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

Abstract

To provide an invention related to a field of communication technologies, and in particular, to a beam sensing method, an apparatus, a communication device, a storage medium, and a chip.SOLUTION: A beam sensing method includes steps of: obtaining a first beam feature set and a second beam feature set associated with a current network standard; and, in response to at least one first parameter of the first beam feature set and at least one second parameter of the second beam feature set meeting a preset condition, selecting the first beam feature set or the second beam feature set as an acquisition source of radio channel state information, in which the first beam feature set is associated with the at least one first parameter and the second beam feature set is associated with the at least one second parameter. According to the present disclosure, it is possible to improve a transmission / reception state of a communication device and improve communication quality of the communication device.SELECTED DRAWING: Figure 5

Description

[Technical Field]

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

[0002] With the development of communication technology, beamforming, as a key technology for medium and high frequency broadband wireless communication systems, is becoming widely used in cellular mobile communication systems, including New Radio (NR, i.e., 5G). Here, beamforming technology can be used to generate beams by adjusting the parameters of the basic units of a phased array, for example, to generate constructive interference for signals at certain angles and destructive interference for signals at other angles. Summary of the Invention [Problem to be solved by the invention]

[0003] The present disclosure provides a beam sensing method, apparatus, communication device, storage medium and chip to improve the reception status of the communication device and enhance the communication quality of the communication device. [Means for solving the problem]

[0004] According to a first aspect of an embodiment of the present disclosure, a beam sensing method is provided, comprising: acquiring a first beam feature set and a second beam feature set associated with a current network standard; and selecting 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 predetermined condition, wherein the first beam feature set is associated with the at least one first parameter and the second beam feature set is associated with the at least one second parameter.

[0005] According to a second aspect of an embodiment of the present disclosure, a beam sensing device is provided, comprising: a set acquisition unit for acquiring a first beam feature set and a second beam feature set associated with a current network standard; and a source determination unit for selecting 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 predetermined condition, wherein the first beam feature set is associated with the at least one first parameter and the second beam feature set is associated with the at least one second parameter.

[0006] According to a third aspect of an embodiment of the present disclosure, there is provided a communications device, comprising: a processor; and a memory for storing instructions executable by the processor, the processor configured to implement the beam sensing method described in any of the previous aspects by executing the instructions.

[0007] According to a fourth aspect of an embodiment of the present disclosure, there is provided a storage medium, the instructions of which, when executed by a processor of a communications device, enable the communications device to perform the beam sensing method of any of the previous aspects.

[0008] According to a fifth aspect of an embodiment of the present disclosure, there is provided a computer program product including a computer program, which, when executed by a processor, implements the method according to any one of the previous aspects.

[0009] According to a sixth aspect of an embodiment of the present disclosure, there is provided a chip including a processor and an interface, wherein the processor reads instructions to implement the method according to any one of the previous aspects. [Effects of the Invention]

[0010] The technical solutions provided by the embodiments of the present disclosure have at least the following beneficial effects:

[0011] In some related embodiments, a first beam feature set and a second beam feature set associated with a current network standard are acquired, and 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 predetermined condition, the first beam feature set or the second beam feature set is selected as an acquisition source of wireless channel state information, where the first beam feature set is associated with the at least one first parameter and the second beam feature set is associated with the at least one second parameter. This provides a beam sensing mechanism that can determine an acquisition source corresponding to wireless channel state information based on 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 satisfy the predetermined condition, thereby improving the accuracy of determining the acquisition source corresponding to the wireless channel state information, avoiding a situation where the wireless channel state information required for channel estimation does not match the acquisition source, resulting in inaccurate determination of wireless channel state information, improving the accuracy of acquiring wireless channel state information, and improving the reception state of a communication device and the communication quality of the communication device.

[0012] It should be understood that the foregoing general description and the following detailed description are exemplary and explanatory only and are not intended to limit the scope of the present disclosure. [Brief explanation of the drawings]

[0013] The drawings herein, which are incorporated in and made a part of the specification, illustrate embodiments consistent with the present disclosure and, together with the specification, serve to explain the principles of the present disclosure and are not intended to unduly limit the disclosure. [Figure 1] 1 is a flowchart of a beamforming method according to an exemplary embodiment. [Figure 2] FIG. 1 is an exemplary schematic diagram of a beamforming application according to an exemplary embodiment. [Figure 3] FIG. 1 is an exemplary schematic diagram of a beamforming application according to an exemplary embodiment. [Figure 4] 1 is an exemplary schematic diagram of a Time-Frequency Tracking Reference Signal (TRS) static wide beam and a Physical Downlink Control Channel (PDSCH) dynamic narrow beam according to an exemplary embodiment; FIG. [Figure 5] 1 is a flowchart of a beam sensing method according to an exemplary embodiment. [Figure 6] 1 is a flowchart of a beam sensing method according to an exemplary embodiment. [Figure 7] 10 is a flowchart of determining downlink beamforming support information according to an exemplary embodiment. [Figure 8a] FIG. 2 is an exemplary schematic diagram of a neural network model according to an exemplary embodiment. [Figure 8b] FIG. 2 is an exemplary schematic diagram of a neural network model according to an exemplary embodiment. [Figure 8c] FIG. 2 is an exemplary schematic diagram of a neural network model according to an exemplary embodiment. [Figure 8d] FIG. 2 is an exemplary schematic diagram of a single decision tree implementation according to an exemplary embodiment. [Figure 9] 4 is an exemplary schematic diagram of first time information and second time information according to an exemplary embodiment; FIG. [Figure 10] 4 is an exemplary schematic diagram of first time information and second time information according to an exemplary embodiment; FIG. [Figure 11] FIG. 1 is a block diagram of a beam sensing device according to an exemplary embodiment. [Figure 12] FIG. 1 is a block diagram of a communication device according to an exemplary embodiment. [Figure 13] FIG. 1 is a block diagram of a chip according to an exemplary embodiment. DETAILED DESCRIPTION OF THE INVENTION

[0014] In order to make those skilled in the art better understand the technical solution of the present disclosure, the following clearly and completely describes the technical solution in the embodiments of the present disclosure in combination with the drawings.

[0015] Embodiments of the present disclosure provide a beam sensing method, an apparatus, a communication device, a storage medium, and a chip. In some embodiments, the beam sensing method may be interchangeable with terms such as an information processing method and a communication method, the beam sensing apparatus may be interchangeable with terms such as an information processing apparatus and a communication apparatus, and the information processing system and a communication system may be interchangeable.

[0016] The embodiments described in this disclosure are not all embodiments, but are only some illustrative embodiments, and do not specifically limit the scope of protection of the present disclosure. Unless contradictory, each step in any one embodiment can be implemented as an independent embodiment, and each step can be arbitrarily combined, for example, a solution obtained by removing some steps from an embodiment can also be implemented as an independent embodiment, the order of steps in an embodiment can be arbitrarily exchanged, alternative implementation forms in an embodiment can be arbitrarily combined, and each embodiment can be arbitrarily combined, for example, some or all steps in different embodiments can be arbitrarily combined, and an embodiment can be arbitrarily combined with alternative implementation forms of other embodiments.

[0017] In each embodiment of the present disclosure, unless there is a special explanation or logical contradiction, the terms and / or descriptions between each embodiment are consistent and can be referenced, and the technical features in different embodiments can be combined based on their inherent logical relationships to form a new embodiment.

[0018] The terminology used in the embodiments of the present disclosure is for the purpose of describing particular embodiments only and is not intended to be limiting of the disclosure.

[0019] In the embodiments of the present disclosure, unless otherwise specified, elements expressed in the singular, such as "one," "a kind," "the," "the," "the above," "said," "the," "this," etc., can mean "one and only one," "one or more," "at least one," etc. For example, when a translation uses English articles such as "a," "an," or "the," the noun after the article can be understood as either a singular expression or a plural expression.

[0020] In the embodiments of the present disclosure, "plurality" refers to two or more.

[0021] In some embodiments, terms such as "at least one of," "one or more," "a plurality of," and "multiple" are interchangeable.

[0022] In some embodiments, the description methods such as "at least one of A and B," "A and / or B," "A in one case, B in the other case," and "in response to A in one case, in response to B in the other case" may include the following technical solutions depending on the case: In some embodiments, A (executing A regardless of B), in some embodiments, B (executing B regardless of A), in some embodiments, selectively executing A and B (A and B are selectively executed), and in some embodiments, A and B (both A and B are executed). The same applies when there are more options, such as A, B, and C.

[0023] In some embodiments, a description such as "A or B" may include the following technical solutions: in some embodiments, A (A is executed regardless of B), in some embodiments, B (B is executed regardless of A), in some embodiments, A and B are executed selectively (A and B are executed selectively). The same applies when there are more options, such as A, B, and C.

[0024] The prefixes "first," "second," and the like used in the embodiments of the present disclosure are intended merely to distinguish between different described objects and do not limit the position, order, priority, number, or content of the described objects. For statements regarding the described objects, please refer to the context of the claims or embodiments. The use of prefixes should not result in unnecessary limitations. For example, if the described object is a "field," the ordinal number before "field" in "first field" and "second field" does not limit the position or order of the "fields." "first" and "second" do not limit whether the modified "fields" are in the same message, nor do they limit the order of the "first field" and "second field." Furthermore, if the described object is a "level," the ordinal number before "level" in "first level" and "second level" does not limit the priority between the "levels." Furthermore, the number of described objects is not limited by the ordinal number and may be one or more. For example, in the case of a "first device," the number of "devices" may be one or more. Furthermore, objects modified by different prefixes may be the same or different. For example, if the object being described is a "device," a "first device" and a "second device" may be the same or different devices, and their types may be the same or different. Furthermore, if the object being described is "information," the "first information" and the "second information" may be the same or different information, and their contents may be the same or different.

[0025] In some embodiments, terms such as "comprises A," "includes A," "indicates A," "carries A," etc. may be understood as directly carrying A or as indirectly indicating A.

[0026] In some examples, terms such as "responsive to," "responsive to determining," "when," "when," "upon," "if," "perhaps," and the like, can be interchanged.

[0027] In some examples, terms such as "greater than," "greater than or equal," "not less than," "more than," "more than or equal," "not less," "higher," "higher or equal," "not lower," and "greater than or equal to" can be interchanged, and terms such as "smaller," "less than or equal," "not greater than," "less," "less than or equal to," "not more than," "lower," "lower or equal," "not higher," and "less than or equal to" can be interchanged.

[0028] In some embodiments, the apparatuses and devices may be interpreted as physical or virtual entities, and their names are not limited to those described in the embodiments, and in some cases may be understood as "equipment," "device," "circuit," "network element," "node," "function," "unit," "section," "system," "network," "chip," "chip system," "entity," "body," etc.

[0029] In some embodiments, a "network" may be understood as devices included in the network, such as access network devices, core network devices, etc.

[0030] In some embodiments, a "terminal" or "terminal device" may be referred to as a "user equipment (UE)," a "user terminal," a "mobile station (MS)," a "mobile terminal (MT)," a subscriber station, a mobile unit, a subscriber unit, a wireless unit, a remote unit, a mobile device, a wireless device, a wireless communication device, a remote device, a mobile subscriber station, an access terminal, a mobile terminal, a wireless terminal, a remote terminal, a handset, a user agent, a mobile client, a client, or the like.

[0031] In some embodiments, data, information, etc. may be obtained with the user's consent.

[0032] It should be noted that terms such as "first," "second," and the like in the specification, claims, and drawings of this disclosure are used to distinguish between similar subjects and are not necessarily used to describe a particular order or priority. Data used in this manner may be interchanged where appropriate, such that the embodiments of the present disclosure described herein may be practiced in an order other than that illustrated or described herein. The embodiments described in the following illustrative examples do not represent all embodiments consistent with the present disclosure. Rather, they are merely examples of apparatus and methods consistent with certain aspects of the present disclosure, as recited in the appended claims.

[0033] According to some embodiments, FIG. 1 is a flowchart of a beamforming method according to an exemplary embodiment. As shown in FIG. 1, the beamforming technique generates a beam by adjusting the parameters of the basic units of the phased array to generate constructive interference for signals at certain angles and destructive interference for signals at other angles.

[0034] According to some embodiments, FIG. 2 is an exemplary schematic diagram of a beamforming application according to an exemplary embodiment. As shown in FIG. 2, taking the application of new wireless NR 5G downlink direction as an example, in order to ensure quality of service to all user equipment (UE) within a coverage area, the transmission of a base station Node B (gNodeB, gNB) in a synchronization broadcast block (SSB) and a system information block (SIB) is performed in a static beam manner.

[0035] According to some embodiments, Figure 3 is an exemplary schematic diagram of a beamforming application according to an exemplary embodiment. As shown in Figure 3, taking a typical static beam design for NR 5G Frequency Range 1 (abbreviated as FR1, also known as Sub-6G) as an example, full coverage is achieved by a static beam design of not more than eight beams. Here, each of the eight beams in Figure 3 has two polarization directions, and the numbers before and after " / " respectively represent the two polarization direction numbers.

[0036] According to some embodiments, after the communication device completes the SSB / SIB message reception, it immediately starts the random access process to complete the coverage area, and the gNB continues to use the broadcast static beam shown in Figure 3 when sending message 2 (abbreviated as Msg2, used for random access request) and message 4 (abbreviated as Msg4, used for contention resolution).

[0037] To enter a Radio Resource Control (RRC) connected state and achieve optimal dedicated user service quality, the gNB's physical downlink shared channel (PDSCH) is transmitted using a dynamic beam obtained based on sounding reference signal (SRS) estimation and precoding matrix indicator (PMI) reporting. In particular, if the SRS / PMI information is not timely or reliable, the gNB switches to a static beam to ensure basic user service quality. The physical downlink control channel (PDCCH) and channel-state information reference signal (CSI-RS) are also transmitted using dynamic / static beams.

[0038] Furthermore, in the downlink direction, the beam information synchronization mechanism between the gNB and the user equipment (UE) is called beam indication. The beam indication mechanism is completed based on downlink signaling "Transmission Configuration Indication" (TCI). A set of TCI states is configured for the UE through high-level signaling, and each TCI state corresponds to a set of reference signals CSI-RS (Channel State Indication-Reference Signal, i.e., Tracking RS, TRS) or SSB, indicating that the radio channel transmission state of the PDSCH or PDCCH is associated with the corresponding reference signal.

[0039] The corresponding relationship is represented by indicating the Quasi Co-located Information (QCL) type, which includes: -typeA: {Doppler shift, Doppler spread, average delay, delay spread} -typeB: {Doppler shift, Doppler spread} -typeC: {Doppler shift, average delay} -typeD: {Spatial Rx parameter}

[0040] Taking type A, which is the most common type in current network deployments, as an example, the TCI status indication indicates 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. Using the reference signal indicated by the associated TCI, the UE can acquire the radio channel status required for radio channel estimation (CE) for PDSCH / PDCCH reception.

[0041] According to some embodiments, the TRS, as a long-period static beam, cannot perfectly match the beam actually used by the physical downlink shared channel (PDSCH) in the time domain. Furthermore, the TRS cannot perfectly match the parallel data system (PDS) beam in the frequency domain because it cannot perform precoding resource block group (PRG) or subband granularity beamforming according to the protocol. To cover PDS beam changes as much as possible, the gNB typically configures a wider, more robust static beam for the TRS to use. As shown in Figure 4, the beam used by the gNB to transmit the TRS is a static wide beam that does not change within a certain time period. The PDSCH signal beam is typically the narrowest beam achievable by the gNB in ​​the spatial domain and changes in the time domain depending on scheduling information (such as Rank, SU / MU-MIMO), UE transmission, or feedback status.

[0042] In FIG. 4, at time slot 1, the gNB configures the service channel PDSCH to single-user multiple-input multiple-output mode (abbreviated as SU-MIMO), with three service flows, each of which is configured with its currently optimal dedicated dynamic beam. At time slot 2, the gNB configures the channel PDSCH to multi-user multiple-input multiple-output mode (abbreviated as MU-MIMO), with two service flows, each of which is configured with its currently optimal dedicated dynamic beam. However, at times slots 1 and 2, the TRS corresponding to the TCI QCL 'type A' state remains unchanged. Here, for example, the non-ideal effect caused by the static wide beam guiding the reception of the dynamic narrow beam can be referred to as the "wide and narrow beam effect." The "wide and narrow beam" effect can refer to, for example, the impact that the beamwidths of the transmitting antenna and receiving antenna in wireless communication have on signal transmission. The "wide and narrow beam" effect includes, for example, a situation where a static wide beam guiding a dynamic narrow beam to receive a signal causes the wireless channel state information to not meet requirements.

[0043] According to some embodiments, the QCL 'type A' carried by the TCI status indication notifies that a static wide beam for the reference signal (TRS and / or SSB) can provide available radio channel state information (CSI) to the PDSCH CE, and the CSI message is, for example, Doppler shift, Doppler spread, average delay, delay spread, etc., but in reality, due to the "wide and narrow beam" effect, the radio channel state information is inaccurate and includes the following: Average delay spread - Static wide beams and dynamic narrow beams undergo different scattering and diffraction paths, and static wide beams usually have larger delay spreads. Maximum delay extension - Static wide beams and dynamic narrow beams undergo different scattering and diffraction paths, and static wide beams usually have a larger maximum delay extension. Doppler shift - Static wide beams and dynamic narrow beams undergo different scattering and diffraction paths, resulting in different Doppler shifts. Doppler broadening - Static wide beams and dynamic narrow beams undergo different scattering and diffraction paths, resulting in different Doppler broadening.

[0044] According to some embodiments, the 5G PDSCH / PDCCH service channel reception can, for example, strictly follow the QCL reference signal indicated by the TCI state by default to acquire radio channel state information (Doppler shift, Doppler spread, average delay, delay spread). In view of the "wide and narrow beam" effect, the radio channel state information acquired 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 base station coverage, the more pronounced the "wide and narrow beam" effect becomes, and the lower the accuracy of the radio channel state information acquired by the corresponding static wide beam becomes compared to the dynamic narrow beam.

[0045] In some embodiments, the 4th generation mobile communication technology (4G) PDSCH TM7 / 8 / 9 service channel reception may, for example, by default use a cell-specific reference signal (CRS) to acquire radio channel state information (Doppler shift, Doppler spread, average delay, delay spread). Due to the "wide and narrow beam" effect, the radio channel state information acquired by the corresponding static wide beam may not accurately match the actual performance of a dynamic narrow beam. Generally, the farther the UE is in the base station coverage, the more pronounced the "wide and narrow beam" effect becomes, and the less accurate the radio channel state information acquired by the corresponding static wide beam becomes compared to a dynamic narrow beam.

[0046] FIG. 5 is a flowchart of a beam sensing method according to an exemplary embodiment. As shown in FIG. 5, the beam sensing method can be used in broadband wireless communication systems that support beamforming, such as Long Term Evolution (LTE) systems, NR systems, and 6th Generation (6G) systems, and includes the following steps S11 to S12.

[0047] In step S11, a first beam feature set and a second beam feature set associated with the current network standard are obtained.

[0048] According to some embodiments, the network standard may, for example, indicate the communication standard and protocol between different mobile communication networks. The current network standard in the embodiments of the present disclosure may, for example, be one of the network standards supported by a communication device, rather than the currently used network standard in the narrow sense. The current network standard does not refer to a specific, fixed network standard. For example, if the specific network standard corresponding to the current network standard changes, the current network standard may change accordingly. For example, if the execution time of the beam sensing method changes, the current network standard may change accordingly.

[0049] In some embodiments, the network standard may be a 2-Generation wireless telephone technology (2G) network standard represented by global system for mobile communication (GSM), a 3rd-Generation (3G) network standard represented by wideband code division multiple access (WCDMA), the 4th generation mobile communication technology (4G) network standard represented by long term evolution (LTE), a 5G network standard represented by new radio (NR), or the like.

[0050] 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, and embodiments of the present disclosure do not limit the number of first beam feature sets. The name of the first beam feature set is not limited, and the first beam feature set may be referred to, for example, as at least one first beam feature. Here, the downlink static beam feature set may include, for example, at least one downlink static beam feature. The downlink static beam feature set does not refer to a specific fixed set. For example, if the number of features included in the first beam feature set changes, the first beam feature set may change accordingly. For example, if any one beam feature in the first beam feature set changes, the first beam feature set may change accordingly.

[0051] 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, and embodiments of the present disclosure do not limit the number of second beam feature sets. The name of the second beam feature set is not limited, and may be referred to, for example, as at least one second beam feature. Here, 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 refer to a specific fixed set. For example, if the number of features included in the second beam feature set changes, the second beam feature set may change accordingly. For example, if any one beam feature in the second beam feature set changes, the second beam feature set may change accordingly.

[0052] According to some embodiments, if a current network standard determines that downlink dynamic beamforming is supported, a first beam feature set and a second beam feature set associated with the current network standard may be acquired. Here, the order of acquiring the first beam feature set and the second beam feature set is not limited. For example, the first beam feature set may be acquired first, and then the second beam feature set may be acquired; for example, the second beam feature set may be acquired first, and then the first beam feature set; or for example, the first beam feature set and the second beam feature set may be acquired simultaneously.

[0053] According to some embodiments, if it is determined that a current network standard supports downlink dynamic beamforming, a downlink static beam feature set and a downlink dynamic beam feature set associated with the current network standard may be acquired. Here, the order of acquiring the downlink static beam feature set and the downlink dynamic beam feature set is not limited. For example, the downlink static beam feature set and the downlink dynamic beam feature set may be acquired simultaneously, or the downlink static beam feature set and the downlink dynamic beam feature set may be acquired separately. For example, the downlink static beam feature set may be acquired first, and then the downlink dynamic beam feature set may be acquired. Here, since the downlink static beam feature set and the downlink dynamic beam feature set each include at least one beam feature, one downlink static beam feature may be acquired first, and then one downlink dynamic beam feature may be acquired, for example, the two sets may be acquired alternately or not. The embodiments of the present disclosure do not limit the specific process of acquiring the downlink static beam feature set and the downlink dynamic beam feature set corresponding to the current network standard.

[0054] 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 predetermined 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 associated with at least one first parameter and the second beam feature set is associated with at least one second parameter.

[0055] In some embodiments, the preset condition may be, for example, a condition for determining an acquisition source corresponding to radio channel state information, where different preset conditions may correspond, for example, to different acquisition sources. The preset condition does not refer to a specific fixed condition. For example, when a condition modification command for a preset condition is received, the preset condition may change accordingly. For example, when any parameter of the preset condition changes, the preset condition may change accordingly. The preset condition may include, for example, whether the RRC connection of the terminal is re-established or released, whether the feature recognition result is the same as the preset result, or whether the ratio between the feature recognition result and the preset result is greater than a ratio threshold.

[0056] In some embodiments, radio channel state information (CSI) may be used to describe, for example, channel attributes of a communication link, where if the acquisition time of the radio channel state information changes, the radio channel state information may change correspondingly.

[0057] In some embodiments, the acquisition source is used to indicate an acquisition source of the wireless channel state information, including but not limited to a dynamic beam characteristic acquisition source and a static beam characteristic acquisition source.

[0058] In some embodiments or related embodiments, a first beam feature set and a second beam feature set associated with a current network standard are acquired, and 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 predetermined condition, the first beam feature set or the second beam feature set is selected as an acquisition source of wireless channel state information, where the first beam feature set is associated with the at least one first parameter and the second beam feature set is associated with the at least one second parameter. This provides a beam sensing mechanism that can determine an acquisition source corresponding to the wireless channel state information based on 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 satisfy the predetermined condition, thereby improving accuracy in determining the acquisition source corresponding to the wireless channel state information, avoiding a situation in which 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, improving the accuracy of acquiring the wireless channel state information, and improving the reception state of the communication device and the communication quality of the communication device.

[0059] FIG. 6 is a flowchart of a beam sensing method according to an exemplary embodiment. As shown in FIG. 6, the beam sensing method is applicable to a wireless communication scenario and includes the following steps S21 to S26.

[0060] In step S21, the cell in which the communication device is currently located is acquired.

[0061] According to some embodiments, for example, a cell currently serving a communication device can be acquired. For example, it can be acquired that the cell currently serving a communication device is, for example, cell A. The communication device may be called, for example, a terminal, and the embodiments of the present disclosure do not limit the name of the communication device.

[0062] In step S22, downlink beamforming support information corresponding to the current network standard of the currently serving cell is determined in response to the network standard information corresponding to the currently serving cell and the downlink beamforming determination order.

[0063] According to some embodiments, the network standard information indicates a type of network standard, and the network standard information corresponding to the currently served cell may be, for example, a 4G network standard.

[0064] In some embodiments, the downlink beamforming decision order may be, for example, a predetermined downlink beamforming support information decision process, for example, the communications device modifies the downlink beamforming decision order based on the received order adjustment command.

[0065] According to some embodiments, the downlink beamforming support information may be used to indicate, for example, whether downlink dynamic beamforming is supported or not.

[0066] According to some embodiments, FIG. 7 is a flowchart determined by downlink beamforming support information according to an exemplary embodiment. As shown in FIG. 7, the method includes:

[0067] According to some embodiments, the step of determining downlink beamforming support information corresponding to the current network standard of the currently serving cell in response to the network standard information corresponding to the currently serving cell and the downlink beamforming decision order includes the steps of: acquiring the network standard information corresponding to the currently serving cell; determining that the communication device is in a radio resource control connected state (RRC_CONNECTED) in response to the network standard information corresponding to the currently serving cell being a first network standard; acquiring first scenario information corresponding to the currently serving cell in response to the dedicated configuration signaling indicating that the communication device is in a preset transmission mode; and determining that the downlink beamforming support information corresponding to the first network standard is that the first network standard supports downlink dynamic beamforming in response to the first scenario information being preset scenario information.

[0068] According to some embodiments, the step of determining downlink beamforming support information corresponding to the current network standard of the currently serving cell in response to the network standard information corresponding to the currently serving cell and the downlink beamforming determination order includes: acquiring the network standard information corresponding to the currently serving cell; determining that the communication device is in a radio resource control connected state in response to the network standard information corresponding to the currently serving cell being a first network standard; and determining that the downlink beamforming support information corresponding to the first network standard indicates that the first network standard does not support downlink dynamic beamforming in response to the dedicated configuration signaling indicating that the communication device is not in a preset transmission mode or the first scenario information being not preset scenario information. Therefore, for the first network standard, the downlink beamforming support information can be determined based on the dedicated configuration signaling and the first scenario information, which can improve the accuracy of the downlink beamforming support information determination and the accuracy of the acquisition source determination.

[0069] In some embodiments, the first network standard may be, for example, a 4G network standard.

[0070] According to some embodiments, the preset transmission mode may be, for example, at least one of TM7, TM8, and TM9. For example, if the dedicated configuration signaling indicates that the communication device is in TM7, the first scenario information corresponding to the currently serving cell may be obtained.

[0071] In some embodiments, the first scenario information may be used to indicate, for example, scenario information corresponding to a currently serving cell. The first scenario information does not refer to specific fixed information. For example, the first scenario information may be obtained using a scenario recognition method. However, the embodiments of the present disclosure are not limited thereto.

[0072] 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 currently serving cell is a 4G network standard, it is determined that the communication device is in a radio resource control connected state (RRC_CONNECTED), and the dedicated configuration signaling indicates that the communication device is in TM7. When the acquired first scenario information corresponding to the currently serving cell is a high-speed rail scenario, it is determined that the downlink beamforming support information corresponding to the 4G network standard indicates that downlink dynamic beamforming is supported.

[0073] If the network standard information corresponding to the currently serving cell is a 4G network standard, it is determined that the communication device is in a radio resource control connected state (RRC_CONNECTED), and if the dedicated configuration signaling indicates that the communication device is not in a pre-configured transmission mode, it is determined that the downlink beamforming support information corresponding to the 4G network standard does not support downlink dynamic beamforming.

[0074] If the network standard information corresponding to the currently serving cell is a 4G network standard, determine that the communication device is in a radio resource control connected state (RRC_CONNECTED), and if the dedicated configuration signaling indicates that the communication device is in a preset transmission mode, if the acquired first scenario information corresponding to the currently serving cell is not preset scenario information, determine that the downlink beamforming support information corresponding to the 4G network standard does not support downlink dynamic beamforming.

[0075] According to some embodiments, the method further includes, in response to a radio resource control signaling reconfiguration occurring in the radio resource control connected state, redetermining downlink beamforming support information corresponding to a current network standard of the currently serving cell. Here, redetermining downlink beamforming support information corresponding to a current network standard of the currently serving cell is applicable when the current network standard is a first network standard or a second network standard. The embodiments of the present disclosure are not limited thereto. Therefore, when a radio resource control signaling reconfiguration occurs, redetermining downlink beamforming support information can improve the accuracy of determining the downlink beamforming support information and the accuracy of determining the acquisition source.

[0076] According to some embodiments, when an RRC signaling reconfiguration occurs in a radio resource control connected state, the communication device determines whether it is in a radio resource control connected state, and if it determines that the communication device is in a radio resource control connected state, it can re-determine downlink beamforming support information corresponding to the current network standard of the currently serving cell based on the dedicated configuration signaling and the first scenario information.

[0077] According to some embodiments, the step of determining downlink beamforming support information corresponding to the current network standard of the currently serving cell in response to the network standard information corresponding to the currently serving cell and the downlink beamforming decision order includes: determining that the network standard information corresponding to the currently serving cell is a second network standard in response to the network standard information corresponding to the currently serving cell not being a first network standard; and determining that the downlink beamforming support information corresponding to the second network standard means that the second network standard supports downlink dynamic beamforming in response to the frequency range information of the currently serving cell being the first frequency range, the communication mode of the currently serving cell being time division duplex, and the second scenario information corresponding to the currently serving cell being preset scenario information.

[0078] Illustratively, in one embodiment of the present disclosure, the step of determining downlink beamforming support information corresponding to the current network standard of the currently serving cell in response to the network standard information corresponding to the currently serving cell and the downlink beamforming decision order includes: determining, if the network standard information corresponding to the currently serving cell is not a first network standard, that the network standard information corresponding to the currently serving cell is a second network standard; acquiring frequency range information corresponding to the currently serving cell; acquiring the communication method of the currently serving cell in response to the frequency range information being a first frequency range (Frequency range 1, FR1); acquiring second scenario information corresponding to the currently serving cell in response to the communication method being time division duplex; and determining, from the downlink beamforming support information corresponding to the second network standard, that the second network standard supports downlink dynamic beamforming in response to the second scenario information being preset scenario information.

[0079] According to some embodiments, determining downlink beamforming support information corresponding to the current network standard of the currently serving cell in response to the network standard information corresponding to the currently serving cell and the downlink beamforming determination order includes: determining that the network standard information corresponding to the currently serving cell is a second network standard in response to the network standard information corresponding to the currently serving cell not being a first network standard; and determining that the downlink beamforming support information corresponding to the second network standard indicates that the second network standard does not support downlink dynamic beamforming in response to the frequency range information corresponding to the currently serving cell not being the first frequency range, or the communication mode of the currently serving cell not being time division duplex, or the second scenario information corresponding to the currently serving cell not being preset scenario information. Therefore, for 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 for different network standards, thereby improving the accuracy of determining the downlink beamforming support information and improving the accuracy of determining the acquisition source.

[0080] According to some embodiments, the second network standard may be, for example, a 5G network standard.

[0081] According to some embodiments, the frequency range information may be used to indicate, for example, the frequency range of the currently served cell. The frequency range information may include, for example, a first frequency range, i.e., frequency range 1, frequency range 2, etc.

[0082] According to some embodiments, communication schemes may include, for example, time division duplex and frequency division duplex.

[0083] In some embodiments, the method includes determining that the network standard information corresponding to the currently serving cell is a 5G network standard, and acquiring frequency range information corresponding to the currently serving cell. In response to the frequency range information being a first frequency range, acquiring a communication mode of the currently serving cell. In response to the communication mode being time division duplex, acquiring second scenario information corresponding to the currently serving cell. In response to the second scenario information being a subway scenario, determining that the downlink beamforming support information corresponding to the 5G network standard indicates that the 5G network standard supports downlink dynamic beamforming.

[0084] According to some embodiments, in response to a radio resource control signaling reconfiguration occurring in a radio resource control connected state, downlink beamforming support information corresponding to a second network standard of the currently serving cell is redetermined.

[0085] In some embodiments, determining downlink beamforming support information corresponding to the current network standard of the currently serving cell in response to the network standard information corresponding to the currently serving cell and the downlink beamforming decision order includes: determining whether the network standard information corresponding to the currently serving cell is a third network standard in response to the network standard information corresponding to the currently serving cell not being a second network standard, and determining the downlink beamforming support information corresponding to the current network standard of the currently serving cell using a decision method corresponding to the third network standard in response to determining that the network standard information corresponding to the currently serving cell is the third network standard, where the third network standard may be, for example, a 6G network standard or above.

[0086] According to some embodiments, in response to a radio resource control signaling reconfiguration occurring in a radio resource control connected state, downlink beamforming support information corresponding to a third network standard of the currently serving cell is redetermined.

[0087] In some embodiments, for example, if it is determined that the network standard information corresponding to the currently serving cell is not a second network standard, it is determined whether the network standard information corresponding to the currently serving cell is a third network standard, and if it is determined that the network standard information corresponding to the currently serving cell is a third network standard, it is possible to determine whether the third network standard supports downlink dynamic beamforming using a determination method corresponding to the third network standard.

[0088] According to some embodiments, determine that the network standard information corresponding to the currently serving cell is a 5G network standard, obtain frequency range information corresponding to the currently serving cell, and if the frequency range information is not a first frequency range, determine that the downlink beamforming support information corresponding to the 5G network standard is that the 5G network standard does not support downlink dynamic beamforming.

[0089] In some embodiments, determine that the network standard information corresponding to the currently serving cell is a 5G network standard, and obtain frequency range information corresponding to the currently serving cell. If the frequency range information is a first frequency range, obtain the communication mode of the currently serving cell. If the communication mode is not time division duplex, determine that the downlink beamforming support information corresponding to the 5G network standard indicates that the 5G network standard does not support downlink dynamic beamforming.

[0090] In some embodiments, when it is determined that the network standard information corresponding to the currently serving cell is a 5G network standard, frequency range information corresponding to the currently serving cell is obtained. When the frequency range information is a first frequency range, the communication mode of the currently serving cell is obtained. When the communication mode is time division duplex, second scenario information corresponding to the currently serving cell is obtained. When the second scenario information is a subway scenario or a high-speed rail scenario, 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.

[0091] In some embodiments, the network standard information corresponding to the currently serving cell is determined to be a 5G network standard, and frequency range information corresponding to the currently serving cell is obtained. If the frequency range information is a first frequency range, the communication mode of the currently serving cell is obtained. If the communication mode is time division duplex, second scenario information corresponding to the currently serving cell is obtained. If the second scenario information is not a subway scenario or a high-speed rail scenario, the downlink beamforming support information corresponding to the 5G network standard is determined to be that the 5G network standard supports downlink dynamic beamforming.

[0092] In some embodiments, for example, when the network standard information corresponding to the currently serving cell is not a 5G network standard, it is determined whether the network standard information corresponding to the currently serving cell is a 6G network standard. For example, when the network standard information corresponding to the currently serving cell is a 6G network standard, a determination method corresponding to the 6G network standard can be used to determine downlink beamforming support information corresponding to the 6G network standard.

[0093] 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 associated with the current network standard are obtained.

[0094] The specific process is as described above, and a detailed description is omitted here.

[0095] 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, and the step of obtaining the first beam feature set and the second beam feature set associated with the current network standard includes the steps of: performing feature extraction on synchronization signals and / or reference signals of the broadband wireless communication system with downlink beamforming enabled to obtain a downlink static beam feature set associated with the current network standard; and performing feature extraction on demodulation reference signals of the broadband wireless communication system with downlink dynamic beamforming enabled to obtain a downlink dynamic beam feature set associated with the current network standard.

[0096] Here, the synchronization signal and / or reference signal includes at least one of a Primary Synchronization Signal (PSS) in the first network standard, a Secondary Synchronization Signal (SSS) in the first network standard, a Cell-Specific Reference Signal (CRS) in the first network standard, an SSB in the second network standard, and a TRS in the second network standard.

[0097] Here, the downlink static beam feature set includes, but is not limited to, a Signal to Interference plus Noise Ratio (SINR), a maximum delay spread (Tmax), a root mean square delay spread (Trms), and a maximum Doppler (Doppler), specifically, a Primary Synchronization Signal-Signal to Interference plus Noise Ratio (PSS-SINR), a Secondary Synchronization Signal-Signal to Interference plus Noise Ratio (SSS-SINR), a Cell-Specific Reference Signal-Signal to Interference plus Noise Ratio (CRS-SINR), a Cell-Specific Reference Signal-maximum delay spread (CRS-Tmax), a Cell-Specific Reference Signal-rms delay spread (Cell-Specific Reference Signal-rms delay spread, CRS-Trms), Cell-Specific Reference Signal-Doppler (CRS-Doppler), SSS-SINR corresponding to the second network standard, Tracking Reference Signal Channel-state information-Signal to Interference plus Noise Ratio (TRS CSI-SINR), Tracking Reference Signal Channel-maximum delay spread (TRS-Tmax), Time-Frequency Tracking Reference Signal-Root Mean Square Delay Extension (TRSThe time-frequency tracking reference signal may include a time-frequency tracking reference signal channel-rms delay spread (TRS-Trms), and a time-frequency tracking reference signal channel-Doppler (TRS-Doppler).

[0098] Here, 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.

[0099] Here, the demodulation reference signal includes at least one of a PDSCH Demodulation Reference Signal (DMRS) in the first network standard or the second network standard, and a PDCCH DMRS in the second network standard.

[0100] Here, the downlink dynamic beam feature set includes, but is not limited to, a signal to interference plus noise ratio (SINR), a maximum delay spread (Tmax), a root mean square delay spread (Trms), and a maximum Doppler (Doppler), specifically, a physical downlink shared channel-signal to interference plus noise ratio (PDCCH-SINR), a physical downlink shared channel-maximum delay spread (PDCCH-Tmax), a physical downlink shared channel-rms delay spread (PDCCH-Trms), a physical downlink shared channel-Doppler (PDCCH-Doppler), and a physical downlink control channel-signal to interference plus noise ratio (PDCCH-Doppler), which correspond to the first network standard or the second network standard. channel-Signal to Interference plus Noise Ratio (PDCCH-SINR), Physical downlink control channel-maximum delay spread (PDCCH-Tmax), Physical downlink control channel-rms delay spread (PDCCH-Trms), and Physical downlink control channel-Doppler (PDCCH-Doppler).

[0101] Here, 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.

[0102] In step 24, a feature recognition result is obtained in response to the 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, wherein the feature recognition result indicates 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 satisfy a predetermined condition.

[0103] The specific process is as described above, and a detailed description is omitted here.

[0104] Here, when obtaining an operation result between at least one first parameter of a first beam feature set and at least one second parameter of a second beam feature set, the first parameter and the second parameter may be, for example, parameters of the same beam feature, and the beam feature may include, but is not limited to, a signal to interference plus noise ratio (SINR), a maximum delay spread (Tmax), a root mean square delay spread (Trms), a maximum Doppler (Doppler), etc.

[0105] According to some embodiments, the step of obtaining a feature recognition result in response to the 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 the step of comparing the difference result and / or ratio result between the at least one first parameter of the first beam feature set and at least one second parameter of the second beam feature set with at least one threshold information to obtain the feature recognition result.

[0106] Here, the feature recognition result may be, for example, a wide and narrow beam effect recognition result, where the wide and narrow beam effect recognition result may correspond to, for example, a network standard, where, for example, different network standards may determine the wide and narrow beam effect recognition result based on different recognition methods.

[0107] Here, the setting of each threshold in the at least one threshold information may be set based on, for example, experience or modulation effect, or may be set based on the accuracy of wide and narrow beam effect recognition results, although the embodiment of the present disclosure is not limited thereto.

[0108] In addition, when there are a plurality of beam features corresponding to the at least one first parameter, the at least one first parameter may include, for example, at least one parameter of each beam feature among the plurality of beam features. In addition, when there are a plurality of beam features corresponding to the at least one second parameter, the at least one second parameter may include, for example, at least one parameter of each beam feature among the plurality of beam features.

[0109] According to some embodiments, the step of 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 a step of obtaining a feature recognition result in response to a calculation result between any one first parameter in the first beam feature set and any one second parameter in the second beam feature set and at least one threshold information, wherein the any one first parameter and the any one second parameter correspond to the same beam feature.

[0110] In some embodiments, the beam characteristic is a signal-to-interference-plus-noise ratio (SINR), wherein the at least one first parameter comprises at least one of a cell-specific reference signal-to-signal-to-interference-plus-noise ratio (CRS-SINR), a primary synchronization signal-to-signal-to-interference-plus-noise ratio (PSS-SINR), and a secondary synchronization signal-to-signal-to-interference-plus-noise ratio (SSS-SINR), and the at least one second parameter comprises a physical downlink shared channel-to-signal-to-interference-plus-noise ratio (PDSCH-SINR); Or, where the at least one first parameter includes at least one of a time-frequency tracking reference signal channel state information—signal-to-interference-plus-noise ratio (TRS CSI-SINR) and a synchronization signal—signal-to-interference-plus-noise ratio (SS-SINR), and the at least one second parameter includes at least one of a physical downlink shared channel—signal-to-interference-plus-noise ratio (PDSCH-SINR) and a physical downlink control channel—signal-to-interference-plus-noise ratio (PDCCH-SINR).

[0111] In some embodiments, the beam characteristic is a maximum delay extension (Tmax), wherein the at least one first parameter comprises a cell-specific reference signal—maximum delay extension (CRS-Tmax) and the at least one second parameter comprises a physical downlink shared channel—maximum delay extension (PDSCH-Tmax), or wherein the at least one first parameter comprises a time-frequency tracking reference signal—maximum delay extension (TRS-Tmax) and the at least one second parameter comprises at least one of a physical downlink shared channel—maximum delay extension (PDSCH-Tmax) and a physical downlink control channel—maximum delay extension (PDCCH-Tmax).

[0112] In some embodiments, the beam feature is a root-mean-square delay extension (Trms), wherein the at least one first parameter comprises a cell-specific reference signal-root-mean-square delay extension (CRS-Trms) and the at least one second parameter comprises a physical downlink shared channel-root-mean-square delay extension (PDSCH-Trms), or the at least one first parameter comprises a time-frequency tracking reference signal-root-mean-square delay extension (TRS-Trms) and the at least one second parameter comprises at least one of a physical downlink shared channel-root-mean-square delay extension (PDSCH-Trms) and a physical downlink control channel-root-mean-square delay extension (PDCCH-Trms).

[0113] In some embodiments, the beam characteristic is maximum Doppler (Doppler), wherein the at least one first parameter comprises at least one of CRS-SINR, PSS-SINR, SSS-SINR, and Cell-Specific Reference Signal—Maximum Doppler (CRS-Doppler), and the at least one second parameter comprises at least one of PDSCH-SINR, Physical Downlink Shared Channel—Maximum Doppler (PDSCH-Doppler), or the at least one first parameter comprises at least one of TRS CSI-SINR, SS-SINR, Time-Frequency Tracking Reference Signal—Maximum Doppler (TRS-Doppler), and the at least one second parameter comprises at least one of PDSCH-SINR, PDCCH-SINR, Physical Downlink Control Channel—Maximum Doppler (PDCCH-Doppler), and Physical Downlink Shared Channel—Maximum Doppler (PDSCH-Doppler).

[0114] According to some embodiments, the step of 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 a step of obtaining a feature recognition result in response to a calculation result between two first parameters of the first beam feature set and two second parameters of the second beam feature set and at least one threshold information, wherein the two first parameters and the two second parameters correspond to two different types of beam features, and the calculation results are two results obtained by performing calculation processing on any one first parameter and any one second parameter of the same beam feature.

[0115] In some embodiments, the at least one first parameter includes at least one of CRS-Tmax and cell-specific reference signal-maximum Doppler (CRS-Doppler), and the at least one second parameter includes at least one of PDSCH-Doppler and PDCCH-Tmax, or the at least one first parameter includes at least one of TRS-Tmax and TRS-Doppler, and the at least one second parameter includes at least one of PDSCH-Tmax, PDCCH-Tmax, PDSCH-Doppler, and PDCCH-Doppler.

[0116] In some embodiments, the at least one first parameter includes at least one of CRS-Trms and CRS-Dopple, and the at least one second parameter includes at least one of PDSCH-Trms and PDSCH-Doppler, or the at least one first parameter includes at least one of TRS-Trms and TRS-Doppler, and the at least one second parameter includes at least one of PDSCH-Trms, PDCCH-Trms, PDSCH-Doppler, and PDCCH-Doppler.

[0117] In some embodiments, the at least one first parameter includes at least one of CRS-SINR, PSS-SINR, SSS-SINR, and CRS-Tmax, and the at least one second parameter includes at least one of PDSCH-SINR and PDSCH-Tmax, or the at least one first parameter includes at least one of TRS CSI-SINR, SS-SINR, and TRS-Tmax, and the at least one second parameter includes at least one of PDSCH-SINR, PDCCH-SINR, PDSCH-Tmax, and PDCCH-Tmax.

[0118] In some embodiments, the at least one first parameter includes at least one of CRS-SINR, PSS-SINR, SSS-SINR, and CRS-Trms, and the at least one second parameter includes at least one of PDSCH-SINR and PDSCH-Tmax, or the at least one first parameter includes at least one of TRS CSI-SINR, SS-SINR, and TRS-Trms, and the at least one second parameter includes at least one of PDSCH-SINR, PDCCH-SINR, PDSCH-Trms, and PDCCH-Trms.

[0119] According to some embodiments, the step of 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 a step of obtaining a feature recognition result in response to a calculation result between three first parameters of the first beam feature set and three second parameters of the second beam feature set and at least one threshold information, wherein the three first parameters and the three second parameters correspond to three different types of beam features, and the calculation results are three results obtained by performing calculation processing on any one first parameter and any one second parameter of the same beam feature.

[0120] In some embodiments, the at least one first parameter includes at least one of CRS-SINR, PSS-SINR, SSS-SINR, CRS-Tmax, and CRS-Trms, and the at least one second parameter includes at least one of PDSCH-SINR, PDSCH-Tmax, and PDSCH-Trms, or the at least one first parameter includes at least one of TRS CSI-SINR, SS-SINR, TRS-Tmax, and TRS-Trms, and the at least one second parameter includes at least one of PDSCH-SINR, PDCCH-SINR, PDSCH-Tmax, PDCCH-Tmax, PDSCH-Trms, and PDCCH-Trms.

[0121] According to some embodiments, when determining a feature recognition result in response to the 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, a threshold design rule belonging to decision design may be used, which can balance the correct judgment rate and the false alarm rate, improve the accuracy of obtaining the feature recognition result, and improve the accuracy of determining the acquisition source.

[0122] According to some embodiments, obtaining a feature recognition result in response to the result of the operation between at least one first parameter of the first beam feature set and at least one second parameter of the second beam feature set and at least one threshold information includes determining that the feature recognition result is a predetermined result in response to a first difference value between any one second parameter and any one first parameter being greater than a first threshold, the first threshold representing a relative SINR index threshold, and the predetermined result indicating that 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 satisfy a predetermined condition. Any one second parameter and any one first parameter can, for example, correspond to the same beam feature.

[0123] According to some embodiments, the at least one first parameter comprises at least one of a cell-specific reference signal-to-interference-plus-noise ratio (CRS-SINR), a primary synchronization signal-to-interference-plus-noise ratio (PSS-SINR) and a secondary synchronization signal-to-interference-plus-noise ratio (SSS-SINR), and the at least one second parameter comprises a physical downlink shared channel-to-interference-plus-noise ratio (PDSCH-SINR), or the at least one first parameter comprises at least one of a time-frequency tracking reference signal channel state information-to-signal-to-interference-plus-noise ratio (TRS CSI-SINR) and a synchronization signal-to-signal-to-interference-plus-noise ratio (SS-SINR), and the at least one second parameter comprises at least one of a physical downlink shared channel-to-interference-plus-noise ratio (PDSCH-SINR) and a physical downlink control channel-to-interference-plus-noise ratio (PDCCH-SINR).

[0124] For example, in one embodiment of the present disclosure, if the current network standard is a 4G network standard, when a difference value between the PDSCH-SINR and the CRS-SINR (or the PSS-SINR or the SSS-SINR) is greater than a first threshold, it may be determined that the feature recognition result is a preset result, for example, indicating that a wide-and-narrow beam effect has occurred. When the difference value between the PDSCH-SINR and the CRS-SINR (or the PSS-SINR or the SSS-SINR) is equal to or less than the first threshold, it may be determined that the feature recognition result is not a preset result. For example, when a difference value between the PDSCH-SINR and the CRS-SINR is greater than the first threshold, it may be determined that the wide-and-narrow beam effect has occurred. When a difference value between the PDSCH-SINR and the CRS-SINR is equal to or less than the first threshold, it may be determined that the wide-and-narrow beam effect has not occurred. Here, the second threshold may represent, for example, a relative SINR index threshold th-sinr-for-BF, and may have a range of values ​​from 5 to 10 dB, for example.

[0125] For example, in one embodiment of the present disclosure, when the current network standard is a 5G network standard, the feature recognition result is determined to be a preset result based on a difference value between the PDSCH-SINR (or PDCCH-SINR) and the TRS CSI-SINR (or Synchronization Signal-Signal to Interference plus Noise Ratio (SS-SINR)) and a first threshold value. Here, the first threshold value may represent, for example, a relative SINR index threshold th-sinr-for-BF, and may range from 5 dB to 10 dB.

[0126] For example, in one embodiment of the present disclosure, if the PDSCH-SINR (or PDCCH-SINR)-TRS CSI-SINR (or SS-SINR) is greater than a first threshold, 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 has occurred, and if the PDSCH-SINR (or PDCCH-SINR)-TRS CSI-SINR (or SS-SINR) is less than or equal to the first threshold, it can be determined that the feature recognition result is not a preset result, for example, it can be determined that the wide and narrow beam effect has not occurred.

[0127] According to some embodiments, the step of obtaining a feature recognition result in response to the 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 a step of determining that the feature recognition result is a predetermined result in response to a first ratio value of any one first parameter and any one second parameter being greater than a second threshold value, wherein the second threshold value represents a relative maximum delay extension index threshold, and the predetermined result indicates that at least one first parameter of the first beam feature set and at least one second parameter of the second beam feature set satisfy a predetermined condition.

[0128] According to some embodiments, the at least one first parameter includes a cell-specific reference signal-maximum delay extension (CRS-Tmax) and the at least one second parameter includes a physical downlink shared channel-maximum delay extension (PDSCH-Tmax), or the at least one first parameter includes a time-frequency tracking reference signal-maximum delay extension (TRS-Tmax) and the at least one second parameter includes at least one of a physical downlink shared channel-maximum delay extension (PDSCH-Tmax) and a physical downlink control channel-maximum delay extension (PDCCH-Tmax), where the second threshold value may represent, for example, a relative maximum delay extension index threshold th-tmax-for-BF, and may range from 1.5 to 3.

[0129] For example, in one embodiment of the present disclosure, when the current network standard is a 4G network standard, if 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, it can be determined that the wide and narrow beam effect has occurred, and when CRS-Tmax / PDSCH-Tmax is less than or equal to the second threshold, it can be determined that the feature recognition result is not a preset result, for example, it can be determined that the wide and narrow beam effect has not occurred.

[0130] For example, in one embodiment of the present disclosure, when the current network standard is a 5G network standard, if TRS-Tmax / PDSCH-Tmax (or PDCCH-Tmax) is greater than a second threshold, 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 has occurred, and when TRS-Tmax / PDSCH-Tmax (or PDCCH-Tmax) is less than or equal to a fourth threshold, it can be determined that the feature recognition result is not a preset result, for example, it can be determined that the wide and narrow beam effect has not occurred.

[0131] According to some embodiments, the step of obtaining a feature recognition result in response to the 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 a step of determining that the feature recognition result is a predetermined result in response to a second ratio value between any one first parameter and any one second parameter being greater than a third threshold value, wherein the third threshold value represents a relative root mean square delay extension index threshold, and the predetermined result indicates that at least one first parameter of the first beam feature set and at least one second parameter of the second beam feature set satisfy a predetermined condition.

[0132] According to some embodiments, the at least one first parameter comprises a cell-specific reference signal-root mean square delay extension (CRS-Trms) and the at least one second parameter comprises a physical downlink shared channel-root mean square delay extension (PDSCH-Trms), or the at least one first parameter comprises a time-frequency tracking reference signal-root mean square delay extension (TRS-Trms) and the at least one second parameter comprises at least one of a physical downlink shared channel-root mean square delay extension (PDSCH-Trms) and a physical downlink control channel-root mean square delay extension (PDCCH-Trms), where the third threshold value may represent, for example, a relative root mean square delay extension index threshold th-trms-for-BF, and may have a value ranging from 2 to 4, for example.

[0133] For example, in one embodiment of the present disclosure, when the current network standard is a 4G network standard, if CRS-Trms / PDSCH-Trms is greater than the third threshold, 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 has occurred, and when CRS-Trms / PDSCH-Trms is less than or equal to the third threshold, it can be determined that the feature recognition result is not a preset result, for example, it can be determined that the wide and narrow beam effect has not occurred.

[0134] For example, in one embodiment of the present disclosure, when the current network standard is a 5G network standard, if 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, it can be determined that the wide and narrow beam effect has occurred, and when TRS-Trms / PDSCH-Trms (or PDCCH-Trms) is less than or equal to the third threshold, it can be determined that the feature recognition result is not a preset result, for example, it can be determined that the wide and narrow beam effect has not occurred.

[0135] According to some embodiments, the step of obtaining a feature recognition result in response to the 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 the step of determining that the feature recognition result is a predetermined result in response to a second difference value between the signal-to-interference-plus-noise ratio (SINR) of any one of the at least one second parameters and the signal-to-interference-plus-noise ratio (SINR) of any one of the at least one first parameters being greater than a fourth threshold value and a third ratio value between the maximum Doppler of any one of the at least one second parameters and the maximum Doppler of any one of the at least one first parameters being less than a fifth threshold value, wherein the fourth threshold value represents a relative SINR index threshold and the fifth threshold value represents a relative maximum Doppler index threshold, and the predetermined result indicates that 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 satisfy a predetermined condition.

[0136] According to some embodiments, the at least one first parameter comprises at least one of CRS-SINR, PSS-SINR, SSS-SINR, and Cell-Specific Reference Signal - Max Doppler (CRS-Doppler), and the at least one second parameter comprises at least one of PDSCH-SINR and Physical Downlink Shared Channel - Max Doppler (PDSCH-Doppler), or the at least one first parameter comprises at least one of TRS CSI-SINR, SS-SINR, and Time-Frequency Tracking Reference Signal - Max Doppler (TRS-Doppler), and the at least one second parameter comprises at least one of PDSCH-SINR, PDCCH-SINR, Physical Downlink Control Channel - Max Doppler (PDCCH-Doppler), and Physical Downlink Shared Channel - Max Doppler (PDSCH-Doppler).

[0137] For example, in one embodiment of the present disclosure, when the current network standard is a 4G network standard, the feature recognition result is determined based on the PDSCH-SINR-CRS-SINR (or PSS-SINR or SSS-SINR) and a fourth threshold, and the PDSCH-Doppler / CRS-Doppler and a fifth threshold, where the fourth threshold may represent, for example, a relative SINR index threshold th-sinr-for-BF and may have a range of values ​​of, for example, 5 to 10 dB, and the fifth threshold may represent, for example, a relative maximum Doppler index threshold th-doppler-for-BF and may have a range of values ​​of, for example, 0.7 to 1.3.

[0138] For example, in one embodiment of the present disclosure, when the current network standard is a 4G network standard, if the PDSCH-SINR-CRS-SINR (or PSS-SINR or SSS-SINR) is greater than th-sinr-for-BF and the PDSCH-Doppler / CRS-Doppler is less than th-doppler-for-BF, 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 has occurred; and when the PDSCH-SINR-CRS-SINR (or PSS-SINR or SSS-SINR) is less than th-sinr-for-BF and / or the PDSCH-Doppler / CRS-Doppler is greater than th-doppler-for-BF, it can be determined that the feature recognition result is not a preset result, for example, it can be determined that the wide and narrow beam effect has not occurred.

[0139] In some embodiments, when the current network standard is a 5G network standard, the feature recognition result is determined based on the PDSCH-SINR (or PDCCH-SINR)-TRS CSI-SINR (or SS-SINR) and a fourth threshold, and the PDSCH-Doppler (or PDCCH-Doppler) / TRS-Doppler and a fifth threshold, where the fourth threshold may represent, for example, a relative SINR index threshold th-sinr-for-BF and may have a range of values ​​ranging from 5 to 10 dB, and the fifth threshold may represent, for example, a relative maximum Doppler index threshold th-doppler-for-BF and may have a range of values ​​ranging from 0.7 to 1.3.

[0140] For example, in one embodiment of the present disclosure, when the current network standard is a 5G network standard, if the PDSCH-SINR (or PDCCH-SINR)-TRS CSI-SINR (or SS-SINR) is greater than th-sinr-for-BF and the PDSCH-Doppler (or PDCCH-Doppler) / TRS-Doppler is less than th-doppler-for-BF, it may be determined that the feature recognition result is a preset result, for example, it may be determined that the wide and narrow beam effect has occurred, and the PDSCH-SINR (or PDCCH-SINR)-TRS CSI-SINR (or SS-SINR) is greater than th-sinr-for-BF and the PDSCH-Doppler (or PDCCH-Doppler) / TRS-Doppler is less than th-doppler-for-BF. If the CSI-SINR (or SS-SINR) is less than th-sinr-for-BF and / or the PDSCH-Doppler (or PDCCH-Doppler) / TRS-Doppler is greater than th-doppler-for-BF, it can be determined that the feature recognition result is not a preset result, for example, it can be determined that the wide and narrow beam effect recognition result is that the wide and narrow beam effect is not occurring.

[0141] In some embodiments, the step of obtaining a feature recognition result in response to the 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 the step of determining that the feature recognition result is a predetermined result in response to a fourth ratio value between the maximum delay extension (Tmax) of any one of the at least one second parameters and the maximum delay extension (Tmax) of any one of the at least one first parameters being greater than a sixth threshold and a fifth ratio value between the maximum Doppler (Doppler) of any one of the at least one second parameters and the maximum Doppler (Doppler) of any one of the at least one first parameters being less than a seventh threshold, wherein the sixth threshold represents a relative maximum delay extension index threshold and the seventh threshold represents a relative maximum Doppler index threshold, and the predetermined result indicates that 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 satisfy a predetermined condition.

[0142] In some embodiments, the at least one first parameter includes at least one of CRS-Tmax and cell-specific reference signal-maximum Doppler (CRS-Doppler), and the at least one second parameter includes at least one of PDSCH-Doppler and PDCCH-Tmax, or the at least one first parameter includes at least one of TRS-Tmax and TRS-Doppler, and the at least one second parameter includes at least one of PDSCH-Tmax, PDCCH-Tmax, PDSCH-Doppler, and PDCCH-Doppler. Here, the sixth threshold may represent, for example, a relative maximum delay extension indicator threshold th-tmax-for-BF, which may have a range of values ​​ranging from 1.5 to 3, and the seventh threshold may represent, for example, a relative maximum Doppler indicator threshold th-doppler-for-BF, which may have a range of values ​​ranging from 0.7 to 1.3.

[0143] For example, in one embodiment of the present disclosure, when the current network standard is a 4G network standard, if 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, it can be determined that the wide and narrow beam effect has occurred, and when CRS-Tmax / PDSCH-Tmax is less than th-tmax-for-BF and / or PDSCH-Doppler / CRS-Doppler is greater than th-doppler-for-BF, it can be determined that the feature recognition result is not a preset result, for example, it can be determined that the wide and narrow beam effect has not occurred.

[0144] In some embodiments, when the current network standard is a 4G network standard, the feature recognition result is determined based on TRS-Tmax / PDSCH-Tmax (or PDCCH-Tmax) and a sixth threshold, and PDSCH-Doppler (or PDCCH-Doppler) / TRS-Doppler and a seventh threshold, where the sixth threshold may represent, for example, a relative maximum delay extension index threshold th-tmax-for-BF, and may range from 1.5 to 3, and the seventh threshold may represent, for example, a relative maximum Doppler index threshold th-doppler-for-BF, and may range from 0.7 to 1.3.

[0145] For example, in one embodiment of the present disclosure, if 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, 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 has occurred. If TRS-Tmax / PDSCH-Tmax (or PDCCH-Tmax) is less than th-tmax-for-BF and / or PDSCH-Doppler (or PDCCH-Doppler) / TRS-Doppler is greater than th-doppler-for-BF, it can be determined that the feature recognition result is not a preset result, for example, it can be determined that the wide and narrow beam effect has not occurred.

[0146] In some embodiments, obtaining a feature recognition result in response to the operation result between 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 and the at least one threshold information includes determining whether a sixth ratio value between a maximum root mean square delay extension (Trms) of any one of the at least one second parameter and a maximum root mean square delay extension (Trms) of any one of the at least one first parameter is greater than an eighth threshold, and whether a maximum Doppler (Doppl) of any one of the at least one second parameter is greater than an eighth threshold. determining that the feature recognition result is a predetermined result in response to a seventh ratio value between the relative maximum root mean square delay extension threshold and the maximum Doppler index threshold of any one of the at least one first parameter being less than a ninth threshold, wherein the eighth threshold represents a relative maximum root mean square delay extension threshold and the ninth threshold represents a relative maximum Doppler index threshold, and the predetermined result indicates that 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 satisfy a predetermined condition.

[0147] In some embodiments, the at least one first parameter includes at least one of CRS-Trms and CRS-Dopple, and the at least one second parameter includes at least one of PDSCH-Trms and PDSCH-Doppler, or the at least one first parameter includes at least one of TRS-Trms and TRS-Doppler, and the at least one second parameter includes at least one of PDSCH-Trms, PDCCH-Trms, PDSCH-Doppler, and PDCCH-Doppler.

[0148] In some embodiments, when the current network standard is a first network standard, the feature recognition result may be determined based on CRS-Trms / PDSCH-Trms corresponding to at least one time point and an eighth threshold, and PDSCH-Doppler / CRS-Doppler corresponding to at least one time point and a ninth threshold. Here, the eighth threshold may represent, for example, a relative root-mean-square delay extension index threshold th-trms-for-BF, and may range from 2 to 4. The ninth threshold may represent, for example, a relative maximum Doppler index threshold th-doppler-for-BF, and may range from 0.7 to 1.3.

[0149] Exemplarily, in one embodiment of the present disclosure, when the current network standard is a first network standard, if 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, it can be determined that the wide and narrow beam effect has occurred; and when CRS-Trms / PDSCH-Trms is less than th-trms-for-BF and / or PDSCH-Doppler / CRS-Doppler is greater than th-doppler-for-BF, it can be determined that the feature recognition result is not a preset result, for example, it can be determined that the wide and narrow beam effect has not occurred.

[0150] In some embodiments, when the current network standard is a second network standard, the feature recognition result may be determined based on the TRS-Trms / PDSCH-Trms (or PDCCH-Trms) corresponding to at least one time point and an eighth threshold, and the PDSCH-Doppler (or PDCCH-Doppler) / TRS-Doppler and a ninth threshold. Here, the eighth threshold may represent, for example, a relative root-mean-square delay extension index threshold th-trms-for-BF, and may range from 2 to 4. The ninth threshold may represent, for example, a relative maximum Doppler index threshold th-doppler-for-BF, and may range from 0.7 to 1.3.

[0151] Exemplarily, in one embodiment of the present disclosure, when the current network standard is the second network standard, if TRS-Trms / PDSCH-Trms (or PDCCH-Trms) are greater than th-trms-for-BF and PDSCH-Doppler (or PDCCH-Doppler) / TRS-Doppler are less than th-doppler-for-BF, it can be determined that the feature recognition result is a preset result, for example, it can be determined that the wide and narrow beam effect has occurred; and if TRS-Trms / PDSCH-Trms (or PDCCH-Trms) are less than th-trms-for-BF and / or PDSCH-Doppler (or PDCCH-Doppler) / TRS-Doppler are greater than th-doppler-for-BF, it can be determined that the feature recognition result is not a preset result, for example, it can be determined that the wide and narrow beam effect has not occurred.

[0152] In some embodiments, the step of obtaining a feature recognition result in response to the 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 the step of determining that the feature recognition result is a predetermined result in response to a third difference value between the SINR of any one of the at least one second parameters and the SINR of any one of the at least one first parameters being greater than a tenth threshold and an eighth ratio value between the maximum delay extension (Tmax) of any one of the at least one second parameters and the maximum delay extension (Tmax) of any one of the at least one first parameters being greater than an eleventh threshold, wherein the tenth threshold represents a relative SINR index threshold and the eleventh threshold represents a relative maximum delay extension index threshold, and the predetermined result indicates that 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 satisfy a predetermined condition.

[0153] In some embodiments, the at least one first parameter includes at least one of CRS-SINR, PSS-SINR, SSS-SINR, and CRS-Tmax, and the at least one second parameter includes at least one of PDSCH-SINR and PDSCH-Tmax, or the at least one first parameter includes at least one of TRS CSI-SINR, SS-SINR, and TRS-Tmax, and the at least one second parameter includes at least one of PDSCH-SINR, PDCCH-SINR, PDSCH-Tmax, and PDCCH-Tmax.

[0154] In some embodiments, when the current network standard is a first network standard, the feature recognition result can be determined based on PDSCH-SINR-CRS-SINR (or PSS-SINR or SSS-SINR) and a tenth threshold, and CRS-Tmax / PDSCH-Tmax and an eleventh threshold, where the tenth threshold may represent, for example, a relative SINR index threshold th-sinr-for-BF and may have a range of values ​​ranging from 5 to 10 dB, and the eleventh threshold may represent, for example, a relative maximum delay extension index threshold th-tmax-for-BF and may have a range of values ​​ranging from 1.5 to 3.

[0155] Exemplarily, in one embodiment of the present disclosure, when the current network standard is a first network standard, if PDSCH-SINR-CRS-SINR (or PSS-SINR or SSS-SINR) is greater than th-sinr-for-BF and CRS-Tmax / PDSCH-Tmax is greater than th-tmax-for-BF, 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 has occurred, and when PDSCH-SINR-CRS-SINR (or PSS-SINR or SSS-SINR) is less than th-sinr-for-BF and / or CRS-Tmax / PDSCH-Tmax is less than th-tmax-for-BF, it can be determined that the feature recognition result is not a preset result, for example, it can be determined that the wide and narrow beam effect has not occurred.

[0156] In some embodiments, when the current network standard is the second network standard, the feature recognition result may be determined based on the PDSCH-SINR (or PDCCH-SINR)-TRS CSI-SINR (or SS-SINR) and the tenth threshold, and the TRS-Tmax / PDSCH-Tmax (or PDCCH-Tmax) and the eleventh threshold. Here, the tenth threshold may represent, for example, a relative SINR index threshold th-sinr-for-BF, which may range from 5 to 10 dB. The eleventh threshold may represent, for example, a relative maximum delay extension index threshold th-tmax-for-BF, which may range from 1.5 to 3.

[0157] For example, in one embodiment of the present disclosure, when the current network standard is the second network standard, if the 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 may be determined that the feature recognition result is a preset result, for example, it may be determined that the wide and narrow beam effect has occurred, and the PDSCH-SINR (or PDCCH-SINR)-TRS If the CSI-SINR (or SS-SINR) is less than or equal to th-siNR-for-BF and / or the TRS-Tmax / PDSCH-Tmax (or PDCCH-Tmax) is less than or equal to th-tmax-for-BF, it can be determined that the feature recognition result is not a preset result, for example, it can be determined that the wide and narrow beam effect recognition result is that the wide and narrow beam effect is not occurring.

[0158] In some embodiments, obtaining a feature recognition result in response to the 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 determining that the feature recognition result is a predetermined result in response to a fourth difference value between the SINR of any one of the at least one second parameters and the SINR of any one of the at least one first parameters being greater than a twelfth threshold and a ninth ratio value between the maximum root mean square delay extension (Trms) of any one of the at least one second parameters and the maximum root mean square delay extension (Trms) of any one of the at least one first parameters being greater than a thirteenth threshold, wherein the twelfth threshold represents a relative SINR index threshold and the thirteenth threshold represents a relative maximum root mean square delay extension, and the predetermined result indicates that 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 satisfy a predetermined condition.

[0159] In some embodiments, the at least one first parameter includes at least one of CRS-SINR, PSS-SINR, SSS-SINR, and CRS-Trms, and the at least one second parameter includes at least one of PDSCH-SINR and PDSCH-Tmax, or the at least one first parameter includes at least one of TRS CSI-SINR, SS-SINR, and TRS-Trms, and the at least one second parameter includes at least one of PDSCH-SINR, PDCCH-SINR, PDSCH-Trms, and PDCCH-Trms.

[0160] In some embodiments, when the current network standard is a first network standard, the feature recognition result may be determined based on PDSCH-SINR-CRS-SINR (or PSS-SINR or SSS-SINR) and a twelfth threshold, and CRS-Trms / PDSCH-Trms and a thirteenth threshold, where the twelfth threshold may represent, for example, a relative SINR index threshold th-sinr-for-BF and may have a range of values ​​ranging from 5 to 10 dB, and the thirteenth threshold may represent, for example, a relative root-mean-square delay extension index threshold th-trms-for-BF and may have a range of values ​​ranging from 2 to 4.

[0161] Exemplarily, in one embodiment of the present disclosure, when the current network standard is the first network standard, if the PDSCH-SINR-CRS-SINR (or PSS-SINR or SSS-SINR) is greater than th-sinr-for-BF and CRS-Trms / PDSCH-Trms is greater than th-trms-for-BF, 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 has occurred; and when the PDSCH-SINR-CRS-SINR (or PSS-SINR or SSS-SINR) is less than th-sinr-for-BF and / or CRS-Trms / PDSCH-Trms is less than th-trms-for-BF, it can be determined that the feature recognition result is not a preset result, for example, it can be determined that the wide and narrow beam effect has not occurred.

[0162] In some embodiments, when the current network standard is a second network standard, the feature recognition result may be determined based on the PDSCH-SINR (or PDCCH-SINR)-TRS CSI-SINR (or SS-SINR) and the 12th threshold, and the TRS-Trms / PDSCH-Trms (or PDCCH-Trms) and the 13th threshold, where the 12th threshold may represent, for example, a relative SINR indicator threshold th-sinr-for-BF and may have a range of values ​​ranging from 5 to 10 dB, and the 13th threshold may represent, for example, a relative root-mean-square delay extension indicator threshold th-trms-for-BF and may have a range of values ​​ranging from 2 to 4.

[0163] For example, in one embodiment of the present disclosure, when the current network standard is the second network standard, if PDSCH-SINR (or PDCCH-SINR) - TRS-Trms / PDSCH-Trms (or PDCCH-Trms) is greater than th-sinr-for-BF and TRS-Trms / PDSCH-Trms (or PDCCH-Trms) is greater than th-trms-for-BF, it may be determined that the feature recognition result is a preset result. For example, it may be determined that the wide and narrow beam effect recognition result is that the wide and narrow beam effect has occurred, and PDSCH-SINR (or PDCCH-SINR) - TRS-Trms / PDSCH-Trms (or PDCCH-Trms) may be determined. If the CSI-SINR (or SS-SINR) is less than or equal to th-siNR-for-BF and / or the TRS-Trms / PDSCH-Trms (or PDCCH-Trms) is less than or equal to th-trms-for-BF, it can be determined that the feature recognition result is not a preset result, for example, it can be determined that the wide and narrow beam effect recognition result is that the wide and narrow beam effect is not occurring.

[0164] In some embodiments, the step of obtaining the feature recognition result in response to the operation result between 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 and the at least one threshold information includes obtaining the feature recognition result when a fifth difference value between the SINR of any one of the at least one second parameter and the SINR of any one of the at least one first parameter is greater than a fourteenth threshold, a tenth ratio value between the maximum delay extension (Tmax) of any one of the at least one second parameter and the maximum delay extension (Tmax) of any one of the at least one first parameter is greater than a fifteenth threshold, and and determining that the feature recognition result is a predetermined result in response to an 11th ratio value between the maximum root mean square delay extension (Trms) of any one of the at least one first parameters and the maximum root mean square delay extension (Trms) of any one of the at least one first parameters being greater than a 16th threshold, wherein the 14th threshold represents a relative SINR index threshold, the 15th threshold represents a relative maximum delay extension index threshold, and the 16th threshold represents a relative maximum root mean square delay extension, and the predetermined result indicates that at least one first parameter of the first beam feature set and at least one second parameter of the second beam feature set satisfy a predetermined condition.

[0165] In some embodiments, the at least one first parameter includes at least one of CRS-SINR, PSS-SINR, SSS-SINR, CRS-Tmax, and CRS-Trms, and the at least one second parameter includes at least one of PDSCH-SINR, PDSCH-Tmax, and PDSCH-Trms, or the at least one first parameter includes at least one of TRS CSI-SINR, SS-SINR, TRS-Tmax, and TRS-Trms, and the at least one second parameter includes at least one of PDSCH-SINR, PDCCH-SINR, PDSCH-Tmax, PDCCH-Tmax, PDSCH-Trms, and PDCCH-Trms.

[0166] In some embodiments, when the current network standard is a first network standard, the feature recognition result may be determined based on PDSCH-SINR-CRS-SINR (or PSS-SINR or SSS-SINR) and a 14th threshold, CRS-Tmax / PDSCH-Tmax and a 15th threshold, and CRS-Trms / PDSCH-Trms and a 16th threshold. Here, the 14th threshold may represent, for example, a relative SINR index threshold th-sinr-for-BF and may have a range of values ​​of, for example, 5 to 10 dB. The 15th threshold may represent, for example, a relative maximum delay extension index threshold th-tmax-for-BF and may have a range of values ​​of, for example, 1.5 to 3. The 16th threshold may represent, for example, a relative root-mean-square delay extension index threshold th-trms-for-BF and may have a range of values ​​of, for example, 2 to 4.

[0167] For example, in one embodiment of the present disclosure, when the current network standard is a first network standard, if PDSCH-SINR-CRS-SINR (or PSS-SINR or SSS-SINR) is greater than th-sinr-for-BF, CRS-Tmax / PDSCH-Tmax is greater than th-tmax-for-BF, and CRS-Trms / PDSCH-Trms is greater than th-trms-for-BF, it may be determined that the feature recognition result is a preset result. For example, it may be determined that the wide and narrow beam effect recognition result indicates that the wide and narrow beam effect occurs. If PDSCH-SINR-CRS-SINR (or PSS-SINR or SSS-SINR) is less than or equal to th-sinr-for-BF and / or CRS-Tmax / PDSCH-Tmax is less than or equal to th-tmax-for-BF and / or CRS-Trms / PDSCH-Trms is less than or equal to th-trms-for-BF, it can be determined that the feature recognition result is not a preset result, for example, it can be determined that the wide and narrow beam effect recognition result is that the wide and narrow beam effect has not occurred.

[0168] In some embodiments, when the current network standard is a second network standard, a wide-and-narrow beam effect recognition result corresponding to at least one time point may be determined based on PDSCH-SINR (or PDCCH-SINR) - TRS CSI-SINR (or SS-SINR) and a 14th threshold, TRS-Tmax / PDSCH-Tmax (or PDCCH-Tmax) and a 15th threshold, and TRS-Trms / PDSCH-Trms (or PDCCH-Trms) and a 16th threshold. Here, the 14th threshold may represent, for example, a relative SINR index threshold th-sinr-for-BF, which may have a range of values ​​ranging from 5 to 10 dB, and the 15th threshold may represent, for example, a relative maximum delay extension index threshold th-tmax-for-BF, which may have a range of values ​​ranging from 1.5 to 3. The sixteenth threshold may represent, for example, a relative root mean square delay extension index threshold th-trms-for-BF, and may range in value from 2 to 4, for example.

[0169] For example, in one embodiment of the present disclosure, if PDSCH-SINR (or PDCCH-SINR) - TRS CSI-SINR (or SS-SINR) is greater than th-sinr-for-BF, 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 may be determined that the feature recognition result is a preset result, for example, it may be determined that the wide and narrow beam effect has occurred, and PDSCH-SINR (or PDCCH-SINR) - TRS If the CSI-SINR (or SS-SINR) is less than or equal to th-siNR-for-BF and / or the TRS-Tmax / PDSCH-Tmax (or PDCCH-Tmax) is less than or equal to th-tmax-for-BF and / or the TRS-Trms / PDSCH-Trms (or PDCCH-Trms) is less than or equal to th-trms-for-BF, it can be determined that the feature recognition result is not a preset result, for example, it can be determined that the wide and narrow beam effect recognition result is that the wide and narrow beam effect is not occurring.

[0170] Here, in an embodiment of the present disclosure, multiple solutions for determining a feature recognition result in response to the 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 may, for example, be combined to determine the feature recognition result, which can improve the accuracy of determining the feature recognition result, reduce cases where accuracy is poor based on the wireless channel state information required for channel estimation, improve the reception status of the communication device, and improve the communication quality of the communication device.

[0171] 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 to obtain a feature recognition result output by the beam sensing neural network model, where the feature recognition result indicates 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 satisfy a preset condition.

[0172] The specific process is as described above, and a detailed description is omitted here.

[0173] Here, in one embodiment of the present disclosure, the type of the pre-set beam sensing neural network model is not limited, and it may be, for example, a model that can determine a 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.

[0174] According to some embodiments, the step of inputting at least one first parameter of the first beam feature set and at least one second parameter of the second beam feature set into a predetermined beam sensing neural network model to obtain the feature recognition result output by the beam sensing neural network model includes the steps 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 predetermined beam sensing neural network model to obtain a vector corresponding to the at least one first parameter and the at least one second parameter, and performing a recognition process on the vector using an activation function of the predetermined beam sensing neural network model to obtain the feature recognition result output by the beam sensing neural network model.

[0175] 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 can be input to a preset beam sensing neural network model, and the beam sensing neural network model can be controlled to estimate whether a wide and narrow beam effect has occurred at the current time.

[0176] In some embodiments, when the current network standard is the second network standard, SS-SINR, TRS CSI-SINR, TRS-Tmax, TRS-Trms, TRS-Doppler, PDCCH-SINR, PDSCH-Tmax (PDCCH-Tmax), PDSCH-Trms (PDCCH-Trms), and PDSCH-Doppler (PDCCH-Doppler) can be input to a beam sensing neural network model. The beam sensing neural network model can be controlled to estimate whether a wide and narrow beam effect has occurred at the current time.

[0177] In response to some embodiments, the wide and narrow beam effect recognition result may be, for example, an output period Tbf, and the range of values ​​that can be taken may be, for example, 0.5 to 5 ms.

[0178] In some embodiments, the input features of the pre-configured beam sensing neural network model may be, for example:

[0179]

number

[0180] Here, if the current network standard is the first network standard, the input of the preset beam sensing neural network model is expressed in the following format: 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 It is an 8x1 vector (where the subscript T at the end of the formula represents transposition, i.e., rearranging a 1x8 row vector into an 8x1 column vector), and each element of the vector represents the result obtained by the t-th sampling, and X[t] is the signal feature obtained by the t-th sampling.

[0181] Here, if the current network standard is the second network standard, the input of the preset beam sensing neural network is expressed in the following format: 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 It is a 9x1 vector, each element of which represents the result obtained by the t-th sampling, and X[t] is the signal feature obtained by the t-th sampling.

[0182] In some embodiments, in a beam sensing neural network model based on a fully connected neural network, each time a signal feature is sampled, the fully connected neural network model is invoked once using only the signal feature of the current sampling to obtain an estimated output value corresponding to the current sampling. Therefore, in the embodiments of the present disclosure, in ×1-dimensional vector,

[0183]

number

[0184] In some embodiments, Figure 8a is an exemplary schematic diagram of a neural network model according to an exemplary embodiment, and as shown in Figure 8a, the preset beam sensing neural network model may be, for example, a fully connected network model, which includes one input layer, M > 1 hidden layers, and one output layer;

[0185]

number

[0186]

number

[0187]

number

[0188]

number

[0189] According to some embodiments, N out The default value of is 1, and the following judgment is made based on the output layer node: if z1>0, the beam sensing neural network judges that the wide and narrow beam effect has occurred at the current time; otherwise, it judges that the wide and narrow beam effect has not occurred at the current time.

[0190] Here, in one embodiment of the present disclosure, the number of input nodes is N in = 8, and the number of output nodes is N out = 1, and the number of hidden layers is M = 2,

[0191]

number

[0192] W1 is the following 6x8 dimensional matrix. [0.47425 -0.01978 -1.9843 0.36086 -1.595 -0.037328 0.43774 0.33768; 0.59427 -1.0934 0.40933 0.34503 0.24259 -0.43542 1.7432 -1.0481; -0.55435 0.074074 0.72131 0.71858 0.9091 0.95278 -0.58335 0.26392; -1.0326 -0.59564 0.73049 0.42118 0.085769 0.71246 0.93609 -0.18115; 2.1112 -0.62527 0.57654 1.0897 0.78288 0.86894 0.42387 -0.78136; 1.7352 0.90966 -1.0508 -0.86148 1.5539 -0.56438 -0.18695 2.4039]

[0193] b1 is the following 6x1 dimensional vector. [0.56686; -0.47827; -0.91867; 1.8984; 0.61859; 0.030253]

[0194] W2 is the following 4x6 dimensional matrix. [-0.47758 -0.49359 0.052784 0.23745 1.3879 -0.21832; 1.3286 0.23366 -0.085707 0.50344 2.4921 -0.14543; 0.63552 -2.0057 0.28092 -0.30701 -0.58309 1.2332; 0.83319 -0.23135 -0.23071 -2.5688 0.9832 0.075375]

[0195] b2 is the following 4x1 dimensional vector: [-0.32724; 1.7266; 0.15219; -1.319]

[0196] W out is a 1x4 dimensional vector. [-0.036337 -1.234 -1.2407 -1.4056]

[0197] b out is the following 1×1 dimensional scalar: [-0.3172]

[0198] Here, in one embodiment of the present disclosure, the number of input nodes is N in = 9, and the number of output nodes is N out = 1, the number of hidden layers is M = 3,

[0199]

number

[0200] W1 is the following 4x9 dimensional matrix. [0.59364 -0.20928 -1.1535 -1.2801 0.60269 -0.058899 -1.8738 -0.73964 -0.91751; 1.436 0.69515 0.61159 -1.0286 -0.79876 -1.733 0.045742 1.3826 -0.47894; 1.0405 1.1476 -0.5495 0.051149 1.3497 -1.0605 0.44058 0.024944 0.90165; -0.20849 0.34914 0.39515 -2.0721 0.12201 0.080399 -0.40045 -0.32359 0.46772]

[0201] b1 is the following 4x1 dimensional vector. [-0.52743; -0.72111; -0.96918; 1.2817]

[0202] W2 is the following 3x4 dimensional matrix. [1.371 1.9237 -0.87408 1.2361; 0.20461 -0.12354 -2.0295 1.1392; -0.97443 -0.17133 0.61787 -1.6262]

[0203] b2 is the following 3x1 dimensional vector: [0.68037; 0.043459; 0.54384]

[0204] W3 is the following 2x3 dimensional matrix. [0.48873 -0.74289 1.1725; 1.49 1.5016 -1.5343]

[0205] b3 is the following 2x1 dimensional vector: [1.203; -0.50165]

[0206] W out is the following 1×2 dimensional vector: [-1.6399 0.18647]

[0207] b out is the following 1×1 dimensional scalar: [0.30811]

[0208] In one embodiment of the present disclosure, for example, a beam sensing neural network model can be trained, where training data and test data can be obtained, for example, from historical communication data or from simulation data. The embodiment of the present disclosure is not limited thereto. In an actual communication process or data simulation, signal features associated with the input of the beam sensing neural network model can be recorded, and labels (i.e., expected output values) of the signal features can be marked according to the current actual communication performance or simulation performance. Each time sampling is performed, a set of input data and corresponding output labels can be obtained. Taking the second network standard as an example, the input obtained by the tth 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 one training or test data of the beam sensing neural network model. Multiple data are obtained by multiple samplings, and these data can be divided into a training data set and a test data set, where the training data set is used to train the neural network parameters, i.e., to obtain each of the preset parameter matrices / vectors / scalars mentioned above, and the test data set is used to verify the performance of the training results.

[0209] In some embodiments, Figure 8b is an exemplary schematic diagram of a neural network model according to an exemplary embodiment, and as shown in Figure 8b, the preset beam sensing neural network model may be, for example, a recursive neural network model. In a beam sensing model based on a recursive neural network, each time a signal feature is sampled, a recursive neural network model is invoked once based on the signal features from the current sampling to the L previous samples to obtain an estimated output value corresponding to the current sampling. Therefore, in a recursive neural network, input data is represented by [x[t-L+1],...,x[t-1],x[t]].

[0210] According to some embodiments, the network model has L hidden states {h[t-L+1],...,h[t]} and L fully connected layers {Φ1,...,Φ L} and one output layer Φ out Including,

[0211]

number

[0212] According to some embodiments, the calculation method (1) of the first hidden state h[t−L+1] is as follows: h[t-L+1]=f1(W hx,1 x[t-L+1]+b1) (1)

[0213]

number

[0214] The calculation method (2) for the kth hidden state (k=2,...,L) is as follows: h[t-L+k]=f k (W hx,k x[t-L+k]+W hh,k h[t-L+k-1]+b k ) (2)

[0215]

number

[0216] According to some embodiments, each node in the output layer may be:

number

[0217]

number

[0218] b out is N out f is a 1-dimensional vector, and both are fixed real coefficients that are preset and obtained through a prior neural network training process. out (·) represents the activation function applied to the output layer, and the definition of the activation function is the same as above.

[0219] According to some embodiments, N out The default value of is 1, and the following judgment is made based on the output layer node: if z1>0, the beam sensing neural network judges that the wide and narrow beam effect has occurred at the current time; otherwise, it judges that the wide and narrow beam effect has not occurred at the current time.

[0220] According to some embodiments, the number of input nodes is N in = 8, and the number of output nodes is N out = 1, the number of hidden states is L = 2,

[0221]

number

[0222] W hx,1 is the following 2x8 dimensional matrix: [0.95805 0.32599 0.50035 0.52071 -1.1799 0.16249 0.51442 0.46264; -0.76883 0.90085 1.8183 -1.201 -0.76587 -1.0905 -0.14306 -0.14932]

[0223] b1 is the following 2x1 dimensional vector. [0.13263; 2.5974]

[0224] W hx,2 is the following 3x8 dimensional matrix: [1.2837 0.30872 0.47553 0.029408 0.15568 0.21218 -1.8522 -0.6046; 1.8945 -0.53089 0.79864 -0.23068 2.5903 0.86492 -0.21696 -0.98725; -2.5078 -1.0806 0.1192 -0.96649 0.33618 -0.96293 -0.37006 0.14036]

[0225] b2 is the following 3x1 dimensional vector: [-0.41078; -0.097416; -0.15023]

[0226] W hh,2 is the following 3x2 dimensional matrix: [-0.27852 0.91732; 0.12799 0.76073; -0.075746 -0.99056]

[0227] W out is the following 1×3 dimensional vector: [-0.45479 -0.48775 -0.67786]

[0228] b outis the following 1×1 dimensional scalar: [1.2692]

[0229] According to some embodiments, the number of input nodes is N in = 9, and the number of output nodes is N out = 1, the number of hidden states is L = 3,

[0230]

number

[0231] The activation functions of the first, second, and third hidden layers are Sigmoid, ReLU, and Softplus, respectively, and the activation function of the output layer is Softmax.

[0232] W hx,1 is the following 3x9 dimensional matrix: [0.46432 0.28459 -0.37168 -0.39109 -0.11489 -1.2409 0.43961 1.5053 0.72785; 0.24993 -1.0127 -0.86236 -0.76395 -0.30244 -0.073267 -1.3072 -0.58309 0.19708; -0.89957 1.006 1.1514 1.5531 2.0053 0.040107 -0.38166 -1.7546 0.48341]

[0233] b1 is the following 3x1 dimensional vector. [1.4983; 0.93334; -0.84369]

[0234] W hx,2 is the following 2x9 dimensional matrix: [1.1493 -1.2864 0.27587 0.8826 -1.0677 0.42064 -0.15513 -0.72571 -0.35817; 0.63565 1.2868 0.91628 1.2741 2.4115 0.39103 -0.39591 0.12894 -0.27977]

[0235] b2 is the following 2x1 dimensional vector: [0.98282; -0.85696]

[0236] W hh,2 is the following 2x3 dimensional matrix: [-0.113 -0.92787 0.38149; 1.1621 -0.32756 -0.70608]

[0237] W hx,3 is the following 2x9 dimensional matrix: [-1.1035 -1.056 0.32574 0.60097 0.9682 2.3773 -0.10138 -1.6612 -0.54795; -1.1946 0.76788 -0.65609 -1.0127 -0.92869 0.51302 0.40007 -1.6123 -0.98417]

[0238] b3 is the following 2x1 dimensional vector: [-1.2314; 0.49445]

[0239] W hh,3 is the following 2x2 dimensional matrix: [-1.6949 0.95131; -0.37369 -1.6743]

[0240] W out is the following 1×2 dimensional vector: [0.88022 0.77134]

[0241] b out is the following 1×1 dimensional scalar: [-1.4642]

[0242] Here, in one embodiment of the present disclosure, the training data or test data of the recursive neural network can be obtained, for example, from actual historical communication data or simulation data. In the actual communication process or data simulation process, the signal features associated with the neural network input can be recorded, and the labels (i.e., expected output values) of the signal features can be marked based on the current actual communication performance or simulation performance. Each time sampling is performed, a set of input data and corresponding output labels can be obtained. According to the second network standard, that is, taking the 5G customer premises network state as an example, the input obtained at the tth sampling is x[t]=[SS-SINR[t], TRS CSI-SINR[t], TRS-Tmax[t], TRS-Trms[t], TRS-Doppler[t], PDSCH-SINR[t] (or PDCCH-SINR), PDSCH-Tmax[t] (or PDCCH-Tmax), PDSCH-Trms[t] (or PDCCH-Trms), PDSCH-Doppler[t] (or PDCCH-Doppler)]. T If x[t], the output value obtained by marking is z[t]. Different from a fully connected neural network model, each data of a recurrent neural network not only includes the input and output at the current time, but also includes inputs at the L-1 previous times, i.e., {x[t-L+1],...,x[t],z[t]} constitutes one training or test data of the neural network. Multiple data are obtained through multiple samplings, and these data can be divided into a training data set and a test data set, where the training data set is used to train the recurrent neural network parameters, i.e., to obtain each preset parameter matrix / vector / scalar of the recurrent neural network model, and the test data set is used to verify the performance of the training results.

[0243] For a given neural network model, the training goal of the neural network model is to minimize the error between the predicted output values ​​and the actual output value labels. A loss function may be defined to quantify the difference between the predicted values ​​and the actual values.

[0244]

number

[0245] Based on the above training data and loss function, we first calculate the initial values ​​(W hx,1 ,…,W hx,L ,W out ,b1,…,b L ,b out ,W hh,2 ,…,W hh,L Then, based on the training samples, calculate the total error, which is the sum of the loss functions of all the training set samples. Then, use the backpropagation process of the recursive neural network model to continuously modify the above calculated parameters during the iteration process until the sum of the loss functions of all the training set samples meets the requirement.

[0246] Optionally, FIG. 8c is an exemplary schematic diagram of a neural network model according to an exemplary embodiment. As shown in FIG. 8c, the preset beam sensing neural network model in the embodiment of the present disclosure is a random forest model. In the beam sensing model based on random forest, each time a signal feature is sampled, the random forest model is invoked once using only the signal feature of the current sampling to obtain an estimated output value corresponding to the current sampling. Therefore, in this section, the input N in × 1-dimensional vector

[0247]

number

[0248] According to some embodiments, the network model includes a decision tree, and when P=1, the random forest model degenerates into a decision tree. Each decision tree provides a different discriminant classification result based on the input data. For example, A and B in FIG. 8c can represent that the wide-and-narrow beam effect occurs at the current time and that the wide-and-narrow beam effect does not occur at the current time, respectively. A vote may be performed on the classification results of multiple decision trees, and the classification result with the most votes becomes the final classification result.

[0249] In some embodiments, taking the binary tree shown in Fig. 8c as an example, the implementation of a single decision tree may be as shown in Fig. 8d, where the bottom layer of the decision tree is the leaf nodes, each of which corresponds to a classification result, and when the decision process is included in a specific leaf node, it can determine the final classification result of the decision tree. In a decision tree, each node in other layers other than the bottom leaf node obtains any feature of the input data and determines whether it meets a certain condition, thereby determining which child node the node should proceed to next.

[0250] Assuming that the order relation is used as the judgment condition for each node, the judgment node for each non-leaf node can be expressed as [k, T], where k represents the feature number and T represents the order relation threshold, that is, the input data

[0251]

number

[0252] Specifically, for a decision tree with Q internal nodes shown in Figure 8d, the input data

[0253]

number

[0254] First judgment: The root node contains the preset parameters [k 0,1 ,T 0,1 ], where the first parameter has possible values ​​1,…,N in The second parameter is a real threshold.

[0255]

number

[0256] Second judgment: The pre-set parameters [k 1,1 ,T 1,1 ],[k 1,2 ,T 1,2 ], where the first parameter in each set of parameters has the possible values ​​1,…,N in The second parameter is a real number threshold. c1 Based on the second decision, the parameters corresponding to the relevant nodes are

[0257]

number

[0258]

number

[0259] According to some embodiments, the number of input nodes is N in = 8, the number of decision trees is P = 3, and the number of internal node layers is Q = 1. The parameters corresponding to the random forest are as follows: Decision tree 1:[k 0,1 ,T 0,1 ]=[1,2.5], [k 1,1 ,T 1,1 ]=[2,1], [k 1,2 ,T 1,2 ]=[4,10]; 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]; 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].

[0260] According to some embodiments, the number of input nodes is N in = 9, the number of decision trees is P = 1, and the number of internal node layers is Q = 2. The parameters corresponding to the random forest are as follows: 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].

[0261] According to some embodiments, training or test data for the random forest can be obtained, for example, from actual historical communication data or numerical simulation. In the actual communication process or numerical simulation, signal features associated with neural network inputs can be recorded, and labels (i.e., expected output values) for the signal features can be marked according to the current actual communication performance or simulated performance. A set of input data and corresponding output labels can be obtained at each sampling. Taking the state of a 5G customer premises network, which is the second network standard, as an example, the input obtained by the tth sampling can be expressed as x[t]=[SS-SINR[t], TRS CSI-SINR[t], TRS-Tmax[t], TRS-Trms[t], TRS-Doppler[t], PDSCH-SINR[t] (or PDCCH-SINR), PDSCH-Tmax[t] (or PDCCH-Tmax), PDSCH-Trms[t] (or PDCCH-Trms), PDSCH-Doppler[t] (or PDCCH-Doppler)]. T If x[t], the obtained output value is marked as z[t], and {x[t],z[t]} constitutes one training or test data of the random forest. Multiple data are obtained through multiple samplings, and these data can be divided into a training data set and a test data set, where the training data set is used for random forest parameter training, i.e., to obtain each preset parameter matrix / vector / scalar mentioned in this section, and the test data set is used to verify the performance of the training results.

[0262] Based on the above training data, each decision tree in the random forest can be constructed, for example, by the following method, where different decision trees are constructed independently and the construction method is the same.

[0263] A subset of samples is extracted with replacement from the entire training set, and a decision tree is trained on the extracted samples.

[0264] Each sample contains N in There are input attributes, and at each node that needs to be split in the decision tree, a specific policy is used to select one attribute as the split attribute for the node, and a corresponding split threshold is determined; the attribute and threshold are not limited, and information gain, for example, can be used.

[0265] In the process of forming a decision tree, each node splits based on the previous step until the node reaches a maximum depth or cannot be split any further.

[0266] To ensure the consistency of the process (i.e., after the maximum depth is given, the total number of decisions in any case is the same), we extend branches whose depth is less than the maximum depth (early termination due to the sample not supporting subdivision) to the maximum depth. The extension method is as follows: For leaf nodes less than the maximum depth, we continue to extend the branches, and then set all the decision parameters of each decision node to [1,T max +1], where T max is always greater than any possible value of x1[t] in any case, for example, infinity. Furthermore, all of the final leaf node determination results corresponding to these branches are the determination results of leaf nodes less than the maximum depth.

[0267] 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 predetermined condition, the first beam feature set or the second beam feature set is selected as a source for acquiring wireless channel state information.

[0268] The specific process is as described above, and a detailed description is omitted here.

[0269] In response to some embodiments, for a continuous observation fixed period, the first time information is the time of any one of the current periods in the continuous observation preset period, and the second time information is the next preset period adjacent to the current period, in this case, an exemplary schematic diagram of the first time information and the second time information may be, for example, as shown in FIG. 9 .

[0270] In response to some embodiments, the step of selecting the first beam feature set or the second beam feature set as an acquisition source of wireless channel state information includes a step of determining that the acquisition source corresponding to the wireless channel state information in the second time information is a dynamic beam feature acquisition source in response to the feature recognition result corresponding to the first time information satisfying a first result requirement and the wireless resource control connection of the communication device not being reset or released, wherein the first time information is the time of any one of the current periods in a continuous observation preset period, the second time information is the next preset period adjacent to the current period, and the first result requirement includes a result requirement that all of the feature recognition results corresponding to the first time information are preset results, or a result requirement that a first number of preset results among the feature recognition results corresponding to the first time information satisfy a number requirement.

[0271] According to some embodiments, the step of selecting the first beam feature set or the second beam feature set as the acquisition source of the radio channel state information includes a step of determining that the acquisition source corresponding to the radio channel state information in the second time information is a dynamic beam feature acquisition source when the feature recognition results corresponding to the first time information are all preset results and the radio resource control connection of the communication device has not been reset or released.

[0272] According to some embodiments, when the first time information is the time of any one of the current periods in the continuous observation preset period, and the step of selecting the first beam feature set or the second beam feature set as the acquisition source of the radio channel state information determines that the acquisition source corresponding to the radio channel state information in the second time information is a dynamic beam feature acquisition source if a first number of the preset results among the feature recognition results corresponding to the first time information meets a number requirement and the radio resource control connection of the communication device has not been reset or released.

[0273] Here, the first number may be, for example, a first number ratio, a first number percentage, a first number multiple, etc. The embodiments of the present disclosure are not limited thereto.

[0274] According to some embodiments, the step of selecting the first beam feature set or the second beam feature set as an acquisition source of wireless channel state information includes a step of determining that the acquisition source corresponding to the wireless channel state information in the second time information is a static beam feature acquisition source in response to the feature recognition result corresponding to the first time information satisfying a second result requirement, wherein the first time information is the time of any one of the current periods in the continuous observation preset period, and the second result requirement includes a result requirement that all feature recognition results corresponding to the first time information are not preset results, or a result requirement that a first number of preset results among the feature recognition results corresponding to the first time information do not satisfy a number requirement.

[0275] According to some embodiments, when the first time information is the time of any one of the current periods in the continuous observation preset period, the step of selecting the first beam feature set or the second beam feature set as the acquisition source of the wireless channel state information includes a step of determining that the acquisition source corresponding to the wireless channel state information in the second time information is a static beam feature acquisition source if the feature recognition results corresponding to the first time information are not all preset results.

[0276] Here, the time information is a continuous observation preset period, which may be, for example, an observation time window (Tobs) period, which may be a fixed observation time window with a possible value range of, for example, 50 to 100 ms, or may be a period corresponding to the number of observations (Nbf) of effective wide and narrow beam effect recognition results, where Nbf is a fixed number of observations with a possible value range of 20 to 50. Here, the time information may be a Tobs period, which can balance the recognition success rate and recognition timeliness, improve the efficiency of determining the wireless channel state information acquisition source, and improve the data reception performance of the communication device.

[0277] In response to some embodiments, when the first time information is the time of any one of the current periods in the continuous observation preset period, and the step of selecting the first beam feature set or the second beam feature set as the acquisition source of the wireless channel state information includes a step of determining that the acquisition source corresponding to the wireless channel state information in the second time information is a static beam feature acquisition source if a first number of the preset results among the feature recognition results corresponding to the first time information does not meet a number requirement.

[0278] Here, the number requirement may be, for example, that the ratio value of the first number to the third number is smaller than a 17th threshold, and the third number may be, for example, the total number corresponding to the wide and narrow beam effect recognition result corresponding to the first time information.

[0279] Here, the 17th threshold may represent, for example, a rate of observation (Rbf) threshold, and the range of values ​​that it can take may be, for example, 60% to 90%.

[0280] Here, the time information is a continuous observation preset period, which may be, for example, a Tobs period, where Tobs may be, for example, a fixed observation time window, the range of which may be, for example, 50 to 100 ms, or may be a period corresponding to Nbf consecutive effective wide and narrow beam effect recognition results, where Nbf is a fixed number of observations, the range of which may be 20 to 50. Here, since the time information is a Tobs period, it is possible to balance the recognition success rate and recognition timeliness, improve the efficiency of determining the wireless channel state information acquisition source, and improve the data reception performance of the communication device.

[0281] According to some embodiments, for a continuous observation sliding cycle, the first time information is the time of any one of the current cycles in the continuous observation sliding cycle, and the second time information is the time information before the next feature recognition result is obtained. In this case, an exemplary schematic diagram of the first time information and the second time information is as shown in Fig. 10, where the cycle sliding direction is an exemplary direction.

[0282] According to some embodiments, the step of selecting the first beam feature set or the second beam feature set as an acquisition source of wireless channel state information includes a step of determining that the acquisition source corresponding to the wireless channel state information in the second time information is a dynamic beam feature acquisition source in response to the feature recognition result corresponding to the first time information satisfying a first result requirement and the wireless resource control connection of the communication device not being reset or released, wherein the first time information is the time of any one of the current periods in the continuous observation sliding period, the second time information is the time information before the next feature recognition result is acquired, and the first result requirement includes a result requirement that all feature recognition results corresponding to the first time information are predetermined results, or a result requirement that a second number of predetermined results among the feature recognition results corresponding to the first time information satisfy a number requirement.

[0283] According to some embodiments, the step of selecting the first beam feature set or the second beam feature set as the acquisition source of the wireless channel state information includes a step of determining that the acquisition source corresponding to the wireless channel state information in the second time information is a static beam feature acquisition source in response to the feature recognition result corresponding to the first time information satisfying a second result requirement, where the first time information is any one time of the current period in the continuous observation sliding period, the second time information is time information before the next feature recognition result is acquired, and the second result requirement includes a result requirement that all feature recognition results corresponding to the first time information are not preset results, or a result requirement that a second number of preset results among the feature recognition results corresponding to the first time information do not satisfy a number requirement; and a step of observing updated information corresponding to the first time information before the feature recognition result corresponding to the second time information is acquired, and redetermining the acquisition source corresponding to the wireless channel state information in the second time information using the updated first time information as the first time information.

[0284] According to some embodiments, the first time information may be, for example, a continuous observation Tobs sliding window, and if 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 reset or released, the radio channel state information acquisition source is locked to the dynamic beam feature acquisition source before the feature recognition results are re-acquired.

[0285] According to some embodiments, the first time information may be, for example, a continuous observation Tobs sliding window, and if the feature recognition results corresponding to the first time information are not all preset results, the wireless channel state information acquisition source is a static beam feature acquisition source before the feature recognition results are re-acquired. The preset result may be, for example, "YES", and the embodiments of the present disclosure are not limited thereto.

[0286] According to some embodiments, the beam feature acquisition source is redetermined when the observation sliding window is updated before the feature recognition results are reacquired.

[0287] Here, the range of possible values ​​for the length Tobs of the sliding observation time window corresponding to the continuous observation Tobs sliding window may be, for example, 50 to 100 ms, or may be a period corresponding to Nbf consecutive effective wide and narrow beam effect recognition results, where Nbf is the number of sliding observations, and the range of possible values ​​may be, for example, 20 to 50.

[0288] In response to some embodiments, when the first time information is any one time of the current period in the continuous observation sliding period, and the step of selecting the first beam feature set or the second beam feature set as the acquisition source of the wireless channel state information includes a step of determining that the acquisition source corresponding to the wireless channel state information in the second time information is a dynamic beam feature acquisition source when a second number of predetermined results among the feature recognition results corresponding to the first time information meets a number requirement and the wireless resource control connection of the communication device has not been reset or released, wherein the second time information is the time information before the next feature recognition result is acquired.

[0289] In response to some embodiments, when the first time information is any one time of the current period in the continuous observation sliding period, the step of selecting the first beam feature set or the second beam feature set as the acquisition source of the wireless channel state information includes a step of determining that the acquisition source corresponding to the wireless channel state information in the second time information is a static beam feature acquisition source when a second number of predetermined results among the feature recognition results corresponding to the first time information does not meet a numerical requirement, and a step of observing updated information corresponding to the first time information before the feature recognition result corresponding to the second time information is acquired, and using the updated first time information as the first time information to re-determine the acquisition source corresponding to the wireless channel state information in the second time information, wherein the first time information is the length of the sliding observation time window, and the first time information is a period corresponding to a predetermined time length or a period corresponding to the effective wide and narrow beam effect recognition results of a preset number of consecutive sliding observations.

[0290] Here, the number requirement may be, for example, that the ratio value of the second number to the fourth number is greater than an 18th threshold, and the fourth number may be, for example, the total number corresponding to the wide and narrow beam effect recognition result corresponding to the first time information.

[0291] Here, the 19th threshold value may represent, for example, an observation ratio threshold value Rbf, and its possible value range may be, for example, 60% to 90%. Here, the possible value range of the length Tobs of the sliding observation time window corresponding to the continuous observation Tobs sliding window may be, for example, 50 to 100 ms, or may be a period corresponding to Nbf consecutive effective wide and narrow beam effect recognition results, where Nbf is the number of sliding observations, and its possible value range may be, for example, 20 to 50.

[0292] It should be noted that the threshold values ​​in the embodiments of the present disclosure do not refer to specific fixed threshold values, and may be adjusted accordingly based on, for example, a threshold modification command or may be changed accordingly based on a network specification, but the embodiments of the present disclosure are not limited thereto.

[0293] In some embodiments or related embodiments, a cell currently serving a communication device is obtained, and downlink beamforming support information corresponding to the current network standard of the currently serving cell is determined in response to network standard information and a downlink beamforming decision order corresponding to the currently serving cell, thereby providing a beam sensing mechanism that can determine downlink beamforming support information in response to the network standard information and the downlink beamforming decision order, thereby improving the accuracy of determining the downlink beamforming support information, and if it is determined that downlink dynamic beamforming is supported, can determine a feature recognition result based on a downlink static beam feature set and a downlink dynamic beam feature set, thereby improving the accuracy of determining the feature recognition result and improving the accuracy of determining an acquisition source corresponding to the wireless channel state information, thereby avoiding the wide-and-narrow beam effect problem of low accuracy in obtaining wireless channel state information required for channel estimation, thereby improving the receiving state of the communication device, improving the robustness of downlink receiving performance, and improving the communication quality of the communication device. In addition, the wide and narrow beam effect recognition result can be determined based on at least one threshold information or a preset beam sensing neural network model, and the feature recognition result can be determined in different ways to improve the accuracy of determining the acquisition source.

[0294] 11 is a block diagram of a beam sensing apparatus according to an exemplary embodiment. Referring to FIG. 11, the apparatus 1100 includes: a set acquisition unit 1101 for acquiring a first beam feature set and a second beam feature set associated with a current network standard; and a source determination unit 1102 for selecting 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 predetermined condition, where the first beam feature set is associated with the at least one first parameter and the second beam feature set is associated with the at least one second parameter.

[0295] According to some embodiments, the source determination unit 1102 further obtains a feature recognition result in response to the 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, wherein the feature recognition result indicates 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 satisfy a predetermined condition.

[0296] According to some embodiments, when the source determination unit 1102 obtains a feature recognition result in response to an operation result between at least one first parameter of the first beam feature set and at least one second parameter of the second beam feature set and at least one threshold information, specifically, the source determination unit 1102 obtains a feature recognition result by comparing a difference result and / or a ratio result between at least one first parameter of the first beam feature set and at least one second parameter of the second beam feature set with at least one threshold information.

[0297] According to some embodiments, when the source determination unit 1102 obtains a feature recognition result in response to the 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, specifically, in response to a first difference value between any one second parameter and any one first parameter being greater than a first threshold, the first threshold represents a relative SINR index threshold, and the predetermined result indicates that at least one first parameter of the first beam feature set and at least one second parameter of the second beam feature set satisfy a predetermined condition.

[0298] According to some embodiments, the at least one first parameter comprises at least one of a cell-specific reference signal-to-interference-plus-noise ratio (CRS-SINR), a primary synchronization signal-to-interference-plus-noise ratio (PSS-SINR), and a secondary synchronization signal-to-interference-plus-noise ratio (SSS-SINR), and the at least one second parameter comprises a physical downlink shared channel-to-interference-plus-noise ratio (PDSCH-SINR), or the at least one first parameter comprises at least one of a time-frequency tracking reference signal channel state information-to-signal-to-interference-plus-noise ratio (TRS CSI-SINR) and a synchronization signal-to-signal-to-interference-plus-noise ratio (SS-SINR), and the at least one second parameter comprises at least one of a physical downlink shared channel-to-interference-plus-noise ratio (PDSCH-SINR), and a physical downlink control channel-to-signal-to-interference-plus-noise ratio (PDCCH-SINR).

[0299] According to some embodiments, when the source determination unit 1102 obtains a feature recognition result in response to an operation result between at least one first parameter of the first beam feature set and at least one second parameter of the second beam feature set and at least one threshold information, specifically, in response to a first ratio value between any one first parameter and any one second parameter being greater than a second threshold, the second threshold represents a relative maximum delay extension indicator threshold, and the predetermined result indicates that at least one first parameter of the first beam feature set and at least one second parameter of the second beam feature set satisfy a predetermined condition.

[0300] According to some embodiments, the at least one first parameter comprises a cell-specific reference signal - maximum delay extension (CRS-Tmax) and the at least one second parameter comprises a physical downlink shared channel - maximum delay extension (PDSCH-Tmax), or the at least one first parameter comprises a time-frequency tracking reference signal - maximum delay extension (TRS-Tmax) and the at least one second parameter comprises at least one of a physical downlink shared channel - maximum delay extension (PDSCH-Tmax) and a physical downlink control channel - maximum delay extension (PDCCH-Tmax).

[0301] According to some embodiments, when the source determination unit 1102 obtains a feature recognition result in response to the 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, specifically, in response to a second ratio value between any one first parameter and any one second parameter being greater than a third threshold, the source determination unit 1102 determines that the feature recognition result is a predetermined result, where the third threshold represents a relative root mean square delay extension index threshold, and the predetermined result indicates that at least one first parameter of the first beam feature set and at least one second parameter of the second beam feature set satisfy a predetermined condition.

[0302] According to some embodiments, the at least one first parameter comprises a cell-specific reference signal—root mean square delay extension (CRS-Trms) and the at least one second parameter comprises a physical downlink shared channel—root mean square delay extension (PDSCH-Trms), or the at least one first parameter comprises a time-frequency tracking reference signal—root mean square delay extension (TRS-Trms) and the at least one second parameter comprises at least one of a physical downlink shared channel—root mean square delay extension (PDSCH-Trms) and a physical downlink control channel—root mean square delay extension (PDCCH-Trms).

[0303] According to some embodiments, when the source determination unit 1102 obtains a feature recognition result in response to the 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, specifically, in response to a second difference value between the signal-to-interference-plus-noise ratio (SINR) of any one of the at least one second parameters and the signal-to-interference-plus-noise ratio (SINR) of any one of the at least one first parameters being greater than a fourth threshold, and a third ratio value between the maximum Doppler of any one of the at least one second parameters and the maximum Doppler of any one of the at least one first parameters being less than a fifth threshold, wherein the fourth threshold represents a relative SINR index threshold, and the fifth threshold represents a relative maximum Doppler index threshold, and the predetermined result indicates that 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 satisfy a predetermined condition.

[0304] According to some embodiments, the at least one first parameter comprises at least one of CRS-SINR, PSS-SINR, SSS-SINR, and Cell-Specific Reference Signal - Max Doppler (CRS-Doppler), and the at least one second parameter comprises at least one of PDSCH-SINR and Physical Downlink Shared Channel - Max Doppler (PDSCH-Doppler), or the at least one first parameter comprises at least one of TRS CSI-SINR, SS-SINR, and Time-Frequency Tracking Reference Signal - Max Doppler (TRS-Doppler), and the at least one second parameter comprises at least one of PDSCH-SINR, PDCCH-SINR, Physical Downlink Control Channel - Max Doppler (PDCCH-Doppler), and Physical Downlink Shared Channel - Max Doppler (PDSCH-Doppler).

[0305] According to some embodiments, when the source determination unit 1102 obtains a feature recognition result in response to the 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, specifically, in response to a fourth ratio value between the maximum delay extension (Tmax) of any one of the at least one second parameters and the maximum delay extension (Tmax) of any one of the at least one first parameters being greater than a sixth threshold, and a fifth ratio value between the maximum Doppler (Doppler) of any one of the at least one second parameters and the maximum Doppler (Doppler) of any one of the at least one first parameters being less than a seventh threshold, the sixth threshold represents a relative maximum delay extension index threshold, and the seventh threshold represents a relative maximum Doppler index threshold, and the predetermined result indicates that 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 satisfy a predetermined condition.

[0306] According to some embodiments, 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, or the at least one first parameter comprises at least one of TRS-Tmax and TRS-Doppler, and the at least one second parameter comprises at least one of PDSCH-Tmax, PDCCH-Tmax, PDSCH-Doppler, and PDCCH-Doppler.

[0307] According to some embodiments, the source determination unit 1102 obtains 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, when a sixth ratio value between the maximum root mean square delay extension (Trms) of any one of the at least one second parameters and the maximum root mean square delay extension (Trms) of any one of the at least one first parameters is greater than an eighth threshold, and when a sixth ratio value between the maximum root mean square delay extension (Trms) of any one of the at least one second parameters is greater than an eighth threshold, In response to a seventh ratio value between any one maximum Doppler and any one maximum Doppler of the at least one first parameter being less than a ninth threshold, the feature recognition result is determined to be a predetermined result, wherein the eighth threshold represents a relative maximum root mean square delay extension threshold and the ninth threshold represents a relative maximum Doppler index threshold, and the predetermined result indicates that at least one first parameter of the first beam feature set and at least one second parameter of the second beam feature set satisfy a predetermined condition.

[0308] According to some embodiments, 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, or the at least one first parameter comprises at least one of TRS-Trms and TRS-Doppler, and the at least one second parameter comprises at least one of PDSCH-Trms, PDCCH-Trms, PDSCH-Doppler, and PDCCH-Doppler.

[0309] According to some embodiments, when the source determination unit 1102 obtains a feature recognition result in response to the 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, specifically, in response to the third difference value between the SINR of any one of the at least one second parameters and the SINR of any one of the at least one first parameters being greater than a tenth threshold, and the eighth ratio value between the maximum delay extension (Tmax) of any one of the at least one second parameters and the maximum delay extension (Tmax) of any one of the at least one first parameters being greater than an eleventh threshold, the tenth threshold represents a relative SINR index threshold, the eleventh threshold represents a relative maximum delay extension index threshold, and the predetermined result indicates that 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 satisfy a predetermined condition.

[0310] According to some embodiments, 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, or the at least one first parameter comprises at least one of TRS CSI-SINR, SS-SINR, and TRS-Tmax, and the at least one second parameter comprises at least one of PDSCH-SINR, PDCCH-SINR, PDSCH-Tmax, and PDCCH-Tmax.

[0311] According to some embodiments, when the source determination unit 1102 obtains a feature recognition result in response to the 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, specifically, in response to a fourth difference value between the SINR of any one of the at least one second parameters and the SINR of any one of the at least one first parameters being greater than a twelfth threshold, and a ninth ratio value between the maximum root mean square delay extension (Trms) of any one of the at least one second parameters and the maximum root mean square delay extension (Trms) of any one of the at least one first parameters being greater than a thirteenth threshold, the twelfth threshold representing a relative SINR index threshold, and the thirteenth threshold representing a relative maximum root mean square delay extension, and the predetermined result indicating that 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 satisfy a predetermined condition.

[0312] According to some embodiments, the at least one first parameter comprises at least one of CRS-SINR, PSS-SINR, SSS-SINR, and CRS-Trms, and the at least one second parameter comprises at least one of PDSCH-SINR and PDSCH-Tmax, or the at least one first parameter comprises at least one of TRS CSI-SINR, SS-SINR, and TRS-Trms, and the at least one second parameter comprises at least one of PDSCH-SINR, PDCCH-SINR, PDSCH-Trms, and PDCCH-Trms.

[0313] According to some embodiments, when the source determination unit 1102 obtains the feature recognition result in response to the 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, specifically, a fifth difference value between the SINR of any one of the at least one second parameters and the SINR of any one of the at least one first parameters is greater than a fourteenth threshold, a tenth ratio value between the maximum delay extension (Tmax) of any one of the at least one second parameters and the maximum delay extension (Tmax) of any one of the at least one first parameters is greater than a fifteenth threshold, and In response to an 11th ratio value between the maximum root mean square delay extension (Trms) of any one of the at least one second parameter and the maximum root mean square delay extension (Trms) of any one of the at least one first parameter being greater than a 16th threshold, determining that the feature recognition result is a predetermined result, wherein the 14th threshold represents a relative SINR index threshold, the 15th threshold represents a relative maximum delay extension index threshold, and the 16th threshold represents a relative maximum root mean square delay extension, and the predetermined result indicates that at least one first parameter of the first beam feature set and at least one second parameter of the second beam feature set satisfy a predetermined condition.

[0314] According to some embodiments, 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 PDSCH-SINR, PDSCH-Tmax, and PDSCH-Trms, or the at least one first parameter comprises at least one of TRS CSI-SINR, SS-SINR, TRS-Tmax, and TRS-Trms, and the at least one second parameter comprises at least one of PDSCH-SINR, PDCCH-SINR, PDSCH-Tmax, PDCCH-Tmax, PDSCH-Trms, and PDCCH-Trms.

[0315] According to some embodiments, the source determination unit 1102 further inputs 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 to obtain a feature recognition result output by the beam sensing neural network model, wherein the feature recognition result indicates 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 satisfy a preset condition.

[0316] According to some embodiments, when the source determination unit 1102 inputs 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 to obtain the feature recognition result output by the beam sensing neural network model, specifically, inputs 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 to obtain a vector corresponding to the at least one first parameter and the at least one second parameter, and performs recognition processing on the vector using an activation function of the preset beam sensing neural network model to obtain the feature recognition result output by the beam sensing neural network model.

[0317] According to some embodiments, when the source determination unit 1102 selects the first beam feature set or the second beam feature set as the acquisition source of the wireless channel state information, specifically, 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 not being reset or released, it determines that the acquisition source corresponding to the wireless channel state information in the second time information is a dynamic beam feature acquisition source, where the first time information is the time of any one of the current periods 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 a result requirement that all the feature recognition results corresponding to the first time information are preset results, or a result requirement that a first number of the preset results among the feature recognition results corresponding to the first time information satisfy a number requirement.

[0318] According to some embodiments, when the source determination unit 1102 selects the first beam feature set or the second beam feature set as the acquisition source of the wireless channel state information, specifically, in response to the feature recognition result corresponding to the first time information satisfying the second result requirement, it determines that the acquisition source corresponding to the wireless channel state information in the second time information is a static beam feature acquisition source, where the first time information is the time of any one of the current periods in the continuous observation preset period, and the second result requirement includes a result requirement that all the feature recognition results corresponding to the first time information are not preset results, or a result requirement that a first number of the preset results among the feature recognition results corresponding to the first time information do not satisfy a number requirement.

[0319] According to some embodiments, when the source determination unit 1102 selects the first beam feature set or the second beam feature set as the acquisition source of the wireless channel state information, specifically, 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 not being reset or released, it determines that the acquisition source corresponding to the wireless channel state information in the second time information is a dynamic beam feature acquisition source, where the first time information is the time of any one of the current periods in the continuous observation sliding period, the second time information is the time information before the next feature recognition result is acquired, and the first result requirement includes a result requirement that all the feature recognition results corresponding to the first time information are preset results, or a result requirement that a second number of the preset results among the feature recognition results corresponding to the first time information satisfy a number requirement.

[0320] According to some embodiments, when the source determination unit 1102 selects the first beam feature set or the second beam feature set as the acquisition source of the wireless channel state information, specifically, in response to the feature recognition result corresponding to the first time information satisfying the second result requirement, it determines that the acquisition source corresponding to the wireless channel state information in the second time information is a static beam feature acquisition source, where the first time information is any one time 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 acquired, 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 the preset results among the feature recognition results corresponding to the first time information does not satisfy the number requirement, and observes updated information corresponding to the first time information before the feature recognition result corresponding to the second time information is acquired, and re-determines the acquisition source corresponding to the wireless channel state information in the second time information using the updated first time information as the first time information.

[0321] According to some embodiments, wherein the first beam feature set includes a downlink static beam feature set and the second beam feature set includes a downlink dynamic beam feature set.

[0322] 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, and when the set acquisition unit 1101 acquires the first beam feature set and the second beam feature set associated with the current network standard, specifically, performs feature extraction on synchronization signals and / or reference signals of a broadband wireless communication system with downlink beamforming enabled to acquire the downlink static beam feature set associated with the current network standard, and performs feature extraction on demodulation reference signals of a broadband wireless communication system with downlink dynamic beamforming enabled to acquire the downlink dynamic beam feature set associated with the current network standard.

[0323] According to some embodiments, the set acquisition unit 1101 further acquires a cell currently serving the communication device, and determines downlink beamforming support information corresponding to the current network standard of the currently serving cell in response to the network standard information and downlink beamforming decision order corresponding to the currently serving cell.

[0324] According to some embodiments, when the set acquisition unit 1101 determines downlink beamforming support information corresponding to the current network standard of the currently serving cell in response to the network standard information corresponding to the currently serving cell and the downlink beamforming decision order, specifically, acquires the network standard information corresponding to the currently serving cell, and determines that the communication device is in a radio resource control connected state in response to the network standard information corresponding to the currently serving cell being a first network standard; acquires first scenario information corresponding to the currently serving cell in response to the dedicated configuration signaling indicating that the communication device is in a preset transmission mode; and determines that the downlink beamforming support information corresponding to the first network standard is that the first network standard supports downlink dynamic beamforming in response to the first scenario information being preset scenario information.

[0325] According to some embodiments, when the set acquisition unit 1101 determines downlink beamforming support information corresponding to the current network standard of the currently serving cell in response to the network standard information corresponding to the currently serving cell and the downlink beamforming decision order, specifically, acquires the network standard information corresponding to the currently serving cell, and determines that the communication device is in a radio resource control connected state in response to the network standard information corresponding to the currently serving cell being a first network standard, and determines that the downlink beamforming support information corresponding to the first network standard is that the first network standard does not support downlink dynamic beamforming in response to the dedicated configuration signaling indicating that the communication device is not in a preset transmission mode or the first scenario information is not preset scenario information.

[0326] According to some embodiments, when the set acquisition unit 1101 determines downlink beamforming support information corresponding to the current network standard of the currently serving cell in response to the network standard information corresponding to the currently serving cell and the downlink beamforming determination order, specifically, in response to the network standard information corresponding to the currently serving cell not being the first network standard, it determines that the network standard information corresponding to the currently serving cell is the second network standard; and in response to the frequency range information of the currently serving cell being the first frequency range, the communication mode of the currently serving cell being time division duplex, and the second scenario information corresponding to the currently serving cell being preset scenario information, it determines that the downlink beamforming support information corresponding to the second network standard means that the second network standard supports downlink dynamic beamforming.

[0327] According to some embodiments, when the set acquisition unit 1101 determines downlink beamforming support information corresponding to the current network standard of the currently serving cell in response to the network standard information corresponding to the currently serving cell and the downlink beamforming determination order, specifically, in response to the network standard information corresponding to the currently serving cell not being the first network standard, it determines that the network standard information corresponding to the currently serving cell is the second network standard; and in response to the frequency range information corresponding to the currently serving cell not being the first frequency range, or the communication mode of the currently serving cell not being time division duplex, or the second scenario information corresponding to the currently serving cell not being preset scenario information, it determines that the downlink beamforming support information corresponding to the second network standard means that the second network standard does not support downlink dynamic beamforming.

[0328] According to some embodiments, when the set acquisition unit 1101 determines downlink beamforming support information corresponding to the current network standard of the currently serving cell in response to the network standard information corresponding to the currently serving cell and the downlink beamforming determination order, specifically, in response to the network standard information corresponding to the currently serving cell not being the second network standard, it determines whether the network standard information corresponding to the currently serving cell is the third network standard, and in response to determining that the network standard information corresponding to the currently serving cell is the third network standard, it uses a determination method corresponding to the third network standard to determine the downlink beamforming support information corresponding to the current network standard of the currently serving cell.

[0329] According to some embodiments, the set obtaining unit 1101 further re-determines downlink beamforming support information corresponding to the current network standard of the currently serving cell in response to a reconfiguration of the radio resource control signaling occurring in the radio resource control connected state.

[0330] The specific manner in which each module performs the operations of the apparatus in the above embodiment is described in detail in the embodiment associated with the method, and a detailed description thereof will be omitted here.

[0331] In some embodiments or related embodiments, the set acquisition unit acquires a first beam feature set and a second beam feature set associated with a current network standard, and the source determination unit selects the first beam feature set or the second beam feature set as an 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 predetermined condition, where the first beam feature set is associated with the at least one first parameter and the second beam feature set is associated with the at least one second parameter. This provides a beam sensing mechanism that can determine an acquisition source corresponding to the wireless channel state information based on 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 satisfy the predetermined condition, thereby improving the accuracy of determining the acquisition source corresponding to the wireless channel state information, avoiding a 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, improving the accuracy of acquiring the wireless channel state information, and improving the reception state of the communication device and the communication quality of the communication device.

[0332] 12 illustrates a schematic block diagram of an exemplary communication device 1200 for implementing embodiments of the present disclosure. 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 may also represent various forms of mobile devices, such as personal digital processors, mobile phones, smartphones, wearable communication devices, and other similar computing devices. The components, their connections and relationships, and their functions illustrated herein are merely examples and are not limitations on the description herein and / or the implementation of the present application as claimed.

[0333] 12, a communications device 1200 includes a computing unit 1201 that can perform various appropriate operations and processes based on a computer program stored in a read-only memory (ROM) 1202 or loaded from a storage unit 1208 into a random access memory (RAM) 1203. The RAM 1203 can contain various programs and data necessary for the operation of the communications device 1200. 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.

[0334] Several components in communication device 1200 are connected to I / O interface 1205, including input unit 1206 such as a keyboard, mouse, etc., output unit 1207 such as various types of monitors, speakers, etc., storage unit 1208 such as a magnetic disk, optical disk, etc., and communication unit 1209 such as a network card, modem, wireless communication transceiver, etc. The communication unit 1209 allows communication device 1200 to exchange information / data with other devices via a computer network such as the Internet and / or various telecom networks.

[0335] The computing unit 1201 may be various general-purpose and / or special-purpose processing components having 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), an artificial intelligence (AI) computing chip, various computing units that execute machine learning model algorithms, a digital signal processor (DSP), and any suitable processor, controller, microcontroller, etc. The computing unit 1201 performs each of the methods and processes described above, such as the large-scale model training method. For example, in some embodiments, the large-scale model training method may be implemented as a computer software program tangibly embodied in a machine-readable medium such as the storage unit 1208. In some embodiments, some or all of the computer program may be loaded and / or installed into 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, it may perform one or more steps of the large-scale model training method described above. Alternatively, in other embodiments, the computing unit 1201 may be configured to perform the beam sensing method via any other suitable method (eg, via firmware).

[0336] 13 is a block diagram of a chip according to an exemplary embodiment. The chip 1300 shown in FIG. 13 includes a processor 1301 and an interface 1302. Optionally, the chip 1300 may include a memory 1303. Here, the number of processors 1301 may be one or more, and the number of interfaces 1302 may be multiple.

[0337] Various embodiments of the systems and techniques described herein may be implemented in digital electronic circuitry systems, integrated circuit systems, field programmable gate arrays (FPGAs), application specific integrated circuits (ASICs), application specific standard products (ASSPs), systems on a chip (SOCs), complex programmable logic devices (CPLDs), computer hardware, firmware, software, and / or combinations thereof. These various embodiments may be embodied in one or more computer programs that can be executed and / or interpreted by a programmable system that includes at least one programmable processor, which may be an application specific or general purpose programmable processor, and that can receive data and instructions from, and transmit data and instructions to, a storage system, at least one input device, and at least one output device.

[0338] Program code for carrying out the methods of the present disclosure can 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 apparatus such that, when executed by the processor or controller, the functions / acts specified in the flowcharts and / or block diagrams are performed. The program code may be executed entirely on the machine, partially on the machine, as a stand-alone software package, partially on the machine and partially on a remote machine, or entirely on a remote machine or server.

[0339] In the context of this disclosure, a machine-readable medium may be a tangible medium that contains or can store a program used by or in connection with an instruction execution system, apparatus, or device. 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, apparatus, or device, or a suitable combination of any of the above. More specific examples of machine-readable storage media include one or more line-based electrical connections, 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 a suitable combination of any of the above.

[0340] To provide for user interaction, the systems and techniques described herein can be implemented on a computer having a display device (e.g., a cathode ray tube (CRT) or liquid crystal display (LCD) monitor) for displaying information to a user, as well as a keyboard and pointing device (e.g., a mouse or trackball) through which a user can provide input to the computer. Other types of devices can also provide for user interaction; for example, the feedback provided to the user can be any form of sensing feedback (e.g., visual feedback, auditory feedback, or tactile feedback) and can receive input from the user in any form (including acoustic, speech, or tactile input).

[0341] The systems and techniques described herein can be implemented in a computing system that includes a back-end component (e.g., as a data server), or a computing system that includes a middleware component (e.g., an application server), or a computing system that includes a front-end component (e.g., a user computer having a graphical user interface or a web browser through which a user interacts with embodiments of the systems and techniques described herein), or any combination of such back-end, middleware, and front-end 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.

[0342] The computer system may include a client and a server. The client and server are generally remote from each other and typically interact via a communication network. The relationship between the client and the server is created by computer programs running on corresponding computers and having a client-server relationship with each other. The server may be a cloud server, also called a cloud computing server or cloud host, which is one of the host products of a cloud computing service system that solves the drawbacks of traditional physical hosts and VPS services (abbreviated as "Virtual Private Server" or "VPS"), such as high management difficulty and low business scalability. The server may be a server of a distributed system or a server combined with a blockchain.

[0343] The various types of flows shown above may be used to rearrange, add, or delete steps. For example, the steps described in the present disclosure may be performed in parallel, sequentially, or in a different order, but this specification is not limited thereto as long as the desired results of the technical solution disclosed in the present disclosure can be achieved.

[0344] The above specific embodiments do not limit the scope of protection of the present disclosure. Those skilled in the art may make various modifications, combinations, subcombinations, and substitutions according to design requirements and other factors. Any modifications, equivalent replacements, improvements, etc. made within the spirit and principle of the present disclosure should be included within the scope of protection of the present disclosure.

Claims

1. A beam sensing method, comprising: obtaining a first beam feature set and a second beam feature set associated with a current network standard; and selecting the first beam feature set or the second beam feature set as a source of 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 predetermined condition, wherein the first beam feature set is associated with the at least one first parameter and the second beam feature set is associated with the at least one second parameter. A beam sensing method comprising:

2. The method comprises: and 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, the feature recognition result indicating 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 satisfy the predetermined condition.

2. The beam sensing method according to claim 1, wherein the beam sensing method comprises:

3. The step of 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: comparing a difference result and / or a ratio result of at least one first parameter of the first beam feature set and at least one second parameter of the second beam feature set with at least one threshold information to obtain a feature recognition result; 3. The beam sensing method according to claim 2, wherein the beam sensing method comprises:

4. The step of 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: determining that the feature recognition result is a predetermined result in response to a first difference value between any one second parameter and any one first parameter being greater than a first threshold, the first threshold representing a relative signal-to-interference-plus-noise ratio (SINR) index threshold, the predetermined 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 satisfy the predetermined condition; 3. The beam sensing method according to claim 2, wherein the beam sensing method comprises:

5. the at least one first parameter comprises at least one of a cell-specific reference signal-to-interference-plus-noise ratio (CRS-SINR), a primary synchronization signal-to-interference-plus-noise ratio (PSS-SINR), and a secondary synchronization signal-to-interference-plus-noise ratio (SSS-SINR); and the at least one second parameter comprises a physical downlink shared channel-to-interference-plus-noise ratio (PDSCH-SINR); Alternatively, the at least one first parameter includes at least one of a time-frequency tracking reference signal channel state information-signal to interference plus noise ratio (TRS CSI-SINR) and a synchronization signal-signal to interference plus noise ratio (SS-SINR), and the at least one second parameter includes at least one of a physical downlink shared channel-signal to interference plus noise ratio (PDSCH-SINR) and a physical downlink control channel-signal to interference plus noise ratio (PDCCH-SINR).

5. The beam sensing method according to claim 4, wherein the beam sensing method comprises:

6. The step of 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: determining that the feature recognition result is a predetermined result in response to a first ratio value of any one of the first parameters and any one of the second parameters being greater than a second threshold value, the second threshold value representing a relative maximum delay extension index threshold, the predetermined 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 satisfy the predetermined condition; 3. The beam sensing method according to claim 2, wherein the beam sensing method comprises:

7. the at least one first parameter comprises a cell-specific reference signal—maximum delay extension (CRS-Tmax), and the at least one second parameter comprises a physical downlink shared channel—maximum delay extension (PDSCH-Tmax); Or, the at least one first parameter includes a time-frequency tracking reference signal—maximum delay extension (TRS-Tmax), and the at least one second parameter includes at least one of a physical downlink shared channel—maximum delay extension (PDSCH-Tmax) and a physical downlink control channel—maximum delay extension (PDCCH-Tmax); 7. The beam sensing method according to claim 6, wherein:

8. The step of 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: determining that the feature recognition result is a predetermined result in response to a second ratio value between any one of the first parameters and any one of the second parameters being greater than a third threshold value, the third threshold value representing a relative root mean square delay expansion index threshold, the predetermined 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 satisfy the predetermined condition; 3. The beam sensing method according to claim 2, wherein the beam sensing method comprises:

9. the at least one first parameter comprises a cell-specific reference signal—root mean square delay extension (CRS-Trms), and the at least one second parameter comprises a physical downlink shared channel—root mean square delay extension (PDSCH-Trms); Or, the at least one first parameter comprises a time-frequency tracking reference signal—root-mean-square delay extension (TRS-Trms), and the at least one second parameter comprises at least one of a physical downlink shared channel—root-mean-square delay extension (PDSCH-Trms) and a physical downlink control channel—root-mean-square delay extension (PDCCH-Trms); 9. The beam sensing method according to claim 8, wherein the beam sensing method comprises:

10. The step of 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: determining that the feature recognition result is a predetermined result in response to a second difference value between a signal-to-interference-plus-noise ratio (SINR) of any one of the at least one second parameters and a signal-to-interference-plus-noise ratio (SINR) of any one of the at least one first parameters being greater than a fourth threshold value and a third ratio value between a maximum Doppler of any one of the at least one second parameters and a maximum Doppler of any one of the at least one first parameters being less than a fifth threshold value, wherein the fourth threshold value represents a relative SINR index threshold and the fifth threshold value represents a relative maximum Doppler index threshold value, and the predetermined result indicates that at least one first parameter of the first beam feature set and at least one second parameter of the second beam feature set satisfy the predetermined condition.

3. The beam sensing method according to claim 2, wherein the beam sensing method comprises:

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

12. The step of 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: determining that the feature recognition result is a predetermined result in response to a fourth ratio value between a maximum delay extension (Tmax) of any one of the at least one second parameters and a maximum delay extension (Tmax) of any one of the at least one first parameters being greater than a sixth threshold value and a fifth ratio value between a maximum Doppler (Doppler) of any one of the at least one second parameters and a maximum Doppler (Doppler) of any one of the at least one first parameters being less than a seventh threshold value, wherein the sixth threshold value represents a relative maximum delay extension index threshold and the seventh threshold value represents a relative maximum Doppler index threshold value, and the predetermined result indicates that at least one first parameter of the first beam feature set and at least one second parameter of the second beam feature set satisfy the predetermined condition; 3. The beam sensing method according to claim 2, wherein the beam sensing method comprises:

13. the at least one first parameter includes at least one of a CRS-Tmax and a cell-specific reference signal - maximum Doppler (CRS-Doppler), and the at least one second parameter includes at least one of a PDSCH-Doppler and a PDCCH-Tmax; Or, the at least one first parameter includes at least one of TRS-Tmax and TRS-Doppler, and the at least one second parameter includes at least one of PDSCH-Tmax, PDCCH-Tmax, PDSCH-Doppler, and PDCCH-Doppler; The beam sensing method according to claim 12,

14. The step of 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: determining that the feature recognition result is a predetermined result in response to a sixth ratio value between the maximum root mean square delay extension (Trms) of any one of the at least one second parameters and the maximum root mean square delay extension (Trms) of any one of the at least one first parameters being greater than an eighth threshold value and a seventh ratio value between the maximum Doppler (Doppler) of any one of the at least one second parameters and the maximum Doppler (Doppler) of any one of the at least one first parameters being less than a ninth threshold value, wherein the eighth threshold value represents a relative maximum root mean square delay extension threshold and the ninth threshold value represents a relative maximum Doppler index threshold, and the predetermined result indicates that at least one first parameter of the first beam feature set and at least one second parameter of the second beam feature set satisfy the predetermined condition; 3. The beam sensing method according to claim 2, wherein the beam sensing method comprises:

15. the at least one first parameter includes at least one of CRS-Trms and CRS-Doppler, and the at least one second parameter includes at least one of PDSCH-Trms and PDSCH-Doppler; Or, the at least one first parameter includes at least one of TRS-Trms and TRS-Doppler, and the at least one second parameter includes at least one of PDSCH-Trms, PDCCH-Trms, PDSCH-Doppler, and PDCCH-Doppler; 15. The beam sensing method according to claim 14,

16. The step of 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: determining that the feature recognition result is a predetermined result in response to a third difference value between the SINR of any one of the at least one second parameters and the SINR of any one of the at least one first parameters being greater than a tenth threshold and an eighth ratio value between a maximum delay extension (Tmax) of any one of the at least one second parameters and a maximum delay extension (Tmax) of any one of the at least one first parameters being greater than an eleventh threshold, wherein the tenth threshold represents a relative SINR index threshold and the eleventh threshold represents a relative maximum delay extension index threshold, and the predetermined result indicates that at least one first parameter of the first beam feature set and at least one second parameter of the second beam feature set satisfy the predetermined condition.

3. The beam sensing method according to claim 2, wherein the beam sensing method comprises:

17. the at least one first parameter includes at least one of CRS-SINR, PSS-SINR, SSS-SINR, and CRS-Tmax, and the at least one second parameter includes at least one of PDSCH-SINR and PDSCH-Tmax; Or, the at least one first parameter includes at least one of a TRS CSI-SINR, a SS-SINR, and a TRS-Tmax, and the at least one second parameter includes at least one of a PDSCH-SINR, a PDCCH-SINR, a PDSCH-Tmax, and a PDCCH-Tmax; 17. The beam sensing method according to claim 16,

18. The step of 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: determining that the feature recognition result is a predetermined result in response to a fourth difference value between the SINR of any one of the at least one second parameters and the SINR of any one of the at least one first parameters being greater than a twelfth threshold and a ninth ratio value between a maximum root mean square delay extension (Trms) of any one of the at least one second parameters and a maximum root mean square delay extension (Trms) of any one of the at least one first parameters being greater than a thirteenth threshold, wherein the twelfth threshold represents a relative SINR index threshold and the thirteenth threshold represents a relative maximum root mean square delay extension, and the predetermined result indicates that at least one first parameter of the first beam feature set and at least one second parameter of the second beam feature set satisfy the predetermined condition.

3. The beam sensing method according to claim 2, wherein the beam sensing method comprises:

19. the at least one first parameter includes at least one of CRS-SINR, PSS-SINR, SSS-SINR, and CRS-Trms, and the at least one second parameter includes at least one of PDSCH-SINR and PDSCH-Tmax; Or, the at least one first parameter includes at least one of a TRS CSI-SINR, a SS-SINR, and a TRS-Trms, and the at least one second parameter includes at least one of a PDSCH-SINR, a PDCCH-SINR, a PDSCH-Trms, and a PDCCH-Trms; 20. The beam sensing method according to claim 18, wherein:

20. The step of 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: a fifth difference value between the SINR of any one of the at least one second parameters and the SINR of any one of the at least one first parameters is greater than a fourteenth threshold, a tenth ratio value between the maximum delay extension (Tmax) of any one of the at least one second parameters and the maximum delay extension (Tmax) of any one of the at least one first parameters is greater than a fifteenth threshold, and a tenth ratio value between the maximum root mean square delay extension (Trms) of any one of the at least one second parameters and the maximum root mean square delay extension (Trms) of any one of the at least one first parameters is greater than a fifteenth threshold. determining that the feature recognition result is a predetermined result in response to an eleventh ratio value of the first beam feature set and the square root delay extension (Trms) being greater than a sixteenth threshold, the fourteenth threshold representing a relative SINR index threshold, the fifteenth threshold representing a relative maximum delay extension index threshold, and the sixteenth threshold representing a relative maximum root mean square delay extension, the predetermined 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 satisfy the predetermined condition.

3. The beam sensing method according to claim 2, wherein the beam sensing method comprises:

21. the at least one first parameter includes at least one of CRS-SINR, PSS-SINR, SSS-SINR, CRS-Tmax, and CRS-Trms, and the at least one second parameter includes at least one of PDSCH-SINR, PDSCH-Tmax, and PDSCH-Trms; Or, the at least one first parameter includes at least one of TRS CSI-SINR, SS-SINR, TRS-Tmax, and TRS-Trms, and the at least one second parameter includes at least one of PDSCH-SINR, PDCCH-SINR, PDSCH-Tmax, PDCCH-Tmax, PDSCH-Trms, and PDCCH-Trms; 21. The beam sensing method according to claim 20,

22. The method comprises: and further comprising: 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 to obtain the feature recognition result output by the beam sensing neural network model, the feature recognition result indicating 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 satisfy the preset condition.

2. The beam sensing method according to claim 1, wherein the beam sensing method comprises:

23. 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 to obtain the feature recognition result output by the beam sensing neural network model, 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 to obtain a vector corresponding to the at least one first parameter and the at least one second parameter; performing a recognition process on the vector using the preset activation function of the beam sensing neural network model to obtain the feature recognition result output by the beam sensing neural network model; 23. The beam sensing method according to claim 22,

24. The step of selecting the first beam feature set or the second beam feature set as a source of wireless channel state information includes: determining that an acquisition source corresponding to radio channel state information in second time information is a dynamic beam feature acquisition source in response to a feature recognition result corresponding to first time information satisfying a first result requirement and a radio resource control connection of the communication device not being reset or released, wherein the first time information is a time of any one of a current period in a continuous observation preset period, the second time information is a next preset period adjacent to the current period, and the first result requirement includes a result requirement that all feature recognition results corresponding to the first time information are preset results, or a result requirement that a first number of preset results among the feature recognition results corresponding to the first time information satisfy a number requirement.

3. The beam sensing method according to claim 2, wherein the beam sensing method comprises:

25. The step of selecting the first beam feature set or the second beam feature set as a source of wireless channel state information includes: determining that the acquisition source corresponding to the radio channel state information in the second time information is a static beam feature acquisition source in response to the feature recognition result corresponding to the first time information satisfying a second result requirement, wherein the first time information is a time of any one of the current periods in a continuous observation preset period, and the second result requirement includes a result requirement that all of the feature recognition results corresponding to the first time information are not preset results, or a result requirement that a first number of the preset results among the feature recognition results corresponding to the first time information do not satisfy a number requirement; 3. The beam sensing method according to claim 2, wherein the beam sensing method comprises:

26. The step of selecting the first beam feature set or the second beam feature set as a source of wireless channel state information includes: determining that an acquisition source corresponding to radio channel state information in second time information is a dynamic beam feature acquisition source in response to a feature recognition result corresponding to first time information satisfying a first result requirement and a radio resource control connection of the communication device not being reset or released, wherein the first time information is a time of any one of a current period in a continuous observation sliding period, the second time information is time information before a next feature recognition result is acquired, and the first result requirement includes a result requirement that all feature recognition results corresponding to the first time information are preset results, or a result requirement that a second number of preset results among the feature recognition results corresponding to the first time information satisfy a number requirement; 3. The beam sensing method according to claim 2, wherein the beam sensing method comprises:

27. The step of selecting the first beam feature set or the second beam feature set as a source of wireless channel state information includes: a step of determining that the acquisition source corresponding to the wireless channel state information in the second time information is a static beam feature acquisition source in response to the feature recognition result corresponding to the first time information satisfying a second result requirement, wherein the first time information is any one time of a current period in a continuous observation sliding period, the second time information is time information before the next feature recognition result is acquired, and the second result requirement includes a result requirement that all feature recognition results corresponding to the first time information are not preset results, or a result requirement that a second number of preset results among the feature recognition results corresponding to the first time information do not satisfy a number requirement; Observing updated information corresponding to the first time information before the feature recognition result corresponding to the second time information is acquired, and re-determining an acquisition source corresponding to the wireless channel state information in the second time information using the updated first time information as the first time information.

3. The beam sensing method according to claim 2, wherein the beam sensing method comprises:

28. 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.

25. The beam sensing method according to claim 24,

29. the first beam feature set includes a downlink static beam feature set, and the second beam feature set includes a downlink dynamic beam feature set; The step of obtaining a first beam feature set and a second beam feature set associated with the current network standard comprises: performing feature extraction on synchronization and / or reference signals of a downlink beamforming enabled broadband wireless communication system to obtain a downlink static beam feature set associated with the current network standard; performing feature extraction on a demodulation reference signal of a downlink dynamic beamforming enabled broadband wireless communication system to obtain a downlink dynamic beam feature set associated with the current network standard; 2. The beam sensing method according to claim 1, wherein the beam sensing method comprises:

30. The method comprises: obtaining a currently serving cell for a communication device; and determining downlink beamforming support information corresponding to a current network standard of the currently serving cell in response to the network standard information corresponding to the currently serving cell and a downlink beamforming decision order.

2. The beam sensing method according to claim 1, wherein the beam sensing method comprises:

31. The step of determining downlink beamforming support information corresponding to the current network standard of the currently serving cell in response to the network standard information and the downlink beamforming decision order corresponding to the currently serving cell includes: obtaining network standard information corresponding to the currently serving cell; determining that the communication device is in a radio resource control connected state in response to the network standard information corresponding to the currently serving cell being a first network standard; In response to the dedicated configuration signaling indicating that the communication device is in a preset transmission mode, acquiring first scenario information corresponding to the currently serving cell; In response to the first scenario information being preset scenario information, determining that downlink beamforming support information corresponding to the first network standard indicates that the first network standard supports downlink dynamic beamforming.

31. The beam sensing method according to claim 30,

32. The step of determining downlink beamforming support information corresponding to the current network standard of the currently serving cell in response to the network standard information and the downlink beamforming decision order corresponding to the currently serving cell includes: obtaining network standard information corresponding to the currently serving cell; determining that the communication device is in a radio resource control connected state in response to the network standard information corresponding to the currently serving cell being a first network standard; In response to the dedicated configuration signaling indicating that the communication device is not in a preset transmission mode or the first scenario information being not preset scenario information, determining that downlink beamforming support information corresponding to the first network standard is that the first network standard does not support downlink dynamic beamforming.

31. The beam sensing method according to claim 30,

33. The step of determining downlink beamforming support information corresponding to the current network standard of the currently serving cell in response to the network standard information and the downlink beamforming decision order corresponding to the currently serving cell includes: determining, in response to the network standard information corresponding to the currently serving cell not being the first network standard, that the network standard information corresponding to the currently serving cell is a second network standard; determining, in response to the frequency range information of the currently serving cell being a first frequency range, the communication mode of the currently serving cell being time division duplex, and the second scenario information corresponding to the currently serving cell being preset scenario information, that downlink beamforming support information corresponding to the second network standard indicates that the second network standard supports downlink dynamic beamforming; 30. The beam sensing method according to claim 29,

34. The step of determining downlink beamforming support information corresponding to the current network standard of the currently serving cell in response to the network standard information and the downlink beamforming decision order corresponding to the currently serving cell includes: determining, in response to the network standard information corresponding to the currently serving cell not being the first network standard, that the network standard information corresponding to the currently serving cell is a second network standard; determining, in response to the frequency range information corresponding to the currently serving cell not being a first frequency range, or the communication method of the currently serving cell not being time division duplex, or the second scenario information corresponding to the currently serving cell not being preset scenario information, that downlink beamforming support information corresponding to the second network standard indicates that the second network standard does not support downlink dynamic beamforming; 31. The beam sensing method according to claim 30,

35. The step of determining downlink beamforming support information corresponding to the current network standard of the currently serving cell in response to the network standard information and the downlink beamforming decision order corresponding to the currently serving cell includes: determining whether the network standard information corresponding to the currently serving cell is a third network standard in response to the network standard information corresponding to the currently serving cell not being a second network standard; In response to determining that the network standard information corresponding to the currently serving cell is the third network standard, determining downlink beamforming support information corresponding to the current network standard of the currently serving cell using a determination method corresponding to the third network standard.

31. The beam sensing method according to claim 30,

36. The method comprises: and further comprising the step of re-determining downlink beamforming support information corresponding to a current network standard of the currently serving cell in response to a reset of radio resource control signaling occurring in the radio resource control connected state.

33. The beam sensing method of claim 32.

37. A beam sensing device, a set acquisition unit for acquiring a first beam feature set and a second beam feature set associated with a current network standard; a source determination unit for selecting 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 predetermined condition, wherein the first beam feature set is associated with the at least one first parameter and the second beam feature set is associated with the at least one second parameter. A beam sensing device characterized by:

38. 1. A communication device, comprising: a processor; a memory for storing instructions executable by said processor; The processor is configured to execute the instructions to implement the method according to any one of claims 1 to 36. Communication devices.

39. A storage medium, The instructions on the storage medium, when executed by a processor of a communications device, cause the communications device to perform a method according to any one of claims 1 to 36. A storage medium characterized by:

40. A chip, a processor and an interface, the processor reading instructions to execute the method according to any one of claims 1 to 36; A chip characterized by:

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