINR indicator threshold th-sinr-for-BF, and the value range can be, for example, 5 to 10 dB; the fifteenth threshold can, for example, represent the relative maximum delay spread indicator threshold th-tmax-for-BF, and the value range can be, for example, 1.5 to 3. The sixteenth threshold can, for example, represent the relative root mean square delay spread indicator threshold th-trms-for-BF, and the value range can be, for example, 2 to 4.

[0295] For example, in one embodiment of the present disclosure, when the current network standard is the first network standard, 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, 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 a preset result. If the identification result is that a wide or narrow beam effect occurs, and 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, it can be determined that the feature recognition result is not a preset result. For example, the identification result of the wide or narrow beam effect can be determined to be that the wide or narrow beam effect does not occur.

[0296] In some embodiments, when the current network standard is the second network standard, PDSCH-SINR (or PDCCH-SINR)-TRS CSI-SINR (or SS-SINR) and the fourteenth threshold, and TRS-Tmax / PDSCH-Tmax (or PDCCH-Tmax) and the fifteenth threshold, and TRS-Trms

[0297] / PDSCH-Trms (or PDCCH-Trms) and the sixteenth threshold value, determine the wide and narrow beam effect identification result corresponding to at least one time point. Among them, the fourteenth threshold value can, for example, represent the relative SINR indicator threshold th-sinr-for-BF, and the value range can be, for example, 5 to 10dB; the fifteenth threshold value can, for example, represent the relative maximum delay spread indicator threshold th-tmax-for-BF, and the value range can be, for example, 1.5 to 3. The sixteenth threshold value can, for example, represent the relative root mean square delay spread indicator threshold th-trms-for-BF, and the value range can be, for example, 2 to 4.

[0298] For example, in one 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, 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 the occurrence of a wide and narrow beam effect, and when PDSCH-SINR (or PDCCH-SINR)-TRS When 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 a preset result. For example, the wide and narrow beam effect recognition result can be determined to be that no wide or narrow beam effect occurs.

[0299] Among them, in the embodiments of the present disclosure, multiple schemes for determining feature recognition results in response to the operation results 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 be combined with each other to determine the feature recognition results, which can improve the accuracy of determining the feature recognition results, reduce the situation where the accuracy of acquiring the wireless channel state information required for channel estimation is poor, improve the receiving state of the communication device, and improve the communication quality of the communication device.

[0300] 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 sensing neural network model, and a feature recognition result output by the beam sensing neural network model is obtained, wherein the feature recognition result is used to indicate whether the at least one first parameter of the first beam feature set and the at least one second parameter of the second beam feature set meet a preset condition;

[0301] The specific process is as described above and will not be repeated here.

[0302] Among them, in one embodiment of the present disclosure, there is no limitation on the type of preset beam sensing neural network model. 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 can be used.

[0303] According to some embodiments, 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 sensing neural network model, and obtaining the feature recognition result output by the beam sensing neural network model includes:

[0304] 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 sensing neural network model, and obtaining a vector corresponding to the at least one first parameter and the at least one second parameter;

[0305] The vector is identified and processed using the activation function of the preset beam sensing neural network model to obtain the feature recognition result output by the beam sensing neural network model.

[0306] In some embodiments, when the current network standard is the first network standard, CRS-SINR, CRS-Tmax, CRS-Trms, CRS-Doppler, PDSCH-SINR, PDSCH-Tmax, PDSCH-Trms, and PDSCH-Doppler may be input into a preset beam sensing neural network model. The beam sensing neural network model may be controlled to determine whether a wide or narrow beam effect occurs at the current time point through reasoning.

[0307] In some embodiments, when the current network standard is the second network standard, 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 sensing neural network model. The beam sensing neural network model can be controlled to determine whether a wide or narrow beam effect occurs at the current time point through reasoning.

[0308] In response to some embodiments, the wide-narrow beam effect identification result may be, for example, an output period Tbf, and its value range may be, for example, 0.5 to 5 ms.

[0309] In some embodiments, the input features of the preset beam sensing neural network model can be, for example, where x[t] can be, for example, N in ×1-dimensional vector, where N in Take corresponding values ​​in 4G / 5G network status.

[0310] Among them, when the current network standard is the first network standard, the input of the preset beam sensing neural network model is expressed in the following form:

[0311] 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 (wherein the upper right subscript T at the end of the formula represents transposition, that is, the 1×8 row vector is rearranged in sequence to an 8×1 column vector). Each element of the vector represents the result obtained by the tth sampling, and X[t] represents the signal feature obtained by the tth sampling.

[0312] Wherein, when the current network standard is the second network standard, the input of the preset beam sensing neural network is expressed in the following form:

[0313] 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 , is a 9×1 vector, each element of which represents the result obtained by the t-th sampling, and X[t] represents the signal characteristics obtained by the t-th sampling.

[0314] In some embodiments, under the beam sensing neural network model based on the fully connected neural network, each time a signal feature is sampled, only the signal feature of the current sample is used to call the fully connected neural network model once to obtain the inference output value corresponding to the current sample. in ×1-dimensional vector Indicates that the [t] symbol representing the sampling time can be omitted.

[0315] In some embodiments, Figure 8a is an example schematic diagram of a neural network model according to an exemplary embodiment. Figure 8a As shown, the preset beam sensing neural network model can be, for example, a fully connected network model. The network model includes 1 input layer, M≥1 hidden layers and 1 output layer, and the corresponding node numbers are In the present invention, the number of hidden layers ranges from 1 to 16, and the number of nodes in each hidden layer is The value range is 1 to 1024.

[0316] Each node in hidden layer 1 is defined as The calculation method is

[0317]

[0318] Where W 1 yes dimensional matrix, b 1 yes dimensional vectors, both of which have preset fixed real coefficients and are obtained through the previous neural network training process. 1 (·) indicates that each element of the input vector is activated by an activation function. The definition of the activation function is the same as that of a general neural network and will not be repeated here. Taking the activation function ReLU as an example, it is defined as f(x) = max(x, 0), then the calculation method of the hidden layer 1 is That is dimensional vector W 1 x+b 1 Each element of is capped at 0 to get the result.

[0319] According to some embodiments, each node in the hidden layer k is defined as The calculation method is

[0320]

[0321] Where W k yes dimensional matrix, b k yes dimensional vector, f k (·) represents the activation function used by the kth layer. Similarly, W k and b k It is obtained in advance through the pre-training process, and the activation function is defined as above.

[0322] According to some embodiments, each node in the output layer is defined as The calculation method is

[0323]

[0324] Where W out yes dimensional matrix, b out YesN out ×1-dimensional vector, f out (·) represents the activation function applicable to the output layer. Similarly, W out and b out It is obtained in advance through the pre-training process, and the activation function is defined as above.

[0325] According to some embodiments, N out The default value is 1, and the following judgment is made based on the output layer node: If z 1 >0, the beam perception neural network determines that the wide and narrow beam effect occurs at the current moment, otherwise it determines that the wide and narrow beam effect does not occur at the current moment.

[0326] Among them, in one embodiment of the present disclosure, the number of input nodes N in =8, the number of output nodes is N out =1, number of hidden layers M = 2, number of hidden layer nodes

[0327] The activation function of each layer is Sigmoid;

[0328] W 1 is a 6×8 dimensional matrix:

[0329]

[0330] b 1 is a 6×1 dimensional vector: [0.56686;

[0332] -0.47827;

[0333] -0.91867; 1.8984; 0.61859; 0.030253]

[0337] W 2 is a 4×6 dimensional matrix:

[0338]

[0339] b 2 is a 4×1 dimensional vector:

[0340] [-0.32724; 1.7266; 0.15219;

[0343] -1.319]

[0344] W out is a 1×4 dimensional vector:

[0345] [-0.036337 -1.234 -1.2407 -1.4056]

[0346] b out is a 1×1 dimensional scalar:

[0347] [-0.3172]

[0348] Among them, in one embodiment of the present disclosure, the number of input nodes N in =9, the number of output nodes is N out =1, number of hidden layers M = 3, number of hidden layer nodes

[0349] The activation function of each hidden layer is ReLU, and the activation function of the output layer is Softmax;

[0350] W 1 is a 4×9 dimensional matrix:

[0351]

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

[0353] [-0.52743;

[0354] -0.72111;

[0355] -0.96918; 1.2817]

[0357] W 2 is a 3×4 dimensional matrix:

[0358]

[0359] b 2 is a 3×1 dimensional vector: [ 0.68037; 0.043459; 0.54384]

[0363] W 3 is a 2×3 dimensional matrix:

[0364] [0.48873 -0.74289 1.1725;

[0365] 1.49 1.5016-1.5343]

[0366] b 3 is a 2×1 dimensional vector: [1.203;

[0368] -0.50165]

[0369] W put is a 1×2 dimensional vector:

[0370] [-1.6399 0.18647]

[0371] b out is a 1×1 dimensional scalar: [0.30811]

[0373] In one embodiment of the present disclosure, for example, a beam sensing neural network model can be trained, wherein the training data and the test data can come from historical communication data, or from simulation data. The present disclosure embodiment is not limited to this. In the actual communication process or data simulation, the signal characteristics related to the input of the beam sensing neural network model can be recorded, and the label of the signal characteristics (i.e., the expected output value) can be marked according to the current actual communication performance or simulation performance. Each sampling can obtain a set of input data and the corresponding output label. Taking the second network standard as an example, assuming that the input obtained by 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 , the output value obtained by marking is z[t], then {x[t], z[t] constitutes a training or test data of the beam sensing neural network model. After multiple samplings, multiple data are obtained, which can be divided into training data sets and test data sets. Among them, the training data set is used for neural network parameter training, that is, to obtain the preset parameter matrices / vectors / scalars mentioned above, and the test data set is used to verify the performance of the training results.

[0374] In some embodiments, Figure 8b is an example schematic diagram of a neural network model according to an exemplary embodiment. Figure 8b As shown, the preset beam sensing neural network model can be, for example, a recurrent neural network model. Under the beam sensing model based on the recurrent neural network, each time a signal feature is sampled, the recurrent neural network model is called once based on the signal features of the previous L samples from the current sample to obtain the inference output value corresponding to the current sample. Therefore, in the recurrent neural network, the input data is represented by [x[t-L+1],…,x[t-1],x[t]].

[0375] According to some embodiments, the network model includes L hidden states {h[t-L+1],…,h[t], where each hidden state is dimensional vector, and L fully connected layers with activation functions {φ 1 ,…,φ L} and 1 output layer φ out In the present invention, the number of hidden states ranges from 1 to 16, and the dimension of each hidden state is The value range is 1 to 1024.

[0376] According to some embodiments, the first hidden state h[t-L+1] is calculated as (1) as follows:

[0377] h[t-L+1]=f 1 (W hx, x[t-L+1]+b 1 ) (1)

[0378] Where W hx, yes dimensional matrix, b 1 yes dimensional vectors, both of which have preset fixed real coefficients and are obtained through the previous neural network training process. 1 (·) indicates that each element of the input vector is subjected to an activation function. 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 hidden state 1 is calculated as follows: first calculate the intermediate variable a = W hx,1 x[t-L+1]+b 1 ,for dimensional vector, and then calculate h[t-L+1], whose i-th element is (1+e -a[i] ) -1 , where a[i] is calculated from the i-th element of the intermediate variable a.

[0379] The calculation method (2) of the kth hidden state (k=2,…,L) is:

[0380] h[t-L+k]=f k (W hx, x[t-L+k]+W hh, h[t-L+k-1]+b k ) (2)

[0381] Among them, W hx, yes dimensional matrix, W hh, yes dimensional matrix, b k yes dimensional vectors, all of which are preset fixed real coefficients obtained through the pre-training process of the neural network. h[t-L+k-1] is the k-1th hidden state ( dimensional vector), f k (·) represents the activation function applicable to the kth layer.

[0382] According to some embodiments, each node in the output layer is defined as The calculation method (3) is:

[0383] z=f out (W out h[t]+b out ) (3)

[0384] Among them, W out yes dimensional matrix, b out YesN out ×1-dimensional vector, both of which are preset fixed real coefficients obtained through the previous neural network training process. out (·) represents the activation function applicable to the output layer, and the activation function is defined as above.

[0385] According to some embodiments, N out The default value is 1, and the following judgment is made based on the output layer node: If z 1 >0, the beam perception neural network determines that the wide and narrow beam effect occurs at the current moment, otherwise it determines that the wide and narrow beam effect does not occur at the current moment.

[0386] According to some embodiments, the number of input nodes N in =8, the number of output nodes is N out =1, number of hidden states L = 2, number of hidden layer nodes

[0387] The activation function of each layer is Sigmoid;

[0388] W hx, is a 2×8 dimensional matrix:

[0389]

[0390] b 1 is a 2×1 dimensional vector: [0.13263; 2.5974]

[0393] W hx, is a 3×8 dimensional matrix:

[0394]

[0395] b 2 is a 3×1 dimensional vector:

[0396] [-0.41078;

[0397] -0.097416;

[0398] -0.15023]

[0399] W hh, is a 3×2 dimensional matrix:

[0400] [-0.27852 0.91732; 0.12799 0.76073;

[0402] -0.075746-0.99056]

[0403] W out is a 1×3 dimensional vector:

[0404] [-0.45479 -0.48775 -0.67786]

[0405] b out is a 1×1 dimensional scalar: [1.2692]

[0407] According to some embodiments, the number of input nodes N in =9, the number of output nodes is N out =1, number of hidden states L = 3, number of hidden layer nodes

[0408] The activation functions of the first, second, and third hidden layers are Sigmoid, ReLU, and Softplus respectively, and the output layer activation function is Softmax;

[0409] W hx, is a 3×9 dimensional matrix:

[0410]

[0411] b 1 is a 3×1 dimensional vector; [1.4983; 0.93334;

[0414] -0.84369]

[0415] W hx, is a 2×9 dimensional matrix:

[0416]

[0417] b 2 is a 2×1 dimensional vector: [0.98282;

[0419] -0.85696]

[0420] W hh, is a 2×3 dimensional matrix:

[0421] [-0.113 -0.92787 0.38149;

[0422] 1.1621 -0.32756 -0.70608]

[0423] W hx, is a 2×9 dimensional matrix:

[0424]

[0425] b 3 is a 2×1 dimensional vector:

[0426] [-1.2314; 0.49445]

[0428] W hh, is a 2×2 dimensional matrix;

[0429] [-1.6949 0.95131;

[0430] -0.37369-1.6743]

[0431] W out is a 1×2 dimensional vector: [ 0.88022 0.77134 ]

[0433] b out is a 1×1 dimensional scalar:

[0434] [-1.4642]

[0435] Among them, in one embodiment of the present disclosure, the training data or test data of the recurrent neural network can come from historical communication actual data, or simulation data. In the actual communication process or data simulation process, the signal characteristics related to the neural network input can be recorded, and the label of the signal characteristic (i.e., the expected output value) can be marked according to the current actual communication performance or simulation performance. A set of input data and the corresponding output label can be obtained for each sampling. Taking the second network standard, i.e., the 5G network state, as an example, assuming that the input obtained by 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, the output value obtained by marking is z[t]. The difference from the fully connected neural network model is that each piece of data in the recurrent neural network contains not only the input and output of the current moment, but also the input of the historical L-1 moments, that is, {x[t-L+1],…,x[t],z[t]} constitutes a piece of training or test data for the neural network. After multiple samplings, multiple pieces of data are obtained, which can be divided into training data sets and test data sets. The training data set is used for recurrent neural network parameter training, that is, to obtain the preset parameter matrices / vectors / scalars of the recurrent neural network model, and the test data set is used to verify the performance of the training results.

[0436] Under a given neural network model, the training goal of the neural network model is to minimize the error between the predicted output value and the actual output value label. In order to quantify the gap between the predicted value and the actual value, a loss function can be defined. For example, the loss function 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 a matrix or vector.

[0437] Based on the above training data and loss function, we first set the initial values ​​of all parameters to be solved of the neural network (including W hx,1 ,…,W hx,L ,W out ,b 1 ,…,b L ,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-mentioned parameters to be solved during the iteration until the sum of the loss functions of all training set samples meets the requirements.

[0438] 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 the 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.

[0439] 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 results of multiple decision trees can be voted on, and the classification result with more votes is the final classification result.

[0440] 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, for example, as shown in Figure 8d shown. 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 child node the node will go to next.

[0441] Assuming that the order relationship is used as the determination condition for each node, 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.

[0442] Specifically, for the decision tree with Q layers of internal nodes shown in Figure 8d , based on the input data will go through Q + 1 determinations to obtain the final judgment result:

[0443] First judgment: The root node has preset parameters [k 0,1 ,T 0,1 ], obtained through pre-training, where the first parameter takes values ​​1,…,N in The second parameter is a real number threshold. Is it true? If true, enter the left branch connected to the root node and mark the judgment result as c 1 = 0, otherwise enter the right branch connected to the root node, and mark the judgment result as c 1 =1.

[0444] Second judgment: corresponding to the internal nodes of the first layer, with preset parameters [k 1,1 ,T 1,1 ],[k 1,2 ,T 1,2 ], obtained through pre-training, where the first parameter of each group of parameters takes the value 1,…,N in The second parameter is a real number threshold. According to the first judgment result c 1 , determine the corresponding parameters of the associated nodes for the second determination determination Is it true? If true, enter the left branch connected to the internal node and mark the judgment result as c 2 = 0, otherwise enter the right branch connected to the internal node, and mark the judgment result as c 2 =1.

[0445] The kth decision (3≤k≤Q+1): corresponds to the internal nodes of the k-1th layer, with preset parameters After pre-training, the first parameter of each group of parameters takes the value 1,…,N in The second parameter is a real number threshold. According to the 1st,…,k-1th judgment results c 1 ,…,c k-1 , determine the corresponding parameters of the associated nodes for the kth decision determination Is it true? If so, enter the left branch connected to the internal node and mark the final judgment result as A. Otherwise, enter the right branch connected to the internal node and mark the final judgment result as B.

[0446] According to some embodiments, the number of input nodes N in =8, number of decision trees P = 3, number of internal node layers Q = 1. The corresponding parameters of random forest are:

[0447] 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];

[0448] 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];

[0449] 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].

[0450] 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 random forest are:

[0451] 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].

[0452] According to some embodiments, the training or test data of the random forest may come from, for example, actual historical communication data or numerical simulation. In the actual communication process or numerical simulation, the signal features related to the neural network input may be recorded, and the label of the signal feature (i.e., the expected output value) may be marked according to the current actual communication performance or simulation performance. Each sampling may obtain a set of input data and the corresponding output label. Taking the second network standard, i.e., the 5G network state, as an example, assuming that the input obtained by 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 output value obtained by marking is z[t], then {x[t], z[t] constitutes a training or test data of the random forest. After multiple samplings, multiple data are obtained, which can be divided into a training data set and a test data set, wherein the training data set is used for random forest parameter training, that is, to obtain the preset parameter matrices / vectors / scalars mentioned in this section, and the test data set is used to verify the performance of the training results.

[0453] Based on the above training data, each decision tree in the random forest can be constructed, for example, in the following manner, where different decision trees are constructed independently and in the same manner:

[0454] Extract some samples from the total training set with replacement, and use the extracted samples to train the decision tree;

[0455] Each sample has N in input attributes, at each node of the decision tree that needs to be split, a specific strategy is used to select one attribute as the splitting attribute of the node, and the corresponding splitting threshold is determined, wherein the attribute and threshold determination strategy are not limited, for example, information gain can be used.

[0456] During the decision tree formation process, each node is split according to the previous step until the maximum depth is reached or it can no longer be split;

[0457] In order to ensure the consistency of the process (i.e., after a given maximum depth, the total number of decisions in any case is the same), branches with a depth less than the maximum depth (which are terminated early because the sample does not support further splitting) are extended to the maximum depth. The extension method is: for leaf nodes that are less than the maximum depth, continue to expand the branch, and the judgment parameters of each decision node are set to [1, T max +1], where Tmax Guaranteed to be greater than x 1 [t] takes a value in any scenario, for example, infinity; at the same time, the final leaf node judgment results corresponding to these branches are all the judgment results of the leaf nodes that are less than the maximum depth.

[0458] 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, the first beam feature set or the second beam feature set is selected as a source for acquiring wireless channel state information.

[0459] The specific process is as described above and will not be repeated here.

[0460] In response to some embodiments, for a continuous observation fixed period, the first time information is any moment of the current period in the continuous observation preset period, and the second time information is the next preset period adjacent to the current period. At this time, the first time information and the second time information can be shown as follows: Fig. 9 shown.

[0461] In response to some embodiments, selecting the first beam feature set or the second beam feature set as a source for acquiring wireless channel state information includes:

[0462] In response to the feature recognition result corresponding to the first time information satisfying the first result requirement, and the wireless resource control connection of the communication device has not been reconfigured or released, it is determined that the acquisition source corresponding to the wireless channel state information in the second time information is the dynamic beam feature acquisition source, wherein the first time information is any moment of the current period in the continuous observation preset period, and 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 number of preset results in the feature recognition results corresponding to the first time information meets the quantity requirement.

[0463] According to some embodiments, selecting the first beam feature set or the second beam feature set as a source for acquiring wireless channel state information includes:

[0464] When the feature recognition results corresponding to the first time information are all preset results and the wireless resource control connection of the communication device has not been reconfigured or released, it is determined that the acquisition source corresponding to the wireless channel state information in the second time information is the dynamic beam feature acquisition source.

[0465] 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 a source for obtaining the wireless channel state information includes:

[0466] When the first number of preset results in the feature identification results corresponding to the first time information meets the quantity requirement and the wireless resource control connection of the communication device has not been reconfigured or released, it is determined that the acquisition source corresponding to the wireless channel state information in the second time information is the dynamic beam feature acquisition source.

[0467] The first quantity may also be, for example, a first quantity ratio, a first quantity percentage, a first quantity multiple, etc. This embodiment of the present disclosure is not limited to this.

[0468] According to some embodiments, selecting the first beam feature set or the second beam feature set as a source for acquiring wireless channel state information includes:

[0469] In response to the feature recognition result corresponding to the first time information satisfying the second result requirement, it is determined that the acquisition source corresponding to the wireless channel state information in the second time information is the static beam feature acquisition source, wherein the first time information is any moment in 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 first number of preset results in the feature recognition results corresponding to the first time information does not meet the quantity requirement.

[0470] According to some embodiments, the first time information is any moment of the current period in the continuous observation preset period, and the first beam feature set or the second beam feature set is selected as the acquisition source of the wireless channel state information, including:

[0471] When the feature recognition results corresponding to the first time information are not all preset results, it is determined that the acquisition source corresponding to the wireless channel state information in the second time information is the static beam feature acquisition source.

[0472] Among them, the time information is a preset period of continuous observation, for example, it can be an observation time window (ObservationTime, Tobs) period, for example, it can be a fixed observation time window, and its value range can be, for example, 50 to 100ms or the period corresponding to the number of continuous observations (number of observations, Nbf) effective wide and narrow beam effect identification results, where Nbf is a fixed number of observations, and the value range is 20 to 50. Among them, the time information is a Tobs period, which can balance the recognition success rate and recognition timeliness, improve the efficiency of determining the source of wireless channel state information acquisition, and improve the data receiving performance of communication equipment.

[0473] In response to some embodiments, the first time information is any moment of the current period in the continuous observation preset period, and the first beam feature set or the second beam feature set is selected as a source for obtaining the wireless channel state information, including:

[0474] When a first number of preset results in the feature recognition result corresponding to the first time information does not meet the quantity requirement, it is determined that the acquisition source corresponding to the wireless channel state information in the second time information is the static beam feature acquisition source.

[0475] The quantity requirement may be, for example, that the ratio of the first quantity to the third quantity is less than a seventeenth threshold. The third quantity may be, for example, the total number of the wide and narrow beam effect recognition results corresponding to the first time information.

[0476] The seventeenth threshold value may, for example, represent an observation ratio threshold (Rate of observation, Rbf), and its value range may, for example, be 60% to 90%.

[0477] The time information is a preset continuous observation period, for example, a Tobs period, and Tobs may be, for example, a fixed observation time window, and its value range may be, for example, 50 to 100 ms or a period corresponding to Nbf consecutive valid wide and narrow beam effect identification results, wherein Nbf is a fixed number of observations, and its value range may be 20 to 50. The time information being a Tobs period may balance the recognition success rate and recognition timeliness, and may improve the efficiency of determining the source of wireless channel state information acquisition, and may improve the data receiving performance of communication equipment.

[0478] According to some embodiments, for the continuous observation sliding cycle, the first time information is any moment of the current cycle in the continuous observation sliding cycle, and the second time information is the time information before the next feature recognition result is not obtained. At this time, the first time information and the second time information example schematic diagram can be, for example, as shown in Fig.10 As shown in FIG. 1 , the periodic sliding direction is an example schematic direction.

[0479] According to some embodiments, selecting the first beam feature set or the second beam feature set as a source for acquiring wireless channel state information includes:

[0480] In response to the feature recognition result corresponding to the first time information satisfying the first result requirement, and the wireless resource control connection of the communication device has not been reconfigured or released, it is determined that the acquisition source corresponding to the wireless channel state information in the second time information is the dynamic beam feature acquisition source, wherein the first time information is any moment of the current period in 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 number of preset results in the feature recognition results corresponding to the first time information meets the quantity requirement.

[0481] According to some embodiments, selecting the first beam feature set or the second beam feature set as a source for acquiring wireless channel state information includes:

[0482] 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 in the second time information is a static beam feature acquisition source, wherein the first time information is any moment of the current period in 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 a result requirement that the feature recognition results corresponding to the first time information are not all preset results or a result requirement that a second number of preset results in the feature recognition results corresponding to the first time information does not meet the quantity requirement;

[0483] Before the feature recognition result corresponding to the second time information is obtained, the update information corresponding to the first time information is observed, and the updated first time information is used as the first time information to re-determine the acquisition source corresponding to the wireless channel state information in the second time information.

[0484] According to some embodiments, the first time information may be, for example, a continuously observed 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 has not been reconfigured or released, the wireless channel state information acquisition source is locked to the dynamic beam feature acquisition source before the feature recognition result is reacquired.

[0485] According to some embodiments, the first time information may be, for example, a continuously observed Tobs sliding window. When the feature recognition results corresponding to the first time information are not all preset results, before the feature recognition results are reacquired, the wireless channel state information acquisition source is the static beam feature acquisition source. The preset result may be, for example, "yes", which is not limited in the embodiments of the present disclosure.

[0486] According to some embodiments, before the feature recognition result is reacquired, the sliding window is updated and the beam feature acquisition source is re-determined.

[0487] Among them, the value range of the sliding observation time window length Tobs corresponding to the continuous observation Tobs sliding window can be, for example, 50 to 100 ms or the period corresponding to Nbf consecutive effective wide and narrow beam effect identification results, where Nbf is the number of sliding observations, and the value range can be, for example, 20 to 50.

[0488] In response to some embodiments, the first time information is any moment of the current period in the continuous observation sliding period, and the first beam feature set or the second beam feature set is selected as a source for obtaining the wireless channel state information, including:

[0489] When the second number of preset results in the feature identification result corresponding to the first time information meets the quantity requirement and the wireless resource control connection of the communication device has not been reconfigured or released, it is determined that the acquisition source corresponding to the wireless channel state information in the second time information is the dynamic beam feature acquisition source, wherein the second time information is the time information before the next feature identification result is not obtained.

[0490] In response to some embodiments, the first time information is any moment of the current period in the continuous observation sliding period, and the first beam feature set or the second beam feature set is selected as a source for obtaining the wireless channel state information, including:

[0491] If the second number of preset results in the feature recognition result corresponding to the first time information does not meet the quantity requirement, determining the acquisition source corresponding to the wireless channel state information in the second time information as the static beam feature acquisition source;

[0492] Before the feature recognition result corresponding to the second time information is obtained, the update information corresponding to the first time information is observed, and the updated first time information is used as the first time information to re-determine the acquisition source corresponding to the wireless channel state information in the second time information. The first time information is the sliding observation time window length, and the first time information is the period corresponding to the effective wide and narrow beam effect recognition result of the preset time length or the preset number of consecutive sliding observations.

[0493] The quantity requirement may be, for example, that the ratio of the second quantity to the fourth quantity is greater than an eighteenth threshold. The fourth quantity may be, for example, the total number of the wide and narrow beam effect recognition results corresponding to the first time information.

[0494] The nineteenth threshold value may represent the observation ratio threshold Rbf, for example, and its value range may be, for example, 60% to 90%. The sliding observation time window length Tobs corresponding to the continuous observation Tobs sliding window may have a value range of, for example, 50 to 100 ms or a period corresponding to Nbf consecutive valid wide and narrow beam effect identification results, where Nbf is the number of sliding observations, and its value range may be, for example, 20 to 50.

[0495] It should be noted that the various thresholds in the embodiments of the present disclosure do not specifically refer to a fixed threshold. For example, they can be adjusted accordingly according to the threshold modification instruction, or changed accordingly according to the network standard. The embodiments of the present disclosure do not limit this.

[0496] In some or related embodiments, by acquiring the current resident cell of the communication device; responding to the network standard information corresponding to the current resident cell and the downlink beamforming determination order, determining the downlink beamforming support information corresponding to the current network standard of the current resident cell; therefore, a beam sensing mechanism can be provided, which can determine the downlink beamforming support information in response to the network standard information and the downlink beamforming determination order, which can improve the accuracy of the downlink beamforming support information determination, and can determine the support for downlink dynamic beamforming. According to the downlink static beam feature set and the downlink dynamic beam feature set, the feature recognition result is determined to improve the accuracy of the feature recognition result determination, which can improve the accuracy of the acquisition source determination corresponding to the wireless channel state information, reduce the situation where the wide and narrow beam effects cause the poor accuracy of the acquisition of the wireless channel state information required for channel estimation, and can improve the receiving state of the communication device, improve the robustness of the downlink receiving performance, and improve the communication quality of the communication device. Secondly, the wide and narrow beam effect identification 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 the acquisition source determination.

[0497] Fig.11 FIG. 1 is a block diagram of a beam sensing device according to an exemplary embodiment. Fig.11 , the device 1100 comprises:

[0498] A set acquisition unit 1101 is used to acquire a first beam feature set and a second beam feature set related to a current network standard;

[0499] The source determination unit 1102 is used to select the first beam feature set or the second beam feature set as the source for obtaining the 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 satisfying a preset condition, wherein 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.

[0500] According to some embodiments, the source determination unit 1102 is further configured to:

[0501] In response to a calculation 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 feature recognition result is obtained, wherein 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.

[0502] According to some embodiments, the source determination unit 1102 is used, when 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, to specifically:

[0503] A difference result and / or a comparison 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 is compared with at least one threshold information to obtain a feature recognition result.

[0504] According to some embodiments, the source determination unit 1102 is used to 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, specifically for:

[0505] In response to a first difference between any second parameter and any first parameter being greater than a first threshold, the feature recognition result is determined to be a preset result, 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 a preset condition.

[0506] According to some embodiments, wherein the at least one first parameter includes at least one of the following: a cell-specific reference signal-signal to interference plus noise ratio CRS-SINR, a primary synchronization signal-signal to interference plus noise ratio PSS-SINR, and a secondary synchronization signal-signal to interference plus noise ratio SSS-SINR; the at least one second parameter includes at least one of the following: a physical downlink shared channel-signal to interference plus noise ratio PDSCH-SINR;

[0507] Alternatively, 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.

[0508] According to some embodiments, the source determination unit 1102 is used to 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, specifically for:

[0509] In response to a first ratio of any first parameter to any second parameter being greater than a second threshold, the feature recognition result is determined to be a preset result, wherein the second 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 preset conditions.

[0510] According to some embodiments, wherein the at least one first parameter comprises at least one of the following: a cell-specific reference signal-maximum delay spread CRS-Tmax, and the at least one second parameter comprises at least one of the following: a physical downlink shared channel-maximum delay spread PDSCH-Tmax;

[0511] or

[0512] 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.

[0513] According to some embodiments, the source determination unit 1102 is used to 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, specifically for:

[0514] In response to a second ratio of any first parameter to any second parameter being greater than a third threshold, the feature recognition result is determined to be a preset result, wherein 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 preset conditions.

[0515] According to some embodiments, wherein the at least one first parameter comprises at least one of the following: a cell-specific reference signal-root mean square delay spread CRS-Trms, and the at least one second parameter comprises at least one of the following: a physical downlink shared channel-root mean square delay spread PDSCH-Trms;

[0516] or

[0517] 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.

[0518] According to some embodiments, the source determination unit 1102 is used to 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, specifically for:

[0519] In response to a second difference between a signal to interference plus noise ratio SING in at least one second parameter and a second difference between a signal to interference plus noise ratio SING in at least one first parameter being greater than a fourth threshold, and a third ratio between a maximum Doppler Doppler in at least one second parameter and a maximum Doppler Doppler in at least one first parameter being less than a fifth threshold, it is determined that the feature recognition result is a preset result, wherein the fourth threshold represents a relative SINR indicator threshold, the fifth threshold represents a relative maximum Doppler indicator 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.

[0520] According to some embodiments, wherein the at least one first parameter comprises 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 comprises at least one of the following: PDSCH-SINR, physical downlink shared channel-maximum Doppler PDSCH-Doppler;

[0521] or,

[0522] 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, PDC CH-SINR, physical downlink control channel-maximum Doppler PDCCH-Doppler and physical downlink shared channel-maximum Doppler PDSCH-Doppler.

[0523] According to some embodiments, the source determination unit 1102 is used to 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, specifically for:

[0524] In response to a fourth ratio of any maximum delay spread Tmax in at least one second parameter to any maximum delay spread Tmax in at least one first parameter being greater than a sixth threshold, and a fifth ratio of any maximum Doppler Doppler in at least one second parameter to any maximum Doppler Doppler in at least one first parameter being less than a seventh threshold, the feature recognition result is determined to be a preset result, wherein the sixth threshold represents a relative maximum delay spread indicator threshold, the seventh threshold represents a relative maximum Doppler indicator 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.

[0525] According to some embodiments, wherein the at least one first parameter comprises at least one of: CRS-Tmax and cell-specific reference signal-maximum Doppler CRS-Doppler, and the at least one second parameter comprises at least one of: PDSCH-Doppler and PDCCH-Tmax;

[0526] or,

[0527] 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-Dopple r.

[0528] According to some embodiments, the source determination unit 1102 is used to 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, specifically for:

[0529] In response to the sixth ratio of 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 an eighth threshold, and the seventh ratio of 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 ninth threshold, the feature recognition result is determined to be a preset result, wherein 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.

[0530] According to some embodiments, wherein the at least one first parameter comprises at least one of: CRS-Trms and CRS-Dopple, and the at least one second parameter comprises at least one of: PDSCH-Trms and PDSCH-Doppler;

[0531] or

[0532] 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.

[0533] According to some embodiments, the source determination unit 1102 is used to 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, specifically for:

[0534] 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 of 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, the feature identification result is determined to be a preset result, wherein the tenth threshold represents the relative SINR indicator threshold, the eleventh threshold represents the relative maximum delay spread indicator 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.

[0535] According to some embodiments, wherein the at least one first parameter comprises at least one of: CRS-SINR, PSS-SINR, SSS-SINR and CRS-Tmax, and the at least one second parameter comprises at least one of: PDSCH-SINR and PDSCH-Tmax;

[0536] or,

[0537] 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 PDC CH-Tmax.

[0538] According to some embodiments, the source determination unit 1102 is used to 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, specifically for:

[0539] 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 and any maximum root mean square delay spread Trms in at least one first parameter being greater than the thirteenth threshold, it is determined that the feature identification result is a preset result, the twelfth threshold represents the relative SINR indicator threshold, the thirteenth 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.

[0540] According to some embodiments, wherein the at least one first parameter comprises at least one of: CRS-SINR, PSS-SINR and SSS-SINR and CRS-Trms, and the at least one second parameter comprises at least one of: PDSCH-SINR and PDSCH-Tmax;

[0541] or,

[0542] 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 PDCC H-Trms.

[0543] According to some embodiments, the source determination unit 1102 is used to 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, specifically for:

[0544] In response to the fifth difference between any SINR in at least one second parameter and any SINR in at least one first parameter being greater than the fourteenth threshold, and the tenth 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 being greater than the fifteenth threshold, and the eleventh ratio of any maximum root mean square delay spread Trms in at least one second parameter and any maximum root mean square delay spread Tr ms in at least one first parameter being greater than the sixteenth threshold, it is determined that the feature identification result is a preset result, wherein the fourteenth threshold represents the relative SINR indicator threshold, the fifteenth threshold represents the relative maximum delay spread indicator threshold, and 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.

[0545] According to some embodiments, wherein the at least one first parameter comprises at least one of: CRS-SINR, PSS-SINR, SSS-SINR, CRS-Tmax, and CRS-Trms, and the at least one second parameter comprises at least one of: PDSC H-SINR, PDSCH-Tmax, and PDSCH-Trms;

[0546] or,

[0547] 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.

[0548] According to some embodiments, the source determination unit 1102 is further configured to:

[0549] 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 sensing neural network model to obtain a feature recognition result output by the beam sensing neural network model, wherein 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 preset conditions.

[0550] According to some embodiments, the source determination unit 1102 is used 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 sensing neural network model, and obtain the feature recognition result output by the beam sensing neural network model, specifically for:

[0551] 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 sensing neural network model, and obtaining a vector corresponding to the at least one first parameter and the at least one second parameter;

[0552] The vector is identified and processed using the activation function of the preset beam sensing neural network model to obtain the feature recognition result output by the beam sensing neural network model.

[0553] According to some embodiments, the source determination unit 1102, when used to select the first beam feature set or the second beam feature set as a source for obtaining the wireless channel state information, is specifically used to:

[0554] In response to the feature recognition result corresponding to the first time information satisfying the first result requirement, and the wireless resource control connection of the communication device has not been reconfigured or released, it is determined that the acquisition source corresponding to the wireless channel state information in the second time information is the dynamic beam feature acquisition source, wherein the first time information is any moment of the current period in the continuous observation preset period, and 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 number of preset results in the feature recognition results corresponding to the first time information meets the quantity requirement.

[0555] According to some embodiments, the source determination unit 1102, when used to select the first beam feature set or the second beam feature set as a source for obtaining the wireless channel state information, is specifically used to:

[0556] In response to the feature recognition result corresponding to the first time information satisfying the second result requirement, it is determined that the acquisition source corresponding to the wireless channel state information in the second time information is the static beam feature acquisition source, wherein the first time information is any moment in 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 first number of preset results in the feature recognition results corresponding to the first time information does not meet the quantity requirement.

[0557] According to some embodiments, the source determination unit 1102, when used to select the first beam feature set or the second beam feature set as a source for obtaining the wireless channel state information, is specifically used to:

[0558] In response to the feature recognition result corresponding to the first time information satisfying the first result requirement, and the wireless resource control connection of the communication device has not been reconfigured or released, it is determined that the acquisition source corresponding to the wireless channel state information in the second time information is the dynamic beam feature acquisition source, wherein the first time information is any moment of the current period in 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 number of preset results in the feature recognition results corresponding to the first time information meets the quantity requirement.

[0559] According to some embodiments, the source determination unit 1102, when used to select the first beam feature set or the second beam feature set as a source for obtaining the wireless channel state information, is specifically used to:

[0560] 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 in the second time information is a static beam feature acquisition source, wherein the first time information is any moment of the current period in 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 a result requirement that the feature recognition results corresponding to the first time information are not all preset results or a result requirement that a second number of preset results in the feature recognition results corresponding to the first time information does not meet the quantity requirement;

[0561] Before the feature recognition result corresponding to the second time information is obtained, the update information corresponding to the first time information is observed, and the updated first time information is used as the first time information to re-determine the acquisition source corresponding to the wireless channel state information in the second time information.

[0562] 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.

[0563] According to some embodiments, 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 1101 is used to acquire the first beam feature set and the second beam feature set related to the current network standard, specifically for:

[0564] Extract features of a synchronization signal and / or a reference signal of a broadband wireless communication system with downlink beamforming enabled, and obtain a downlink static beam feature set related to the current network standard;

[0565] Feature extraction is performed on a demodulation reference signal of a broadband wireless communication system with downlink dynamic beamforming enabled to obtain a downlink dynamic beam feature set related to the current network standard.

[0566] According to some embodiments, the set acquisition unit 1101 is further configured to:

[0567] Obtain the current resident cell of the communication device;

[0568] In response to the network standard information corresponding to the current resident cell and the downlink beamforming determination order, downlink beamforming support information corresponding to the current network standard of the current resident cell is determined.

[0569] According to some embodiments, the set acquisition unit 1101 is configured to determine the downlink beamforming support information corresponding to the current network standard of the current resident cell in response to the network standard information corresponding to the current resident cell and the downlink beamforming determination order, and is specifically configured to:

[0570] Obtain the network standard information corresponding to the current resident cell;

[0571] In response to the network standard information corresponding to the current camping cell being the first network standard, determining that the communication device is in a radio resource control connection state;

[0572] In response to the dedicated configuration signaling indicating that the communication device is in a preset transmission mode, obtaining first scenario information corresponding to the current resident cell;

[0573] In response to the first scenario information being the preset scenario information, it is determined that the downlink beamforming support information corresponding to the first network standard is that the first network standard supports downlink dynamic beamforming.

[0574] According to some embodiments, the set acquisition unit 1101 is configured to determine the downlink beamforming support information corresponding to the current network standard of the current resident cell in response to the network standard information corresponding to the current resident cell and the downlink beamforming determination order, including:

[0575] Obtain the network standard information corresponding to the current resident cell;

[0576] In response to the network standard information corresponding to the current camping cell being the first network standard, determining that the communication device is in a radio resource control connection state;

[0577] 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, it is determined that the downlink beamforming support information corresponding to the first network standard is that the first network standard does not support downlink dynamic beamforming.

[0578] According to some embodiments, the set acquisition unit 1101 is configured to determine the downlink beamforming support information corresponding to the current network standard of the current resident cell in response to the network standard information corresponding to the current resident cell and the downlink beamforming determination order, including:

[0579] In response to the network standard information corresponding to the current resident cell not being the first network standard, determining that the network standard information corresponding to the current resident cell is the second network standard;

[0580] In response to the frequency range information of the current cell being the first frequency range, the communication mode of the current cell being time division duplex, and the second scene information corresponding to the current cell being the preset scene information, the downlink beamforming support information corresponding to the second network standard is determined to be the second network standard supporting downlink dynamic beamforming.

[0581] According to some embodiments, the set acquisition unit 1101 is configured to determine the downlink beamforming support information corresponding to the current network standard of the current resident cell in response to the network standard information corresponding to the current resident cell and the downlink beamforming determination order, and is specifically configured to:

[0582] In response to the network standard information corresponding to the current resident cell not being the first network standard, determining that the network standard information corresponding to the current resident cell is the second network standard;

[0583] In response to the fact that the frequency range information corresponding to the current cell is not the first frequency range, or the communication mode of the current cell is not time division duplex, or the second scene information corresponding to the current cell is not the preset scene information, it is determined that the downlink beamforming support information corresponding to the second network standard is that the second network standard does not support downlink dynamic beamforming.

[0584] According to some embodiments, the set acquisition unit 1101 is configured to determine the downlink beamforming support information corresponding to the current network standard of the current resident cell in response to the network standard information corresponding to the current resident cell and the downlink beamforming determination order, and is specifically configured to:

[0585] In response to the network standard information corresponding to the current resident cell not being the second network standard, determining whether the network standard information corresponding to the current resident cell is a third network standard;

[0586] In response to determining that the network standard information corresponding to the current resident cell is the third network standard, a determination method corresponding to the third network standard is adopted to determine the downlink beamforming support information corresponding to the current network standard of the current resident cell.

[0587] According to some embodiments, the set acquisition unit 1101 is further configured to:

[0588] In response to a radio resource control signaling reconfiguration occurring in the radio resource control connection state, downlink beamforming support information corresponding to a current network standard of a current resident cell is re-determined.

[0589] Regarding the device in the above embodiment, the specific manner in which each module performs operations has been described in detail in the embodiment of the method, and will not be elaborated here.

[0590] In some or related embodiments, a set acquisition unit is used to acquire a first beam feature set and a second beam feature set related to the current network standard; a source determination unit 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 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, wherein 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 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 meet the preset condition, which can improve the accuracy of determining the acquisition source corresponding to the wireless channel state information, reduce the situation where the wireless channel state information required for channel estimation does not match the acquisition source, resulting in inaccurate determination of the wireless channel state information, improve the accuracy of acquiring the wireless channel state information, improve the receiving state of the communication device, and improve the communication quality of the communication device.

[0591] Fig.12 A schematic block diagram of an example communication device 1200 that can be used to implement an embodiment of the present disclosure is shown. The communication device is intended to represent various forms of digital computers, such as 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 personal digital processing, cellular phones, smart phones, wearable communication devices, and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely examples and are not intended to limit the implementation of the present disclosure described and / or required herein.

[0592] like Fig.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.

[0593] A number of 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 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 through a computer network such as the Internet and / or various telecommunication networks.

[0594] The computing unit 1201 may be a variety of general and / or special 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, digital signal processors (DSPs), and any appropriate processors, controllers, microcontrollers, etc. The computing unit 1201 performs 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 may be implemented as a computer software program, which is tangibly contained in a machine-readable medium, such as a storage unit 1208. In some embodiments, part or all of the computer program may be loaded and / or installed on 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 may be performed. Alternatively, in other embodiments, the computing unit 1201 may be configured to perform the beam sensing method in any other appropriate manner (for example, by means of firmware).

[0595] See also Fig.13 FIG. 1 is a block diagram of a chip according to an exemplary embodiment. Fig.13The chip shown includes a processor 1301 and an interface 1302. Optionally, it may also include a memory 1303. The number of the processor 1301 may be one or more, and the number of the interface 1302 may be multiple.

[0596] Various implementations of the systems and techniques described above herein can be implemented in digital electronic circuit systems, integrated circuit systems, field programmable gate arrays (FPGAs), application specific integrated circuits (ASICs), application specific standard products (ASSPs), systems on chips (SOCs), load programmable logic devices (CPLDs), computer hardware, firmware, software, and / or combinations thereof. These various implementations 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, which can be a special purpose or general purpose programmable processor that can receive data and instructions from a storage system, at least one input device, and at least one output device, and transmit data and instructions to the storage system, the at least one input device, and the at least one output device.

[0597] The program code for implementing the method of the present disclosure may be written in any combination of one or more programming languages. These program codes may be provided to a processor or controller of a general-purpose computer, a special-purpose computer, or other programmable data processing device, so that the program code, when executed by the processor or controller, enables the functions / operations specified in the flow chart and / or block diagram to be implemented. The program code may be executed entirely on the machine, partially on the machine, partially on the machine and partially on a remote machine as a stand-alone software package, or entirely on a remote machine or server.

[0598] In the context of the present disclosure, a machine-readable medium may be a tangible medium that may contain or store a program for use by or in conjunction with an instruction execution system, device, or equipment. A machine-readable medium may be a machine-readable signal medium or a machine-readable storage medium. A machine-readable medium may include, but is not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, device, or equipment, or any suitable combination of the foregoing. A more specific example of a machine-readable storage medium may include an electrical connection based on one or more lines, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.

[0599] To provide interaction with a user, the systems and techniques described herein can be implemented on a computer having: a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to the user; and a keyboard and pointing device (e.g., a mouse or trackball) through which the user can provide input to the computer. Other types 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).

[0600] The systems and techniques described herein can be implemented in a computing system that includes backend components (e.g., as a data server), or a computing system that includes middleware components (e.g., an application server), or a computing system that includes frontend components (e.g., a user computer with a graphical user interface or a web browser through which a user can interact with implementations of the systems and techniques described herein), or a computing system that includes any combination of such backend components, middleware components, or frontend components. The components of the system can be interconnected by any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include: a local area network (LAN), a wide area network (WAN), the Internet, and a blockchain network.

[0601] A computer system may include a client and a server. The client and the server are generally remote 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 corresponding computers and having a client-server relationship with each other. The server may be a cloud server, also known as a cloud computing server or cloud host, which is a host product in the cloud computing service system to solve the defects of difficult management and weak business scalability in traditional physical hosts and VPS services ("Virtual Private Server", or "VPS" for short). The server may also be a server of a distributed system, or a server combined with a blockchain.

[0602] It should be understood that the various forms of processes shown above can be used to reorder, add or delete steps. For example, the steps recorded in this disclosure can be executed in parallel, sequentially or in different orders, as long as the desired results of the technical solutions disclosed in this disclosure can be achieved, and this document does not limit this.

[0603] The above specific implementations do not constitute a limitation on the protection scope of the present disclosure. It should be understood by those skilled in the art that various modifications, combinations, sub-combinations and substitutions can be made according to design requirements and other factors. Any modification, equivalent substitution and improvement made within the spirit and principle of the present disclosure shall be included in the protection scope of the present disclosure.

Claims

1. A beam sensing method, characterized in that: include: Obtain a first beam feature set and a second beam feature set related to the current network standard; 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 acquiring wireless channel state information, wherein 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; 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 sensing neural network model, and obtain a feature recognition result output by the beam sensing neural network model, wherein 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.

2. The method according to claim 1, characterized in that 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 sensing neural network model, and obtaining a feature recognition result output by the beam sensing neural network model, comprises: 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 sensing neural network model, and obtaining a vector corresponding to the at least one first parameter and the at least one second parameter; The vector is identified and processed using the activation function of the preset beam sensing neural network model to obtain the feature recognition result output by the beam sensing neural network model.

3. The method according to claim 1, characterized in that The selecting the first beam feature set or the second beam feature set as a source for acquiring wireless channel state information includes: In response to the feature recognition result corresponding to the first time information satisfying the first result requirement, and the wireless resource control connection of the communication device has not been reconfigured or released, it is determined that the acquisition source corresponding to the wireless channel state information in the second time information is the dynamic beam feature acquisition source, wherein the first time information is any moment of the current period in 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 number of preset results in the feature recognition results corresponding to the first time information meets the quantity requirement.

4. The method according to claim 1, characterized in that: The selecting the first beam feature set or the second beam feature set as a source for acquiring wireless channel state information includes: In response to the feature recognition result corresponding to the first time information satisfying the second result requirement, it is determined that the acquisition source corresponding to the wireless channel state information in the second time information is the static beam feature acquisition source, wherein the first time information is any moment in 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 first number of preset results in the feature recognition results corresponding to the first time information does not meet the quantity requirement.

5. The method according to claim 1, characterized in that The selecting the first beam feature set or the second beam feature set as a source for acquiring wireless channel state information includes: In response to the feature recognition result corresponding to the first time information satisfying the first result requirement and the wireless resource control connection of the communication device has not been reconfigured or released, it is determined that the acquisition source corresponding to the wireless channel state information in the second time information is the dynamic beam feature acquisition source, wherein the first time information is any moment of the current period in 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 number of preset results in the feature recognition results corresponding to the first time information meets the quantity requirement.

6. The method according to claim 1, characterized in that The selecting the first beam feature set or the second beam feature set as a source for acquiring wireless channel state information includes: 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 in the second time information is a static beam feature acquisition source, wherein the first time information is any moment of the current period in 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 a result requirement that the feature recognition results corresponding to the first time information are not all preset results or a result requirement that a second number of 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 obtained, the update information corresponding to the first time information is observed, and the updated first time information is used as the first time information to re-determine the acquisition source corresponding to the wireless channel state information in the second time information.

7. The method according to any one of claims 3 to 6, characterized in that: in, 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.

8. The method according to claim 1, characterized in that in, 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 acquiring of the first beam feature set and the second beam feature set related to the current network standard includes: Extracting features of a synchronization signal and / or a reference signal of a broadband wireless communication system with downlink beamforming enabled, and obtaining a downlink static beam feature set related to the current network standard; Feature extraction is performed on a demodulation reference signal of a broadband wireless communication system with downlink dynamic beamforming enabled to obtain a downlink dynamic beam feature set related to the current network standard.

9. The method according to claim 1, characterized in that: The method further comprises: Obtain the current resident cell of the communication device; In response to the network standard information corresponding to the current resident cell and the downlink beamforming determination order, downlink beamforming support information corresponding to the current network standard of the current resident cell is determined.

10. The method according to claim 9, characterized in that The determining, in response to the network standard information corresponding to the currently resident cell and the downlink beamforming determination order, the downlink beamforming support information corresponding to the current network standard of the currently resident cell includes: Obtaining network standard information corresponding to the currently resident cell; In response to the network standard information corresponding to the current camping cell being the first network standard, determining that the communication device is in a radio resource control connection state; In response to dedicated configuration signaling indicating that the communication device is in a preset transmission mode, acquiring first scenario information corresponding to the current resident cell; In response to the first scenario information being preset scenario information, it is determined that the downlink beamforming support information corresponding to the first network standard is that the first network standard supports downlink dynamic beamforming.

11. The method according to claim 9, characterized in that The determining, in response to the network standard information corresponding to the currently resident cell and the downlink beamforming determination order, the downlink beamforming support information corresponding to the current network standard of the currently resident cell includes: Obtaining network standard information corresponding to the currently resident cell; In response to the network standard information corresponding to the current camping cell being the first network standard, determining that the communication device is in a radio resource control connection state; In response to a dedicated configuration signaling indicating that the communication device is not in a preset transmission mode, or the first scenario information corresponding to the currently resident cell is not the preset scenario information, it is determined that the downlink beamforming support information corresponding to the first network standard is that the first network standard does not support downlink dynamic beamforming.

12. The method according to claim 9, characterized in that The determining, in response to the network standard information corresponding to the currently resident cell and the downlink beamforming determination order, the downlink beamforming support information corresponding to the current network standard of the currently resident cell includes: In response to the network standard information corresponding to the current resident cell not being the first network standard, determining that the network standard information corresponding to the current resident cell is the second network standard; In response to the frequency range information of the current cell being the first frequency range, the communication mode of the current cell being time division duplex, and the second scene information corresponding to the current cell being the preset scene information, it is determined that the downlink beamforming support information corresponding to the second network standard is that the second network standard supports downlink dynamic beamforming.

13. The method according to claim 9, characterized in that The determining, in response to the network standard information corresponding to the currently resident cell and the downlink beamforming determination order, the downlink beamforming support information corresponding to the current network standard of the currently resident cell includes: In response to the network standard information corresponding to the current resident cell not being the first network standard, determining that the network standard information corresponding to the current resident cell is the second network standard; In response to the fact that the frequency range information corresponding to the current cell is not the first frequency range, or the communication mode of the current cell is not time division duplex, or the second scene information corresponding to the current cell is not the preset scene information, it is determined that the downlink beamforming support information corresponding to the second network standard is that the second network standard does not support downlink dynamic beamforming.

14. The method according to claim 9, characterized in that The determining, in response to the network standard information corresponding to the currently resident cell and the downlink beamforming determination order, the downlink beamforming support information corresponding to the current network standard of the currently resident cell includes: In response to the network standard information corresponding to the current resident cell not being the second network standard, determining whether the network standard information corresponding to the current resident cell is a third network standard; In response to determining that the network standard information corresponding to the current resident cell is the third network standard, a determination method corresponding to the third network standard is adopted to determine the downlink beamforming support information corresponding to the current network standard of the current resident cell.

15. The method according to any one of claims 10 to 11, characterized in that The method further comprises: In response to a radio resource control signaling reconfiguration occurring in the radio resource control connection state, downlink beamforming support information corresponding to a current network standard of the current resident cell is re-determined.

16. A beam sensing device, characterized in that: include: A set acquisition unit, used to acquire a first beam feature set and a second beam feature set related to the current network standard; a source determination unit, configured to select 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 satisfying a preset condition, wherein 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 source determination unit is further 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 sensing neural network model, and obtain a feature recognition result output by the beam sensing neural network model, wherein 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.

17. The device according to claim 16, characterized in that The source determination unit is further configured to: 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 sensing neural network model, and obtaining a vector corresponding to the at least one first parameter and the at least one second parameter; The vector is identified and processed using the activation function of the preset beam sensing neural network model to obtain the feature recognition result output by the beam sensing neural network model.

18. A communication device, characterized in that: include: processor; a memory for storing instructions executable by the processor; The processor is configured to execute the instructions to implement the method as claimed in any one of claims 1 to 15.

19. A storage medium, when instructions in the storage medium are executed by a processor of a communication device, the communication device is enabled to execute the method according to any one of claims 1 to 15.

20. A chip, characterized in that: The method comprises a processor and an interface; the processor is used to read instructions to execute the method according to any one of claims 1 to 15.

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