Electronic device and method for wireless communication, and computer readable storage medium

Abstract

The invention relates to an electronic device and method for wireless communication and a computer readable storage medium. The electronic equipment for wireless communication comprises a processing circuit, and the processing circuit is configured to perform beam measurement with user equipment within the service range of the electronic equipment based on a plurality of measurement beams with predetermined intervals so as to obtain measurement results for the plurality of measurement beams, and obtaining, via a prediction model for predicting a beam pair to be used for communication between the electronic device and the user equipment, a predicted beam in the predicted beam pair predicted by the prediction model based on the measurement result, the predicted beam being indicated by a relative positional relationship with a specific measurement beam in the plurality of measurement beams.

Description

Technical Field

[0001] The present disclosure relates to the field of wireless communication technology, and in particular to electronic devices and methods for wireless communication, and more particularly to electronic devices and methods for wireless communication related to beam prediction. Background Art

[0002] In order to overcome the huge path loss in millimeter wave or higher frequency band communications, a large-scale antenna array is generally used at the transceiver end and assisted by beamforming technology. By adjusting the phase of the antenna array, beamforming technology enables the antenna to send or receive beams in a direction, thereby obtaining beamforming gain.

[0003] Generally, there are many orthogonal beams available for transmitters and receivers. Therefore, it is a difficult search problem to find the optimal beam pair in the Cartesian product set of all transmit beams and receive beams. In the current NR (New Radio) beam management scheme, the dependency between wide beam and narrow beam gain is utilized, and a hierarchical beam search scheme is adopted. The scheme consists of three stages. That is, the beam measurement overhead in the traditional beam management method is large, and a total of three stages of multiple measurements are required. Figure 1 is a schematic diagram showing the first stage of NR beam scanning. Figure 1 As shown in the figure, in the first stage, the base station uses a wide beam for initial beam scanning, and the user adopts a wide beam for reception. The traditional layered beam scanning method is very sensitive to noise. If there is a deviation in the wide beam measurement in the first stage, the overall performance will be seriously affected. Figure 2 is a schematic diagram showing the second stage of NR beam scanning. Figure 2 As shown, in the second stage, the base station selects a narrow beam to perform fine-tuning beam scanning according to a channel state information reference signal (CSI-RS), and the user still uses a wide beam for reception. Figure 3 is a schematic diagram showing the third stage of NR beam scanning. Figure 3 As shown in FIG. 1 , in the third stage, the base station uses the adjusted narrow beam as the transmit beam, and the user selects the narrow beam according to the CSI-RS signal to perform fine-tuning beam scanning to determine the final user receiving beam. Under this scheme, a total of N w +N n +N Rx The beam scan is N w is the number of base station wide beams, N r is the number of narrow beams under each wide beam of the base station, N Rx is the number of narrow beams for the user, which results in a larger beam measurement overhead.

[0004] With the development of artificial intelligence (AI) technology, a technology that uses deep learning methods to solve the beam prediction problem has emerged. The main method is to measure the reference signal received power (RSRP) information of certain selected beam pairs, and use the powerful fitting ability of deep learning to predict the RSRP information of other beam pairs or directly predict the optimal beam. In general, using deep learning methods, the prediction of the optimal beam can be completed by measuring the RSRP of very few K groups of beam pairs, which greatly reduces the beam measurement overhead compared to the NR beam management solution.

[0005] Existing artificial intelligence prediction schemes consider more single transmit or receive beam prediction problems. In traditional beam management schemes or single beam prediction schemes, the measurement beam can be configured arbitrarily, and the feedback of the measurement results only needs to indicate the optimal measurement beam according to the resource block of the measurement beam. The difficulty of the beam pair prediction problem where the model is deployed at a single base station (or user) end is that in the artificial intelligence-based beam pair prediction method, the input of the artificial intelligence model includes not only the RSRP of the measurement beam, but also the relative relationship between the measurement beams. If the configuration modules of the model and the measurement beam are not on the same side, communication between the two is required to reach a consensus on the relative relationship of the measurement beams. Therefore, the configuration of the measurement beam in the traditional beam management scheme needs to be adjusted. In addition, the optimal prediction beam output by the model is not necessarily included in the measurement beam. Therefore, the method of indicating through the resource block of the measurement beam in traditional beam management also needs to be adjusted. Summary of the invention

[0006] A brief overview of the present invention is provided below in order to provide a basic understanding of certain aspects of the present invention. It should be understood that this overview is not an exhaustive overview of the present invention. It is not intended to identify key or important parts of the present invention, nor is it intended to limit the scope of the present invention. Its purpose is merely to present certain concepts in a simplified form as a prelude to a more detailed description discussed later.

[0007] According to one aspect of the present disclosure, there is provided an electronic device for wireless communication, comprising a processing circuit, the processing circuit being configured to: perform beam measurement with a user device within a service range of the electronic device based on a plurality of measurement beams having a predetermined interval to obtain measurement results for the plurality of measurement beams, and obtain a predicted beam in a predicted beam pair predicted by the prediction model based on the measurement results via a prediction model for predicting a beam pair to be used for communication between the electronic device and the user device, wherein the predicted beam is indicated by a relative positional relationship with a specific measurement beam in the plurality of measurement beams. According to an embodiment of the present disclosure, the prediction model is enabled to clearly understand the relative relationship between the measurement beams, and in addition, the predicted beam can be correctly indicated even if the predicted beam is not in the set of the plurality of measurement beams.

[0008] According to one aspect of the present disclosure, there is provided an electronic device for wireless communication, comprising a processing circuit, the processing circuit being configured to: perform beam measurement based on a plurality of measurement beams with a predetermined interval with a network side device providing services for the electronic device to obtain measurement results for the plurality of measurement beams, and obtain a predicted beam in a predicted beam pair predicted by the prediction model based on the measurement results via a prediction model for predicting a beam pair to be used for communication between the electronic device and the network side device, wherein the predicted beam is indicated by a relative positional relationship with a specific measurement beam in the plurality of measurement beams. According to an embodiment of the present disclosure, the prediction model is enabled to clearly understand the relative relationship between the measurement beams, and in addition, the predicted beam can be correctly indicated even if the predicted beam is not in the set of the plurality of measurement beams.

[0009] According to one aspect of the present disclosure, a method for wireless communication is provided, comprising: performing beam measurement with a user device within a service range of an electronic device based on multiple measurement beams with predetermined intervals to obtain measurement results for the multiple measurement beams, and obtaining, via a prediction model for predicting a beam pair to be used for communication between the electronic device and the user device, a predicted beam in a predicted beam pair predicted by the prediction model based on the measurement results, wherein the predicted beam is indicated by a relative position relationship with a specific measurement beam in the multiple measurement beams.

[0010] According to one aspect of the present disclosure, a method for wireless communication is provided, comprising: performing beam measurement based on multiple measurement beams with a predetermined interval with a network side device providing services for an electronic device to obtain measurement results for the multiple measurement beams, and obtaining, via a prediction model for predicting a beam pair to be used for communication between the electronic device and the network side device, a predicted beam in a predicted beam pair predicted by the prediction model based on the measurement results, wherein the predicted beam is indicated by a relative position relationship with a specific measurement beam in the multiple measurement beams.

[0011] According to other aspects of the present invention, there are also provided computer program codes and computer program products for implementing the above method for wireless communication, and a computer-readable storage medium having the computer program codes for implementing the above method for wireless communication recorded thereon. BRIEF DESCRIPTION OF THE DRAWINGS

[0012] In order to further illustrate the above and other advantages and features of the present invention, the specific embodiments of the present invention are further described in detail below in conjunction with the accompanying drawings. The accompanying drawings together with the following detailed description are included in this specification and form a part of this specification. Elements with the same function and structure are represented by the same reference numerals. It should be understood that these drawings only describe typical examples of the present invention and should not be regarded as limiting the scope of the present invention. In the drawings:

[0013] Figure 1 is a schematic diagram showing the first stage of NR beam scanning;

[0014] Figure 2 is a schematic diagram showing the second stage of NR beam scanning;

[0015] Figure 3 is a schematic diagram showing the third stage of NR beam scanning;

[0016] Figure 4 A functional module block diagram of an electronic device for wireless communication according to an embodiment of the present disclosure is shown;

[0017] Figure 5 is a schematic diagram showing a beam measurement configuration based on a beam ID according to an embodiment of the present disclosure;

[0018] Figure 6 is a schematic diagram showing a beam measurement configuration based on beam angle according to an embodiment of the present disclosure;

[0019] Figure 7 is a schematic diagram showing a beam measurement configuration supporting wide beams and narrow beams according to an embodiment of the present disclosure;

[0020] Figure 8 is a schematic diagram showing a prediction model based on a neural network according to an embodiment of the present disclosure;

[0021] Fig. 9 is a schematic diagram showing the input of a prediction model according to an embodiment of the present disclosure;

[0022] Fig.10 is a schematic diagram showing the output of a prediction model based on a beam ID according to an embodiment of the present disclosure;

[0023] Fig.11 is a schematic diagram showing the output of a prediction model based on beam space angle according to an embodiment of the present disclosure;

[0024] Fig.12 is an example of a flowchart showing information interaction between an electronic device and a user device when a prediction model is deployed on the electronic device side;

[0025] Fig.13is an example of a flowchart showing information interaction between an electronic device and a user device when a prediction model is deployed on the user device side;

[0026] Fig.14 is a schematic diagram showing an O1 scenario of DeepMIMO;

[0027] Fig.15 is a diagram showing simulation results regarding prediction accuracy;

[0028] Fig.16 is a diagram showing simulation results regarding normalized beam gain;

[0029] Fig.17 A functional module block diagram of an electronic device for wireless communication according to another embodiment of the present disclosure is shown;

[0030] Fig.18 A flow chart of a method for wireless communication according to an embodiment of the present disclosure is shown;

[0031] Fig.19 A flow chart of a method for wireless communication according to another embodiment of the present disclosure is shown;

[0032] Fig. 20 is a block diagram showing a first example of a schematic configuration of an eNB or gNB to which the technology of the present disclosure can be applied;

[0033] Fig.21 is a block diagram showing a second example of a schematic configuration of an eNB or gNB to which the technology of the present disclosure can be applied;

[0034] Fig. 22 is a block diagram showing an example of a schematic configuration of a smartphone to which the technology of the present disclosure can be applied;

[0035] Fig.23 is a block diagram showing an example of a schematic configuration of a car navigation device to which the technology of the present disclosure can be applied; and

[0036] Fig.24 is a block diagram of an exemplary structure of a general personal computer in which the method and / or apparatus and / or system according to the embodiments of the present invention can be implemented. DETAILED DESCRIPTION

[0037] Exemplary embodiments of the present invention will be described below in conjunction with the accompanying drawings. For the sake of clarity and conciseness, not all features of actual implementations are described in the specification. However, it should be understood that many implementation-specific decisions must be made in the process of developing any such actual implementation in order to achieve the developer's specific goals, such as meeting those constraints related to the system and business, and these constraints may vary from implementation to implementation. In addition, it should be understood that although the development work may be very complex and time-consuming, it is only a routine task for those skilled in the art who benefit from the present disclosure.

[0038] It is also necessary to explain here that, in order to avoid obscuring the present invention due to unnecessary details, only the device structure and / or processing steps closely related to the solution according to the present invention are shown in the accompanying drawings, while other details that are not closely related to the present invention are omitted.

[0039] Figure 4 A functional module block diagram of an electronic device 400 for wireless communication according to an embodiment of the present disclosure is shown.

[0040] like Figure 1 As shown, the electronic device 400 includes: a result obtaining unit 401, which can be configured to perform beam measurement with a user device within the service range of the electronic device 400 based on multiple measurement beams with a predetermined interval to obtain measurement results for multiple measurement beams; and a beam obtaining unit 403, which can be configured to obtain a predicted beam in a predicted beam pair predicted by a prediction model based on the measurement result via a prediction model (which may also be referred to as an artificial intelligence model) for predicting a beam pair to be used for communication between the electronic device 400 and the user device, wherein the predicted beam is indicated by a relative position relationship with a specific measurement beam in the multiple measurement beams.

[0041] The result obtaining unit 401 and the beam obtaining unit 403 may be implemented by one or more processing circuits, which may be implemented as a chip or a processor, for example. Figure 4 The various functional units in the electronic device 400 shown in the figure are merely logical modules divided according to the specific functions implemented by them, and are not used to limit the specific implementation method.

[0042] The electronic device 400 can be arranged on the base station side or can be communicatively connected to the base station. Here, it should also be noted that the electronic device 400 can be implemented at the chip level, or it can also be implemented at the device level. For example, the electronic device 400 can work as the base station itself, and can also include external devices such as memory, transceiver (not shown). The memory can be used to store programs and related data information that need to be executed by the electronic device 400 to implement various functions. The transceiver may include one or more communication interfaces to support communication with different devices (e.g., UE, base station, etc.), and the implementation form of the transceiver is not specifically limited here.

[0043] As an example, the base station may be, for example, an eNB or a gNB.

[0044] The wireless communication system according to the present disclosure may be a 5G NR (New Radio) communication system, a 5G+ communication system, or a 6G communication system. Further, the wireless communication system according to the present disclosure may include a non-terrestrial network (NTN). Optionally, the wireless communication system according to the present disclosure may also include a terrestrial network (TN). In addition, those skilled in the art may understand that the wireless communication system according to the present disclosure may also be a 4G or 3G communication system.

[0045] In the electronic device 400 according to an embodiment of the present disclosure, multiple measurement beams are set to have a plurality of measurement beams with a predetermined interval, so that the plurality of measurement beams satisfy a specific beam configuration (also referred to as a beam measurement configuration).

[0046] For example, the predetermined interval may be determined according to an application scenario.

[0047] As an example, each predicted beam pair includes a transmit beam and a receive beam, and the predicted beam in the beam pair is one of the transmit beam and the receive beam. The predicted beam pair predicted by the prediction model may include one or more beam pairs, and accordingly, the predicted beam may include one or more predicted beams.

[0048] In the prior art, when using artificial intelligence methods to measure beams, the entire transmit (Tx) beam set is transmitted at the transmitter, and only some Tx beams are measured for RSRP at the receiver. At this time, all Tx beams at the transmitter can be indicated by resource blocks. However, if the scheme of transmitting all Tx beams is selected, it will lead to a problem of large transmission time overhead. Because the beams that need to be measured often occupy a small part of the overall beam set, it will bring a large transmission overhead.

[0049] The beam pair referred to in the present invention includes a transmission beam and a receiving end beam that form a communication link. The transmitting end and the receiving end can simultaneously know which two specific beams the transmitting beam and the receiving beam are, that is, the transmitting end knows which receiving beam is based on the information provided by the receiving end when knowing which transmitting beam is, and the receiving end knows which transmitting beam is based on the information provided by the transmitting end when knowing which receiving beam is. Alternatively, the transmitting end and the receiving end may only know which beam they are using, that is, the receiving end does not provide the receiving beam information to the transmitting end, so that the transmitting end only knows which transmitting beam is but does not know which receiving beam is, and the transmitting end does not provide the transmitting beam information to the receiving end, so that the receiving end only knows which receiving beam is but does not know which transmitting beam is.

[0050] According to the embodiment of the present disclosure, in the beam measurement phase, measurement is performed using flexibly configured measurement beams that meet a predetermined interval, so that the prediction model can clearly understand the relative relationship between the measurement beams. In the feedback phase of the prediction beam, the prediction beam is indicated by the relative position relationship with a specific measurement beam in multiple measurement beams, and the prediction beam can be correctly indicated even if the prediction beam is not in the set of multiple measurement beams.

[0051] As an example, the above-mentioned specific measurement beam may be a measurement beam (optimal measurement beam) with the largest reference signal received power (RSRP) corresponding to the measurement beam among multiple measurement beams. The optimal measurement beam may be an example of a specific measurement beam. Those skilled in the art may also think of other examples of specific measurement beams, which are not described here. In the following, the specific measurement beam is sometimes referred to as the optimal measurement beam.

[0052] As an example, the prediction model can be deployed on the electronic device 400 side or the user equipment side, so that flexible beam configuration can be performed for the scenario where the prediction model is deployed on the user equipment side and the electronic device 400 side respectively.

[0053] As an example, in the case where the prediction model is deployed on the user device side: multiple measurement beams are transmitting beams on the electronic device 400 side, the user device uses the prediction model to predict a predicted beam as a transmitting beam in a predicted beam pair, and the beam obtaining unit 403 can be configured to receive an indication of the predicted beam from the user device.

[0054] For example, in the case where the prediction model is deployed on the user equipment side, the measurement beam is the Tx beam on the electronic device 400 side, and the Tx beam of the electronic device 400 satisfies the specific beam configuration, and the electronic device 400 can use the Tx beam to transmit in order (for example, in a clockwise or counterclockwise order), and the user equipment can receive with any receive (Rx) beam. The predicted beam is the Tx beam in the predicted beam pair predicted by the prediction model, and the electronic device 400 can receive an indication of the Tx predicted beam (i.e., the predicted beam as the Tx beam) from the user equipment.

[0055] As an example, in the case where the prediction model is deployed on the electronic device 400 side: multiple measurement beams are receiving beams on the user device side, and the beam obtaining unit 403 can be configured to use the prediction model to predict a predicted beam as a receiving beam in a predicted beam pair, and feed back an indication of the predicted beam to the user device.

[0056] For example, when the prediction model is deployed on the electronic device 400 side, the measurement beam is the Rx beam on the user equipment side, and the Rx beam of the user equipment satisfies the specific beam configuration, the user equipment can use the Rx beam to receive in order (for example, in a clockwise or counterclockwise order), and the electronic device 400 can transmit with any Tx beam. The predicted beam is the Rx beam in the predicted beam pair predicted by the prediction model, and the electronic device 400 can feed back an indication of the Rx predicted beam (i.e., the predicted beam as the Rx beam) to the user equipment.

[0057] As an example, the above-mentioned interval is the interval between beam IDs of multiple measurement beams, and the configuration information about multiple measurement beams (also referred to as beam measurement configuration information or measurement configuration information) includes the beam ID of the starting beam in the multiple measurement beams and the above-mentioned interval.

[0058] In the case where the prediction model is deployed on the user equipment side, the electronic device 400 can, for example, select the starting beam ID and the beam ID measurement interval (i.e., the interval between the beam IDs of multiple measurement beams) in the measurement configuration information of the relevant Tx beam according to the application scenario. Preferably, the beam measurement configuration information may also include the number K of measurement beams. For example, the electronic device 400 takes the starting beam ID as the starting point and selects K beams as multiple Tx measurement beams (i.e., as the measurement beams of the Tx beams on the electronic device 400 side) at the determined fixed ID interval. The electronic device 400 sends the beam measurement configuration information to the user equipment, so that the user equipment can correspond the beam ID to the resource block, and the user equipment can obtain the Tx prediction beam based on the beam measurement configuration information and using the prediction model.

[0059] In the case where the prediction model is deployed on the electronic device 400 side, the user equipment can, for example, select the starting beam ID and the beam ID measurement interval in the measurement configuration information of the Rx beam according to the application scenario. For example, the user equipment takes the starting beam ID as the starting point and selects K beams as multiple Rx measurement beams (i.e., as the measurement beams of the Rx beams on the user equipment side) at the determined fixed ID interval. The user equipment sends the beam measurement configuration information to the electronic device 400, so that the electronic device 400 can correspond the beam ID to the resource block, and the electronic device 400 can obtain the Rx predicted beam based on the beam measurement configuration information and using the prediction model.

[0060] For example, if the electronic device 400 (or user equipment) selects beam ID 4 as the starting beam, the beam ID measurement interval is 2, and the number of measurement beams is 3, the electronic device 400 (or user equipment) takes beams with beam IDs 4, 6, and 8 for measurement. The starting beam ID, beam ID measurement interval, and number of measurement beams selected by the electronic device 400 (or user equipment) can be adjusted according to actual conditions.

[0061] Figure 5 FIG. 1 is a schematic diagram showing a beam measurement configuration based on a beam ID according to an embodiment of the present disclosure. Figure 5 , beams with beam IDs from ID0 to ID8 are shown. Taking the measurement beam as the Tx beam as an example, in beam measurement configuration 1, the starting beam ID is ID0, the beam ID measurement interval is 4, and K is 3; in beam measurement configuration 2, the starting beam ID is ID1, the beam ID measurement interval is 2, and K is 3; in beam measurement configuration 3, the starting beam ID is ID0, the beam ID measurement interval is 2, and K is 5.

[0062] As an example, the relative positional relationship between the prediction beam and a specific measurement beam among the multiple measurement beams is reflected by the difference between the beam ID of the prediction beam and the beam ID of the specific measurement beam.

[0063] For example, the electronic device 400 (or user equipment) indicates the optimal measurement beam (the above-mentioned specific measurement beam) according to the resource block, calculates and feeds back the difference between the ID of the predicted beam and the optimal measurement beam (if multiple predicted beams are fed back, the feedback can be performed according to the prediction probability sorting). Preferably, other optional auxiliary information for auxiliary prediction model training can also be fed back, and the auxiliary information can include, for example, the RSRP value of the optimal measurement beam, the RSRP value of the optimal predicted beam, the probability value of the predicted beam being the optimal beam, etc. The transmission of such auxiliary information can also assist the electronic device 400 (or user equipment) in beam selection. In the existing 5G scheme, the initial access phase is transmitted by the physical random access channel (PRACH), and the CSI information about the optimal measurement beam is fed back in the CSI-ReportConfig in the radio resource control (RRC) signaling. According to an embodiment of the present disclosure, feedback content about the relative predicted beam position information can be added to the reportQuantity CHOICE in the CSI-ReportConfig of the RRC.

[0064] For example, assuming that the IDs of the measurement beams are 4, 6, and 8, and beam measurements are performed on three resource blocks 1, 2, and 3, respectively, the beam ID of the optimal measurement beam is 6, the beam ID of the optimal prediction beam (e.g., the prediction beam with the highest prediction probability) is 7, and the beam ID of the suboptimal prediction beam (e.g., the prediction beam with the second highest prediction probability) is 9. During feedback, the optimal measurement beam is indicated by the second resource block, and the relative relationship between the optimal prediction beam and the measurement beam is indicated by feedback +1 (+1=7-6) and +3 (+3=9-6).

[0065] In combination with the above description, it can be seen that according to the embodiment of the present disclosure, the configuration of beam measurement and feedback prediction beam based on the beam ID method provides more flexible beam selection for the electronic device 400 (or user equipment).

[0066] As an example, the above interval is an interval between beam space angles of the plurality of measurement beams, and the configuration information about the plurality of measurement beams includes the beam space angle of a starting beam among the plurality of measurement beams and the above interval.

[0067] In the case where the prediction model is deployed on the user equipment side, the electronic device 400 can, for example, select the beam space angle of the starting beam and the beam angle measurement interval (i.e., the interval between the beam space angles of multiple measurement beams) in the measurement configuration information of the relevant Tx beam according to the application scenario. Preferably, the beam measurement configuration information may also include the number K of measurement beams. For example, the electronic device 400 takes the beam space angle of the starting beam as the starting point and selects K beams as multiple Tx measurement beams at a determined fixed space angle interval. The electronic device 400 sends the beam measurement configuration information to the user equipment so that the user equipment can correspond the beam space angle to the resource block, and the user equipment can obtain the Tx predicted beam based on the beam measurement configuration information and using the prediction model.

[0068] In the case where the prediction model is deployed on the electronic device 400 side, the user equipment can, for example, select the beam space angle and beam angle measurement interval of the starting beam in the measurement configuration information of the Rx beam according to the application scenario. For example, the user equipment takes the beam space angle of the starting beam as the starting point and selects K beams as multiple Rx measurement beams at the determined fixed space angle interval. The user equipment sends the beam measurement configuration information to the electronic device 400, so that the electronic device 400 can correspond the beam space angle to the resource block, and the electronic device 400 can obtain the Rx predicted beam based on the beam measurement configuration information and using the prediction model.

[0069] For example, if the electronic device 400 (or user device) selects an angle of 30° relative to the antenna normal as the starting angle, the angle measurement interval is 5°, and the number of beam measurements is 3, then the electronic device 400 (or user device) needs to select beams with angles of 30°, 35°, and 40° relative to the antenna normal as measurement beams.

[0070] Figure 6 is a schematic diagram showing a beam measurement configuration based on beam angle according to an embodiment of the present disclosure. Figure 6 , beams with spatial angles of -60°, -45°, -30°, -15°, 0°, 15°, 30°, 45°, and 60° are shown. Taking the measurement beam as the Tx beam as an example, in beam measurement configuration 1, the beam spatial angle of the starting beam is -60°, the beam angle measurement interval is 60°, and K is 3; in beam measurement configuration 2, the beam spatial angle of the starting beam is -45°, the beam angle measurement interval is -15°, and K is 3; in beam measurement configuration 3, the beam spatial angle of the starting beam is -60°, the beam angle measurement interval is 30°, and K is 5.

[0071] As an example, the relative position relationship between the prediction beam and a specific measurement beam among the multiple measurement beams is reflected by the difference between the beam space angle of the prediction beam and the beam space angle of the specific measurement beam.

[0072] In the existing 5G solution, the first phase (P1), the second phase (P2), and the third phase (P3) of the beam scanning phase are defined in 3GPP TR38.802-6.1.6.1. According to the embodiment of the present disclosure, the order and selection of the transmit beam or receive beam in the three phases can be changed through the beam measurement configuration.

[0073] As an example, the plurality of measurement beams include a wide beam and a narrow beam, and configuration information of the wide beam and the narrow beam are independent of each other.

[0074] For example, in the beam measurement phase, the measurement beam may include a wide beam and a narrow beam. If the measurement beam includes both a wide beam and a narrow beam, it is first necessary to determine the beam measurement configuration information of the wide beam and the narrow beam respectively, and then perform the measurement of the wide beam and the narrow beam in turn. Among them, the beam measurement configuration information of the wide beam and the beam measurement configuration information of the narrow beam can be selected independently of each other. Therefore, a beam set defined by different beam measurement configuration information is supported, which can conveniently, flexibly and efficiently implement beam measurement.

[0075] For example, in the beam ID mode, if the beam measurement configuration information of the wide beam is: the starting beam ID is W2, the measurement interval is 2, and the number of measurements is 2, and the beam measurement configuration information of the narrow beam is: the starting beam ID is N4, the measurement interval is 1, and the number of measurements is 3, then the base station (or user) selects measurement beams with beam IDs W2, W4, N4, N5, and N6 in turn for beam measurement.

[0076] Figure 7 is a schematic diagram showing a beam measurement configuration supporting wide beams and narrow beams according to an embodiment of the present disclosure. Figure 7 , narrow beams with beam IDs ID0 to ID8 and wide beams with beam IDs WID 0 to WID 3 are shown. Taking the measurement beam as the Tx beam as an example, Figure 7 In the wide beam measurement configuration 2 + narrow beam measurement configuration 1 shown in , the starting beam ID of the wide beam is WID0, the beam angle measurement interval is 1, and the number of beams is 4, while the starting beam ID of the narrow beam is ID0, the beam angle measurement interval is 4, and the number of beams is 3; Figure 7 In the wide beam measurement configuration 1 + narrow beam measurement configuration 3 shown in , the starting beam ID of the wide beam is WID0, the beam angle measurement interval is 2, and the number of beams is 2, while the starting beam ID of the narrow beam is ID0, the beam angle measurement interval is 2, and the number of beams is 5.

[0077] As an example, in a 3D beamforming scenario, the beam space angle of a beam is indicated by a horizontal angle and a vertical angle.

[0078] In the measurement, prediction and feedback method for the spatial beam angle, in a scenario supporting 3D beamforming, the directional angle of beam measurement and feedback and the number of measurements can be indicated by the horizontal angle and the vertical angle.

[0079] For example, if the beam measurement configuration information is: the starting beam angle is: vertical 10°, horizontal 30° (recorded as (10°, 30°)), the beam angle measurement interval is: vertical 5°, horizontal 5°, the number of measurements is 2 vertically and 3 horizontally, then the beams that the electronic device 400 (or user equipment) needs to measure can be expressed as: (10°, 30°), (10°, 35°), (10°, 40°), (15°, 30°), (15°, 35°), (15°, 40°). When performing predicted beam feedback, the horizontal angle and vertical angle relative to the optimal measurement beam can also be fed back.

[0080] As an example, when the electronic device 400 and the user device do not support a beam pointing to a beam spatial angle of a predicted beam during communication, a beam having a minimum difference with the beam spatial angle of the predicted beam is used for communication. Thus, the correspondence between the spatial angle of the predicted beam and the real beam used for communication can be determined. For example, the electronic device 400 (or user device) may not support a predicted beam pointing precisely to a certain beam spatial angle, but it can select a beam having a minimum difference with the beam spatial angle of the predicted beam for communication.

[0081] The user equipment can report its absolute geographic location by reporting its absolute geographic location direction or reporting the beam ID of its beam. In the above, the beam space angle of the beam is described as an angle relative to the antenna normal. As an example, in the case where the user equipment supports reporting its absolute geographic location direction, the beam space angle of the beam is the true angle of the beam. That is, in the case where the user equipment supports reporting its absolute geographic location direction, the beam space angle of the beam can be, for example, a true angle relative to the north direction. For example, in the case where the user equipment supports reporting its absolute geographic location direction, the user equipment needs to know its own absolute position and spatial angle. In the case where the user equipment supports reporting the beam ID of its beam (for example, the beam ID of its optimal beam), the base station and the user equipment need to have a consistent understanding of the beam ID, that is, the base station and the user equipment need to have a unified understanding of the relationship between the beam ID of the user equipment and the absolute geographic location of the user equipment in advance.

[0082] As can be seen from the above description, according to the embodiments of the present disclosure, the configuration of beam measurement and feedback prediction beam based on the beam space angle method provides more flexible beam selection for the electronic device 400 (or user equipment).

[0083] As an example, the prediction model may be implemented based on a neural network. Figure 8 is a schematic diagram showing a prediction model based on a neural network according to an embodiment of the present disclosure. Figure 8 As shown in the figure, the batch layer is responsible for regularizing the data input, the convolution layer is responsible for extracting the local features of adjacent beams, the fully connected layer is responsible for extracting the global features of the beam, the dropout layer is responsible for preventing overfitting, and the shortcut structure of the convolutional neural network is responsible for preventing the degradation of the neural network. Among them, the "x5" on the right side of the convolution layer means that the convolution layer in the virtual box appears in series 5 times, that is, there are 5 convolution layer structures in series between the batch layer and the dropout layer. The input of the neural network is the RSRP value of all measured beam pairs, and the input of the corresponding position of the unmeasured beam pair is 0; the output result is the RSRP predicted value of the beam pair at the corresponding position or the probability of being the optimal predicted beam.

[0084] Fig. 9 is a schematic diagram showing the input of the prediction model according to an embodiment of the present disclosure. Fig. 9 As shown, the input of the prediction model is the RSRP values ​​of all measured beam pairs (referred to as measured beam pairs, including Tx beams and Rx beams), and the corresponding position input of the unmeasured beam pairs is 0.

[0085] Fig.10 is a schematic diagram showing the output of a prediction model based on a beam ID according to an embodiment of the present disclosure. Fig.10 As shown, both the Tx beam and the Rx beam are indicated by beam IDs (e.g., ID0 to ID8). Fig.10 The RSRP values ​​of the “measured beam pairs” shown in Fig. 9 The RSRP values ​​of the corresponding positions in are the same. The output of the prediction model includes: the predicted RSRP value of the beam pair including the Tx beam of ID4 and the Rx beam of ID0 is 3.0, and the predicted RSRP value of the beam pair including the Tx beam of ID5 and the Rx beam of ID0 is 3.2. Since the predicted RSRP value of the beam pair including the Tx beam of ID5 and the Rx beam of ID0 is the largest, the beam pair can be predicted as the optimal predicted beam pair.

[0086] Fig.11 is a schematic diagram showing the output of a prediction model based on beam space angle according to an embodiment of the present disclosure. Fig.11 As shown, Fig.11 As shown, both the Tx beam and the Rx beam are indicated by beam space angles. Fig.11 The RSRP values ​​of the “measured beam pairs” shown in Fig. 9 The RSRP values ​​of the corresponding positions in the prediction model are the same. The output of the prediction model includes: the predicted RSRP value of the beam pair including the Tx beam with a spatial angle of 0° and the Rx beam with a spatial angle of -45° is 3.0, and the predicted RSRP value of the beam pair including the Tx beam with a spatial angle of 15° and the Rx beam with a spatial angle of -45° is 3.2. Since the predicted RSRP value of the beam pair including the Tx beam with a spatial angle of 15° and the Rx beam with a spatial angle of -45° is the largest, the beam pair can be predicted as the optimal predicted beam pair.

[0087] For example, the specific beam prediction process of the prediction model can refer to the process of predicting the beam based on the neural network. For example, the neural network can adopt a multi-channel convolutional neural network structure, and use the convolution layer and the fully connected layer to extract the relevant information between the beams. As an example, the prediction model can be based on the convolutional neural network, and the measurement results for the wide beam and the measurement results for the narrow beam are used as inputs of different channels of the convolutional neural network for prediction by the convolutional neural network.

[0088] As an example, when the difference between the RSRP corresponding to the predicted beam output by the prediction model and the RSPR obtained by measuring based on the predicted beam is greater than or equal to a predetermined difference threshold, the number of predicted beams is increased and / or the number of multiple measurement beams is increased. As an example, when the difference between the RSRP corresponding to the predicted beam output by the prediction model and the RSPR obtained by measuring based on the predicted beam is less than a predetermined difference threshold, the number of predicted beams is reduced and / or the number of multiple measurement beams is reduced.

[0089] In the prior art, when using artificial intelligence methods to predict beams, a fixed beam configuration is used for measurement and prediction, and the ID of each measured beam and the order of beam transmission are fixed. If a fixed beam measurement configuration is selected, it will lead to poor flexibility. Since the measurement beam and the beam input into the prediction model are fixed, it is difficult to make adaptive modifications to the changing wireless environment, which affects the measurement overhead and prediction performance.

[0090] According to the embodiments of the present disclosure, dynamic prediction of the number of beams and dynamic configuration of measurement beams are supported, thereby reducing measurement overhead and communication overhead while ensuring performance.

[0091] Fig.12 It is an example of a flowchart showing information interaction between the electronic device 400 and the user equipment (referred to as user) when the prediction model is deployed on the electronic device 400 (referred to as base station) side.

[0092] In S1, the user and the base station perform function and model authentication. For example, the base station and the user can interact with at least part of the following information: whether wide beam is supported, whether 3D beamforming is supported, whether reporting of absolute geographic location direction is supported, whether beams indexed by angle are supported, the number of Tx beams, the number of Rx beams, and the number of inputs to the prediction model.

[0093] In S2, the base station initializes / modifies the Tx beam mode. For example, the Tx beam mode may include the number of Tx beams. As described above, when the prediction model is deployed on the electronic device 400 side, the base station may transmit with any Tx beam.

[0094] In S3, the user initializes / modifies the beam measurement configuration information of the Rx beam. As described above, when the prediction model is deployed on the electronic device 400 side, the measurement beam refers to the Rx beam on the user side, and the Rx beam of the user satisfies a specific beam measurement configuration.

[0095] In S4, the user notifies the base station of beam measurement configuration information of the Rx beam as the measurement beam.

[0096] In S5, the base station selects a beam in the Tx beam mode, and the user selects a beam corresponding to the Rx beam measurement configuration information, performs beam measurement, and feeds back RSRP information of the measured beam pair.

[0097] In S6, the base station uses the prediction model to perform beam prediction using the measured RSRP values ​​of the beam pairs.

[0098] In S7, the base station feeds back the information related to the optimal measurement beam and the optimal prediction beam to the user. For example, the base station indicates the optimal measurement beam according to the resource block, and feeds back the difference between the IDs of the optimal prediction beam and the optimal measurement beam or the difference between the spatial angles of the optimal prediction beam and the optimal measurement beam.

[0099] In S8, the base station and the user perform RSRP measurement on the predicted beam to obtain the RSRP measurement result for the predicted beam, and notify the measurement result.

[0100] In S9, the base station determines whether to adjust the number of predicted beams output by the prediction model and / or whether to adjust the Tx beam mode (for example, adjust the number of Tx beams) based on the difference between the predicted value of RSRP corresponding to the predicted beam output by the prediction model and the actual measured RSRP value obtained in S8.

[0101] In S10, the user determines whether to adjust the Rx beam measurement configuration information (for example, adjust the number of Rx beams) based on the difference between the predicted value of RSRP corresponding to the predicted beam output by the prediction model and the actual measured RSRP value obtained in S8.

[0102] Combination Fig.12 It can be seen that when the model is deployed on the electronic device 400, the beam measurement configuration and the number of output prediction beams can be flexibly adjusted to reduce communication overhead.

[0103] Fig.13 It is an example of a flowchart showing information interaction between an electronic device 400 (referred to as a base station) and a user equipment when a prediction model is deployed on the user equipment (referred to as a user) side.

[0104] In S1, the user and the base station perform function and model authentication. For example, the base station and the user can interact with at least part of the following information: whether wide beam is supported, whether 3D beamforming is supported, whether reporting of absolute geographic location direction is supported, whether beams indexed by angle are supported, the number of Tx beams, the number of Rx beams, and the number of inputs to the prediction model.

[0105] In S2, the base station initializes / modifies the beam measurement configuration information of the Tx beam. As described above, when the prediction model is deployed on the user equipment side, the measurement beam refers to the Tx beam on the electronic device 400 side, and the Tx beam on the electronic device 400 side satisfies a specific beam measurement configuration.

[0106] In S3, the user initializes / changes the Rx beam mode. For example, the Rx beam mode may include the number of Rx beams. As described above, when the prediction model is deployed on the user equipment side, the user can receive with any Rx beam.

[0107] In S4, the base station notifies the user of beam measurement configuration information of the Tx beam as the measurement beam.

[0108] In S5, the base station transmits the Tx beams in sequence according to the beam measurement configuration information of the Tx beams, and the user measures the RSRP value of the beam pair using the beams in the Rx beam mode.

[0109] In S6, the user uses the prediction model to perform beam prediction using the measured RSRP value.

[0110] In S7, the user feeds back the information related to the optimal measurement beam and the optimal prediction beam to the base station. For example, the user indicates the optimal measurement beam according to the resource block, and feeds back the difference between the IDs of the optimal prediction beam and the optimal measurement beam or the difference between the spatial angles of the optimal prediction beam and the optimal measurement beam.

[0111] In S8, the base station and the user perform RSRP measurement on the predicted beam to obtain the RSRP measurement result for the predicted beam, and notify the measurement result.

[0112] In S9, the base station determines whether to adjust the Tx beam measurement configuration information (for example, adjust the number of Tx beams) according to the difference between the predicted value of RSRP corresponding to the predicted beam output by the prediction model and the actual measured RSRP value obtained in S8.

[0113] In S10, the user determines whether to adjust the number of predicted beams output by the prediction model and / or whether to adjust the Rx beam mode (for example, adjust the number of Rx beams) based on the difference between the predicted value of RSRP corresponding to the predicted beam output by the prediction model and the actual measured RSRP value obtained in S8.

[0114] Combination Fig.13 It can be seen that when the model is deployed on the user equipment side, the beam measurement configuration and the number of output prediction beams can be flexibly adjusted to reduce communication overhead.

[0115] In the present disclosure, beam prediction is simulated. Considering the transmission scenario under millimeter wave, the O1 scenario of DeepMIMO is used to generate channel data. Fig.14 is a schematic diagram showing the O1 scenario of DeepMIMO. Fig.14 In the figure, BS represents base station, for example, BS12 represents the 12th base station; R represents row, for example, R550 represents the 550th row; the white boxes marked with numbers represent buildings, and the numbers represent the height of the buildings, for example, the building near BS12 is 14 meters high.

[0116] In the simulation, it is assumed that users are randomly and uniformly distributed in the DeepMIMO scenario. Fig.14 The simulation parameters are shown in the following table.

[0117] Simulation parameters Numeric Carrier frequency 28GHz mmWave enabled base stations BS5 bandwidth 100MHz Number of base station antennas / number of beams 64 Number of user antennas / number of beams 4 Antenna shape Uniform linear array antenna Antenna spacing One-half wavelength

[0118] In the simulation, three beam prediction methods are considered: 1) Traditional beam scanning method (traditional method), select M×N beams to measure their RSRP, and select the beam pair with the largest RSRP among the measured beam pairs. 2) AI K=1 method, select M×N beam pairs to measure their RSRP, and send the measurement results as input to the prediction model. After obtaining the output, select the beam pair with the highest prediction probability as the optimal prediction beam pair. 3) AI K=3 method, select M×N beam pairs to measure their RSRP, and send the measurement results as input to the prediction model. After obtaining the output, select the 3 beam pairs with the highest prediction probability. After beam measurement of these 3 beams, select the beam pair with the highest RSRP as the optimal prediction beam pair.

[0119] Two evaluation metrics are considered.

[0120] Evaluation index 1 is the prediction accuracy: Assuming that the number of samples used for evaluation is N1, and the number of samples where the beam predicted is the actual optimal beam is N2, the accuracy is expressed as:

[0121]

[0122] Evaluation index 2 is the normalized beam gain: Assuming that the average received power (actual measured power) obtained by using the predicted optimal beam pair is The maximum actual measured power of all selectable beam pairs that can be emitted by the electronic device 400 or the user equipment is P a , the normalized beam gain is expressed as

[0123]

[0124] The upper limits of the above two evaluation indicators are both 1.

[0125] The loss function of the prediction model adopts the cross entropy loss function, which can be expressed as:

[0126]

[0127] Among them, x is a different sample; y i (x) is a binary indicator variable, which takes the value 1 when the i-th beam pair of the x-th sample is the optimal beam pair, and takes the value 0 in other cases; p i (x) represents the probability that the i-th beam pair in the prediction output of the prediction model of the x-th sample is the optimal prediction beam pair. The optimizer can adopt the Adam optimizer in the prior art for optimization.

[0128] Fig.15 It is a figure which shows the simulation result about the prediction accuracy.

[0129] exist Fig.15 In the figure, the horizontal axis is written in the format of A×B, where A represents the number of transmit beams on the electronic device 400, B represents the number of receive beams on the user device, and the product of the two represents the total number of beam pairs measured. For simplicity, the horizontal axis is marked with "beam measurement configuration". For example, 8×2 means that the number of transmit beams measured on the electronic device 400 is 8, the number of receive beams measured on the user device is 2, and a total of 16 beam pairs are measured. For example, assume that the total number of transmit beams available on the electronic device 400 is 64, and the total number of receive beams available on the user device is 4. 8×2 means that 8 transmit beams are selected from the 64 transmit beams available on the electronic device 400, for example, according to the beam measurement configuration described above, and 2 receive beams are selected from the 4 receive beams available to the user device.

[0130] Fig.15 The vertical axis in represents the prediction accuracy.

[0131] from Fig.15 It can be seen that in terms of prediction accuracy, the performance of the AI ​​K=3 method and the AI ​​K=1 method are both better than the traditional method, and the performance of the AI ​​K=3 method is better than the AI ​​K=1 method, and the AI ​​K=1 method is better than the traditional method.

[0132] Fig.16 is a graph of simulation results regarding normalized beam gain.

[0133] Fig.16 The horizontal axis of Fig.15 Same as in , the ordinate represents the normalized beam gain.

[0134] from Fig.16 It can be seen that in terms of normalized beam gain, the performance of the AI ​​K=3 method and the AI ​​K=1 method are both better than the traditional method, and the performance of the AI ​​K=3 method is better than the AI ​​K=1 method, and the AI ​​K=1 method is better than the traditional method.

[0135] For each method, more measured beam pairs lead to better performance. However, it can be seen that for the cases with 16×2 and 8×4 as the horizontal axes, although the total number of measured beam pairs for both configurations is equal to 32, the normalized beam gain in the 16×2 case is better than that in the 8×4 case. This is because the number of transmit beams in the 16×2 case is more, and the number of receive beams in the 8×4 case is more. When the total number of measured beam pairs is constant, the prediction results under more measured transmit beams can enable the system to obtain higher beam gains.

[0136] In addition, it can be observed that for the AI ​​K=3 method, the performance shows a slight improvement as the number of measured beam pairs increases. This is because even with 4×4 beam measurements, the performance of the normalized beam gain under the AI ​​K=3 method is close to the upper limit, that is, close to 1.

[0137] The present disclosure also provides an electronic device for wireless communication according to another embodiment. Fig.17 A functional module block diagram of an electronic device 1700 for wireless communication according to another embodiment of the present disclosure is shown.

[0138] like Fig.17As shown, the electronic device 1700 includes: a measurement result obtaining unit 1701, which can be configured to perform beam measurement based on a plurality of measurement beams with a predetermined interval with a network side device providing services for the electronic device 1700, so as to obtain measurement results for the plurality of measurement beams; and a prediction beam obtaining unit 1703, which can be configured to obtain a prediction beam in a prediction beam pair predicted by a prediction model based on the measurement result via a prediction model for predicting a beam pair to be used by the electronic device 1700 to communicate with the network side device, wherein the prediction beam is indicated by a relative position relationship with a specific measurement beam in the plurality of measurement beams. And, it should be understood that, Fig.17 The various functional units in the electronic device 1700 shown in the figure are merely logical modules divided according to the specific functions implemented by them, and are not used to limit the specific implementation method.

[0139] The unit for obtaining the measurement result 1701 and the unit for obtaining the predicted beam 1703 may be implemented by one or more processing circuits, which may be implemented as a chip, for example.

[0140] The electronic device 1700 can be arranged on the user equipment side or can be communicatively connected to the user equipment. Here, it should also be noted that the electronic device 1700 can be implemented at the chip level, or it can also be implemented at the device level. For example, the electronic device 1700 can work as the user equipment itself, and can also include external devices such as memory, transceiver (not shown in the figure), etc. The memory can be used to store programs and related data information that need to be executed by the user equipment to implement various functions. The transceiver may include one or more communication interfaces to support communication with different devices (e.g., base stations, other user equipment, etc.), and the implementation form of the transceiver is not specifically limited here.

[0141] The wireless communication system according to the present disclosure may be a 5G NR communication system, a 5G+ communication system, or a 6G communication system. Further, the wireless communication system according to the present disclosure may include a non-terrestrial network. Optionally, the wireless communication system according to the present disclosure may also include a terrestrial network. In addition, those skilled in the art may understand that the wireless communication system according to the present disclosure may also be a 4G or 3G communication system.

[0142] As an example, the network side device in the embodiment of the electronic device 1700 may be the electronic device 400 mentioned above. As an example, the electronic device 1700 may be the user equipment involved in the embodiment of the electronic device 400 mentioned above.

[0143] According to the embodiment of the present disclosure, in the beam measurement phase, measurement is performed using flexibly configured measurement beams that meet a predetermined interval, so that the prediction model can clearly understand the relative relationship between the measurement beams. In the feedback phase of the prediction beam, the prediction beam is indicated by the relative position relationship with a specific measurement beam in multiple measurement beams, and the prediction beam can be correctly indicated even if the prediction beam is not in the set of multiple measurement beams.

[0144] As an example, the specific measurement beam may be a measurement beam whose corresponding reference signal received power RSRP is the largest among multiple measurement beams.

[0145] As an example, the interval may be an interval between beam IDs of the plurality of measurement beams, and the configuration information about the plurality of measurement beams includes the beam ID of a start beam among the plurality of measurement beams and the interval.

[0146] For an example of beam measurement configuration based on beam ID, see Figure 5 The description will not be repeated here.

[0147] As an example, the relative position relationship between the prediction beam and the specific measurement beam is reflected by the difference between the beam ID of the prediction beam and the beam ID of the specific measurement beam.

[0148] As an example, the interval may be an interval between beam space angles of the plurality of measurement beams, and the configuration information about the plurality of measurement beams includes the beam space angle of a starting beam among the plurality of measurement beams and the interval.

[0149] An example of a beam measurement configuration based on beam angle can be found in Figure 6 The description will not be repeated here.

[0150] As an example, the relative position relationship between the prediction beam and the specific measurement beam is reflected by the difference between the beam space angle of the prediction beam and the beam space angle of the specific measurement beam.

[0151] As an example, the plurality of measurement beams include a wide beam and a narrow beam, and configuration information of the wide beam and the narrow beam are independent of each other.

[0152] Examples of beam measurement configurations supporting wide and narrow beams can be found in Figure 7 The description will not be repeated here.

[0153] As an example, in a 3D beamforming scenario, the beam space angle of a beam is indicated by a horizontal angle and a vertical angle.

[0154] As an example, when a beam pointing to a beam space angle of a predicted beam is not supported during communication between the electronic device 1700 and the network side device, a beam having a minimum difference with the beam space angle of the predicted beam is used for communication.

[0155] As an example, the prediction model is a convolutional neural network, and the measurement results for the wide beam and the measurement results for the narrow beam are used as inputs of different channels of the convolutional neural network for the convolutional neural network to make predictions.

[0156] As an example, when the difference between the RSRP corresponding to the predicted beam output by the prediction model and the RSPR obtained by measuring based on the predicted beam is greater than or equal to a predetermined difference threshold, the number of predicted beams is increased and / or the number of multiple measurement beams is increased.

[0157] As an example, when the difference between the RSRP corresponding to the predicted beam output by the prediction model and the RSPR obtained by measuring based on the predicted beam is less than a predetermined difference threshold, the number of predicted beams is reduced and / or the number of multiple measurement beams is reduced.

[0158] In the process of describing the electronic device 400 and the electronic device 1700 for wireless communication in the above embodiments, it is obvious that some processes or methods are also disclosed. Below, an overview of these methods is given without repeating some details discussed above, but it should be noted that although these methods are disclosed in the process of describing the electronic device for wireless communication, these methods do not necessarily use the components described or are not necessarily performed by those components. For example, the embodiments of the electronic device for wireless communication can be partially or completely implemented using hardware and / or firmware, and the methods for wireless communication discussed below can be completely implemented by a computer executable program, although these methods can also use the hardware and / or firmware of the electronic device for wireless communication.

[0159] Fig.18 A flowchart of a method S1800 for wireless communication according to an embodiment of the present disclosure is shown. The method S1800 starts at step S1802. In step S1804, beam measurement is performed with a user device within a service range of the electronic device based on multiple measurement beams with a predetermined interval to obtain measurement results for the multiple measurement beams. In step S1806, a prediction model for predicting a beam pair to be used for communication between the electronic device and the user device is used to obtain a predicted beam in the predicted beam pair predicted by the prediction model based on the measurement result, wherein the predicted beam is indicated by a relative position relationship with a specific measurement beam in the multiple measurement beams. The method S1800 ends at step S1808.

[0160] The method may be executed, for example, by the electronic device 400 described above. For specific details, reference may be made to the description of the related processing of the electronic device 400, which will not be repeated here.

[0161] Fig.19 A flowchart of a method S1900 for wireless communication according to another embodiment of the present disclosure is shown. The method S1900 starts at step S1902. In step S1904, beam measurement is performed with a network-side device that provides services for an electronic device based on a plurality of measurement beams with a predetermined interval to obtain measurement results for the plurality of measurement beams. In step S1906, a prediction model is used to predict a beam pair to be used for communication between the electronic device and the network-side device, and a predicted beam in the predicted beam pair predicted by the prediction model based on the measurement result is obtained, wherein the predicted beam is indicated by a relative positional relationship with a specific measurement beam in the plurality of measurement beams. The method S1900 ends at step S1908.

[0162] The method may be executed, for example, by the electronic device 1700 described above. For specific details, reference may be made to the description of the related processing of the electronic device 1700, which will not be repeated here.

[0163] The technology of the present disclosure can be applied to various products.

[0164] The electronic device 400 can be set on the base station side or connected to the base station. The base station can be implemented as any type of evolved Node B (eNB) or gNB (5G base station). eNB includes, for example, macro eNB and small eNB. Small eNB can be an eNB that covers a cell smaller than a macro cell, such as a pico eNB, a micro eNB, and a home (femto) eNB. Similar situations can also be applied to gNB. Alternatively, the base station can be implemented as any other type of base station, such as a NodeB and a base transceiver station (BTS). The base station may include: a main body (also referred to as a base station device) configured to control wireless communications; and one or more remote radio heads (RRHs) arranged in a place different from the main body. In addition, various types of electronic devices can work as a base station by temporarily or semi-permanently performing base station functions.

[0165] The electronic device 1700 may be implemented as various user devices. The user device may be implemented as a mobile terminal (such as a smart phone, a tablet personal computer (PC), a notebook PC, a portable game terminal, a portable / dongle-type mobile router, and a digital camera) or a vehicle-mounted terminal (such as a car navigation device). The user device may also be implemented as a terminal for performing machine-to-machine (M2M) communication (also referred to as a machine type communication (MTC) terminal). In addition, the user device may be a wireless communication module (such as an integrated circuit module including a single chip) installed on each of the above-mentioned terminals.

[0166] [Application examples for base stations]

[0167] (First application example)

[0168] Fig. 20 800 is a block diagram showing a first example of a schematic configuration of an eNB or gNB to which the technology of the present disclosure can be applied. Note that the following description takes eNB as an example, but can also be applied to gNB. The eNB 800 includes one or more antennas 810 and a base station device 820. The base station device 820 and each antenna 810 can be connected to each other via an RF cable.

[0169] Each of the antennas 810 includes a single or multiple antenna elements (such as multiple antenna elements included in a multiple-input multiple-output (MIMO) antenna) and is used for the base station device 820 to transmit and receive wireless signals. Fig. 20 As shown, the eNB 800 may include multiple antennas 810. For example, the multiple antennas 810 may be compatible with multiple frequency bands used by the eNB 800. Fig. 20 An example is shown in which the eNB 800 includes a plurality of antennas 810 , but the eNB 800 may also include a single antenna 810 .

[0170] The base station device 820 includes a controller 821 , a memory 822 , a network interface 823 , and a wireless communication interface 825 .

[0171] The controller 821 may be, for example, a CPU or a DSP, and operates various functions of the higher layers of the base station device 820. For example, the controller 821 generates a data packet based on the data in the signal processed by the wireless communication interface 825, and transmits the generated packet via the network interface 823. The controller 821 may bundle data from a plurality of baseband processors to generate a bundled packet, and transmit the generated bundled packet. The controller 821 may have a logical function to perform the following control: the control may be such as radio resource control, radio bearer control, mobility management, admission control, and scheduling. The control may be performed in conjunction with a nearby eNB or core network node. The memory 822 includes a RAM and a ROM, and stores programs executed by the controller 821 and various types of control data (such as a terminal list, transmission power data, and scheduling data).

[0172] The network interface 823 is a communication interface for connecting the base station device 820 to the core network 824. The controller 821 can communicate with the core network node or another eNB via the network interface 823. In this case, the eNB 800 and the core network node or other eNBs can be connected to each other through a logical interface (such as an S1 interface and an X2 interface). The network interface 823 can also be a wired communication interface or a wireless communication interface for a wireless backhaul line. If the network interface 823 is a wireless communication interface, the network interface 823 can use a higher frequency band for wireless communication compared to the frequency band used by the wireless communication interface 825.

[0173] The wireless communication interface 825 supports any cellular communication scheme (such as long term evolution (LTE) and LTE-Advanced), and provides a wireless connection to a terminal located in a cell of the eNB 800 via the antenna 810. The wireless communication interface 825 may generally include, for example, a baseband (BB) processor 826 and an RF circuit 827. The BB processor 826 may perform, for example, encoding / decoding, modulation / demodulation, and multiplexing / demultiplexing, and perform various types of signal processing of layers (e.g., layer 1, medium access control (MAC), radio link control (RLC), and packet data convergence protocol (PDCP)). Instead of the controller 821, the BB processor 826 may have a part or all of the above-mentioned logical functions. The BB processor 826 may be a memory storing a communication control program, or a module including a processor configured to execute a program and related circuits. Updating the program may change the function of the BB processor 826. The module may be a card or a blade inserted into a slot of the base station device 820. Alternatively, the module may also be a chip mounted on a card or a blade. Meanwhile, the RF circuit 827 may include, for example, a mixer, a filter, and an amplifier, and transmits and receives a wireless signal via the antenna 810 .

[0174] like Fig. 20As shown, the wireless communication interface 825 may include multiple BB processors 826. For example, the multiple BB processors 826 may be compatible with multiple frequency bands used by the eNB 800. Fig. 20 As shown, the wireless communication interface 825 may include multiple RF circuits 827. For example, the multiple RF circuits 827 may be compatible with multiple antenna elements. Fig. 20 An example is shown in which the wireless communication interface 825 includes a plurality of BB processors 826 and a plurality of RF circuits 827 , but the wireless communication interface 825 may also include a single BB processor 826 or a single RF circuit 827 .

[0175] When the electronic device 400 is implemented as Fig. 20 In the illustrated eNB 800, its transceiver may be implemented by a wireless communication interface 825. At least a portion of the functions may also be implemented by a controller 821. For example, the controller 821 may enable the prediction model to clearly understand the relative relationship between the measurement beams by executing the functions of the units in the electronic device 400. In addition, even if the predicted beam is not in the set of multiple measurement beams, the predicted beam can be correctly indicated.

[0176] (Second application example)

[0177] Fig.21 830 is a block diagram showing a second example of a schematic configuration of an eNB or gNB to which the technology of the present disclosure can be applied. Note that similarly, the following description takes the eNB as an example, but can also be applied to the gNB. The eNB 830 includes one or more antennas 840, a base station device 850, and an RRH 860. The RRH 860 and each antenna 840 can be connected to each other via an RF cable. The base station device 850 and the RRH 860 can be connected to each other via a high-speed line such as an optical fiber cable.

[0178] Each of the antennas 840 includes a single or multiple antenna elements (such as multiple antenna elements included in a MIMO antenna) and is used for the RRH 860 to transmit and receive wireless signals. Fig.21 As shown, the eNB 830 may include multiple antennas 840. For example, the multiple antennas 840 may be compatible with multiple frequency bands used by the eNB 830. Fig.21 An example is shown in which the eNB 830 includes a plurality of antennas 840 , but the eNB 830 may also include a single antenna 840 .

[0179] The base station device 850 includes a controller 851, a memory 852, a network interface 853, a wireless communication interface 855, and a connection interface 857. The controller 851, the memory 852, and the network interface 853 are similar to the reference Fig.21The controller 821, memory 822 and network interface 823 described are the same.

[0180] The wireless communication interface 855 supports any cellular communication scheme (such as LTE and LTE-Advanced), and provides wireless communication to a terminal located in a sector corresponding to the RRH 860 via the RRH 860 and the antenna 840. The wireless communication interface 855 may generally include, for example, a BB processor 856. In addition to the BB processor 856 being connected to the RF circuit 864 of the RRH 860 via the connection interface 857, the BB processor 856 is connected to the reference RF circuit 864 of the RRH 860. Fig.21 The same as the BB processor 826 described above. Fig.21 As shown, the wireless communication interface 855 may include multiple BB processors 856. For example, the multiple BB processors 856 may be compatible with multiple frequency bands used by the eNB 830. Fig.21 An example is shown in which the wireless communication interface 855 includes a plurality of BB processors 856 , but the wireless communication interface 855 may also include a single BB processor 856 .

[0181] The connection interface 857 is an interface for connecting the base station device 850 (wireless communication interface 855) to the RRH 860. The connection interface 857 may also be a communication module for connecting the base station device 850 (wireless communication interface 855) to the RRH 860 for communication in the above-mentioned high-speed line.

[0182] The RRH 860 includes a connection interface 861 and a wireless communication interface 863 .

[0183] The connection interface 861 is an interface for connecting the RRH 860 (wireless communication interface 863) to the base station device 850. The connection interface 861 may also be a communication module for communication in the above-mentioned high-speed line.

[0184] The wireless communication interface 863 transmits and receives wireless signals via the antenna 840. The wireless communication interface 863 may generally include, for example, an RF circuit 864. The RF circuit 864 may include, for example, a mixer, a filter, and an amplifier, and transmits and receives wireless signals via the antenna 840. Fig.21 As shown, the wireless communication interface 863 may include multiple RF circuits 864. For example, the multiple RF circuits 864 may support multiple antenna elements. Fig.21 An example is shown in which the wireless communication interface 863 includes a plurality of RF circuits 864 , but the wireless communication interface 863 may also include a single RF circuit 864 .

[0185] When the electronic device 400 is implemented as Fig.21In the case of the eNB 830 shown, its transceiver may be implemented by the wireless communication interface 855. At least part of the functions may also be implemented by the controller 851. For example, the controller 851 may enable the prediction model to clearly understand the relative relationship between the measurement beams by executing the functions of the units in the electronic device 400. In addition, even if the predicted beam is not in the set of multiple measurement beams, the predicted beam can be correctly indicated.

[0186] [Application examples on user devices]

[0187] (First application example)

[0188] Fig. 22 900 is a block diagram showing an example of a schematic configuration of a smartphone 900 to which the technology of the present disclosure can be applied. The smartphone 900 includes a processor 901, a memory 902, a storage device 903, an external connection interface 904, a camera device 906, a sensor 907, a microphone 908, an input device 909, a display device 910, a speaker 911, a wireless communication interface 912, one or more antenna switches 915, one or more antennas 916, a bus 917, a battery 918, and an auxiliary controller 919.

[0189] The processor 901 may be, for example, a CPU or a system on chip (SoC), and controls the functions of the application layer and other layers of the smartphone 900. The memory 902 includes a RAM and a ROM, and stores data and programs executed by the processor 901. The storage device 903 may include a storage medium such as a semiconductor memory and a hard disk. The external connection interface 904 is an interface for connecting an external device such as a memory card and a universal serial bus (USB) device to the smartphone 900.

[0190] The camera 906 includes an image sensor such as a charge coupled device (CCD) and a complementary metal oxide semiconductor (CMOS), and generates a captured image. The sensor 907 may include a group of sensors such as a measurement sensor, a gyro sensor, a geomagnetic sensor, and an acceleration sensor. The microphone 908 converts the sound input to the smart phone 900 into an audio signal. The input device 909 includes, for example, a touch sensor, a keypad, a keyboard, a button, or a switch configured to detect a touch on the screen of the display device 910, and receives an operation or information input from a user. The display device 910 includes a screen such as a liquid crystal display (LCD) and an organic light emitting diode (OLED) display, and displays an output image of the smart phone 900. The speaker 911 converts an audio signal output from the smart phone 900 into sound.

[0191] The wireless communication interface 912 supports any cellular communication scheme (such as LTE and LTE-Advanced), and performs wireless communication. The wireless communication interface 912 may generally include, for example, a BB processor 913 and an RF circuit 914. The BB processor 913 may perform, for example, encoding / decoding, modulation / demodulation, and multiplexing / demultiplexing, and perform various types of signal processing for wireless communication. Meanwhile, the RF circuit 914 may include, for example, a mixer, a filter, and an amplifier, and transmit and receive wireless signals via an antenna 916. Note that although the figure shows a situation where one RF link is connected to one antenna, this is only schematic, and also includes a situation where one RF link is connected to multiple antennas through multiple phase shifters. The wireless communication interface 912 may be a chip module on which the BB processor 913 and the RF circuit 914 are integrated. As shown in FIG. Fig. 22 As shown, the wireless communication interface 912 may include multiple BB processors 913 and multiple RF circuits 914. Fig. 22 An example is shown in which the wireless communication interface 912 includes a plurality of BB processors 913 and a plurality of RF circuits 914 , but the wireless communication interface 912 may also include a single BB processor 913 or a single RF circuit 914 .

[0192] In addition, in addition to the cellular communication scheme, the wireless communication interface 912 can support other types of wireless communication schemes, such as short-range wireless communication schemes, near field communication schemes, and wireless local area network (LAN) schemes. In this case, the wireless communication interface 912 can include a BB processor 913 and an RF circuit 914 for each wireless communication scheme.

[0193] Each of the antenna switches 915 switches a connection destination of the antenna 916 between a plurality of circuits (eg, circuits for different wireless communication schemes) included in the wireless communication interface 912 .

[0194] Each of the antennas 916 includes a single or multiple antenna elements (such as multiple antenna elements included in a MIMO antenna) and is used for the wireless communication interface 912 to transmit and receive wireless signals. Fig. 22 As shown, the smartphone 900 may include multiple antennas 916. Fig. 22 An example is shown in which the smartphone 900 includes a plurality of antennas 916 , but the smartphone 900 may also include a single antenna 916 .

[0195] In addition, the smartphone 900 may include an antenna 916 for each wireless communication scheme. In this case, the antenna switch 915 may be omitted from the configuration of the smartphone 900.

[0196] The bus 917 connects the processor 901, the memory 902, the storage device 903, the external connection interface 904, the camera 906, the sensor 907, the microphone 908, the input device 909, the display device 910, the speaker 911, the wireless communication interface 912, and the auxiliary controller 919 to each other. Fig. 22 The various blocks of the smartphone 900 shown are supplied with power, the feed lines being partially shown as dashed lines in the figure. The auxiliary controller 919 operates the minimum necessary functions of the smartphone 900, for example in a sleep mode.

[0197] When the electronic device 1700 is implemented as a smart phone as a user device, for example Fig. 22 In the case of the smart phone 900 shown, the transceiver of the electronic device 1700 can be implemented by the wireless communication interface 912. At least part of the functions can also be implemented by the processor 901 or the auxiliary controller 919. For example, the processor 901 or the auxiliary controller 919 executes the functions of the units in the electronic device 1700, so that the prediction model can clearly understand the relative relationship between the measurement beams. In addition, even if the prediction beam is not in the set of multiple measurement beams, the prediction beam can be correctly indicated.

[0198] (Second application example)

[0199] Fig.23 9 is a block diagram showing an example of a schematic configuration of a car navigation device 920 to which the technology of the present disclosure can be applied. The car navigation device 920 includes a processor 921, a memory 922, a global positioning system (GPS) module 924, a sensor 925, a data interface 926, a content player 927, a storage medium interface 928, an input device 929, a display device 930, a speaker 931, a wireless communication interface 933, one or more antenna switches 936, one or more antennas 937, and a battery 938.

[0200] The processor 921 may be, for example, a CPU or an SoC, and controls a navigation function and another function of the car navigation device 920. The memory 922 includes a RAM and a ROM, and stores data and a program executed by the processor 921.

[0201] The GPS module 924 measures the position (such as latitude, longitude and altitude) of the car navigation device 920 using GPS signals received from GPS satellites. The sensor 925 may include a group of sensors such as a gyro sensor, a geomagnetic sensor and an air pressure sensor. The data interface 926 is connected to, for example, the vehicle network 941 via an unshown terminal and acquires data (such as vehicle speed data) generated by the vehicle.

[0202] The content player 927 reproduces content stored in a storage medium such as a CD and a DVD, which is inserted into the storage medium interface 928. The input device 929 includes, for example, a touch sensor, a button, or a switch configured to detect a touch on the screen of the display device 930, and receives an operation or information input from a user. The display device 930 includes a screen such as an LCD or an OLED display, and displays an image of a navigation function or reproduced content. The speaker 931 outputs a sound of a navigation function or reproduced content.

[0203] The wireless communication interface 933 supports any cellular communication scheme (such as LTE and LTE-Advanced), and performs wireless communication. The wireless communication interface 933 may generally include, for example, a BB processor 934 and an RF circuit 935. The BB processor 934 may perform, for example, encoding / decoding, modulation / demodulation, and multiplexing / demultiplexing, and perform various types of signal processing for wireless communication. Meanwhile, the RF circuit 935 may include, for example, a mixer, a filter, and an amplifier, and transmit and receive wireless signals via an antenna 937. The wireless communication interface 933 may also be a chip module on which the BB processor 934 and the RF circuit 935 are integrated. Fig.23 As shown, the wireless communication interface 933 may include multiple BB processors 934 and multiple RF circuits 935. Fig.23 An example is shown in which the wireless communication interface 933 includes a plurality of BB processors 934 and a plurality of RF circuits 935 , but the wireless communication interface 933 may also include a single BB processor 934 or a single RF circuit 935 .

[0204] In addition, in addition to the cellular communication scheme, the wireless communication interface 933 can support other types of wireless communication schemes, such as short-range wireless communication schemes, near field communication schemes, and wireless LAN schemes. In this case, for each wireless communication scheme, the wireless communication interface 933 can include a BB processor 934 and an RF circuit 935.

[0205] Each of the antenna switches 936 switches a connection destination of the antenna 937 between a plurality of circuits included in the wireless communication interface 933 , such as circuits for different wireless communication schemes.

[0206] Each of the antennas 937 includes a single or multiple antenna elements (such as multiple antenna elements included in a MIMO antenna), and is used for the wireless communication interface 933 to transmit and receive wireless signals. Fig.23 As shown, the car navigation device 920 may include multiple antennas 937. Fig.23 An example is shown in which the car navigation device 920 includes a plurality of antennas 937 , but the car navigation device 920 may also include a single antenna 937 .

[0207] Furthermore, the car navigation device 920 may include an antenna 937 for each wireless communication scheme. In this case, the antenna switch 936 may be omitted from the configuration of the car navigation device 920.

[0208] Battery 938 is fed via a feed line to Fig.23 The respective blocks of the illustrated car navigation device 920 are supplied with electric power, and feed lines are partially illustrated as dotted lines in the figure. The battery 938 accumulates electric power supplied from the vehicle.

[0209] When the electronic device 1700 is implemented as a car navigation device on the user device side, for example Fig.23 In the case of the car navigation device 920 shown, the transceiver of the electronic device 1700 can be implemented by the wireless communication interface 933. At least part of the functions can also be implemented by the processor 921. For example, the processor 921 enables the prediction model to clearly understand the relative relationship between the measurement beams by executing the functions of the units in the above-mentioned electronic device 1700. In addition, even if the prediction beam is not in the set of multiple measurement beams, the prediction beam can be correctly indicated.

[0210] The technology of the present disclosure may also be implemented as an in-vehicle system (or vehicle) 940 including a car navigation device 920, an in-vehicle network 941, and one or more blocks in a vehicle module 942. The vehicle module 942 generates vehicle data (such as vehicle speed, engine speed, and fault information), and outputs the generated data to the in-vehicle network 941.

[0211] The basic principles of the present invention are described above in conjunction with specific embodiments. However, it should be pointed out that for those skilled in the art, it is understandable that all or any steps or components of the method and device of the present invention can be implemented in any computing device (including a processor, storage medium, etc.) or a network of computing devices in the form of hardware, firmware, software, or a combination thereof. This can be achieved by those skilled in the art using their basic circuit design knowledge or basic programming skills after reading the description of the present invention.

[0212] Furthermore, the present invention also provides a program product storing machine-readable instruction codes. When the instruction codes are read and executed by a machine, the method according to the embodiment of the present invention can be executed.

[0213] Accordingly, the storage medium for carrying the program product storing the machine-readable instruction code is also included in the disclosure of the present invention. The storage medium includes but is not limited to a floppy disk, an optical disk, a magneto-optical disk, a memory card, a memory stick, and the like.

[0214] When the present invention is implemented by software or firmware, the data is transferred from a storage medium or a network to a computer (eg, Fig.24 The general-purpose computer 2400 shown in the figure is installed with the programs constituting the software, and when the various programs are installed, the computer can execute various functions, etc.

[0215] exist Fig.24 In the embodiment of the present invention, a central processing unit (CPU) 2401 performs various processes according to a program stored in a read-only memory (ROM) 2402 or a program loaded from a storage section 2408 to a random access memory (RAM) 2403. In the RAM 2403, data required when the CPU 2401 performs various processes and the like is also stored as needed. The CPU 2401, the ROM 2402, and the RAM 2403 are connected to each other via a bus 2404. An input / output interface 2405 is also connected to the bus 2404.

[0216] The following components are connected to the input / output interface 2405: an input section 2406 (including a keyboard, a mouse, etc.), an output section 2407 (including a display such as a cathode ray tube (CRT), a liquid crystal display (LCD), etc., and a speaker, etc.), a storage section 2408 (including a hard disk, etc.), a communication section 2409 (including a network interface card such as a LAN card, a modem, etc.). The communication section 2409 performs communication processing via a network such as the Internet. A drive 2410 may also be connected to the input / output interface 2405 as needed. A removable medium 2411 such as a magnetic disk, an optical disk, a magneto-optical disk, a semiconductor memory, etc. is installed on the drive 2410 as needed, so that a computer program read out therefrom is installed in the storage section 2408 as needed.

[0217] In the case where the above-described series of processing is realized by software, a program constituting the software is installed from a network such as the Internet or a storage medium such as the removable medium 2411 .

[0218] It should be understood by those skilled in the art that such storage media is not limited to Fig.24 The removable medium 2411 shown has a program stored therein and is distributed separately from the device to provide the program to the user. Examples of the removable medium 2411 include magnetic disks (including floppy disks (registered trademark)), optical disks (including compact disk read-only memory (CD-ROM) and digital versatile disks (DVD)), magneto-optical disks (including minidiscs (MD) (registered trademark)), and semiconductor memories. Alternatively, the storage medium may be a ROM 2402, a hard disk included in the storage portion 2408, or the like, in which the program is stored and distributed to the user together with the device containing them.

[0219] It should also be noted that in the apparatus, method and system of the present invention, each component or each step can be decomposed and / or recombined. These decompositions and / or recombinations should be regarded as equivalent solutions of the present invention. In addition, the steps of performing the above series of processes can naturally be performed in chronological order according to the order of description, but do not necessarily need to be performed in chronological order. Some steps can be performed in parallel or independently of each other.

[0220] Finally, it should be noted that the terms "comprises", "includes" or any other variations thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device that includes a series of elements includes not only those elements, but also includes other elements not explicitly listed, or also includes elements inherent to such process, method, article or device. In addition, in the absence of more restrictions, the elements defined by the sentence "comprises a ..." do not exclude the existence of other identical elements in the process, method, article or device that includes the elements.

[0221] Although the embodiments of the present invention are described in detail above in conjunction with the accompanying drawings, it should be understood that the above-described embodiments are only used to illustrate the present invention and do not constitute a limitation of the present invention. For those skilled in the art, various modifications and changes can be made to the above-mentioned embodiments without departing from the essence and scope of the present invention. Therefore, the scope of the present invention is limited only by the attached claims and their equivalent meanings.

[0222] The present technology can also be implemented as follows.

[0223] Solution 1. An electronic device for wireless communication, comprising:

[0224] The processing circuit is configured to:

[0225] performing beam measurement based on a plurality of measurement beams having a predetermined interval with a user equipment within a service range of the electronic device to obtain measurement results for the plurality of measurement beams, and

[0226] Via a prediction model for predicting a beam pair to be used by the electronic device to communicate with the user equipment, a predicted beam in the predicted beam pair predicted by the prediction model based on the measurement result is obtained, wherein the predicted beam is indicated by a relative position relationship with a specific measurement beam among the multiple measurement beams.

[0227] Solution 2. An electronic device according to Solution 1, wherein the interval is an interval between beam IDs of the multiple measurement beams, and the configuration information about the multiple measurement beams includes the beam ID of a starting beam among the multiple measurement beams and the interval.

[0228] Solution 3. An electronic device according to Solution 1, wherein the interval is the interval between the beam space angles of the multiple measurement beams, and the configuration information about the multiple measurement beams includes the beam space angle of the starting beam in the multiple measurement beams and the interval.

[0229] Solution 4. An electronic device according to Solution 2, wherein the relative position relationship is reflected by a difference between a beam ID of the predicted beam and a beam ID of the specific measurement beam.

[0230] Solution 5. An electronic device according to Solution 3, wherein the relative position relationship is reflected by the difference between the beam space angle of the predicted beam and the beam space angle of the specific measurement beam.

[0231] Solution 6. The electronic device according to Solution 4 or 5, wherein the specific measurement beam is a measurement beam having a maximum corresponding reference signal received power RSRP among the multiple measurement beams.

[0232] Solution 7. An electronic device according to Solution 3, wherein, in a 3D beamforming scenario, a beam space angle of the beam is indicated by a horizontal angle and a vertical angle.

[0233] Solution 8. An electronic device according to Solution 5, wherein, when a beam with a beam space angle pointing to the predicted beam is not supported during communication between the electronic device and the user device, a beam with a minimum difference with the beam space angle of the predicted beam is used for the communication.

[0234] Solution 9. An electronic device according to Solution 3, wherein, when the user equipment supports reporting its absolute geographic location direction, the beam space angle of the beam is the true angle of the beam.

[0235] Solution 10. The electronic device according to Solution 2 or 3, wherein the multiple measurement beams include a wide beam and a narrow beam, and configuration information of the wide beam and the narrow beam are independent of each other.

[0236] Solution 11. The electronic device according to Solution 10, wherein:

[0237] The prediction model is based on a convolutional neural network, and

[0238] The measurement result for the wide beam and the measurement result for the narrow beam are used as inputs of different channels of the convolutional neural network for prediction by the convolutional neural network.

[0239] Solution 12. The electronic device according to any one of Solution 1 to Solution 11, wherein:

[0240] When the difference between the reference signal received power RSRP corresponding to the predicted beam output by the prediction model and the RSPR obtained by measuring based on the predicted beam is greater than or equal to a predetermined difference threshold, the number of the predicted beams is increased and / or the number of the multiple measurement beams is increased.

[0241] Solution 13. The electronic device according to any one of Solution 1 to Solution 11, wherein:

[0242] When the difference between the reference signal received power RSRP corresponding to the predicted beam output by the prediction model and the RSPR obtained by measuring based on the predicted beam is less than a predetermined difference threshold, the number of predicted beams is reduced and / or the number of the multiple measurement beams is reduced.

[0243] Solution 14. The electronic device according to any one of Solution 1 to Solution 13, wherein:

[0244] In the case where the prediction model is deployed on the electronic device side:

[0245] The multiple measurement beams are receiving beams on the user equipment side, and

[0246] The processing circuit is configured to predict the predicted beam as the receiving beam in the predicted beam pair using the prediction model, and feed back an indication of the predicted beam to the user equipment.

[0247] Solution 15. The electronic device according to any one of Solution 1 to Solution 13, wherein:

[0248] In the case where the prediction model is deployed on the user equipment side:

[0249] The multiple measurement beams are transmission beams on the electronic device side, and the user equipment predicts the predicted beam as the transmission beam in the predicted beam pair using the prediction model; and

[0250] The processing circuit is configured to receive an indication of the predicted beam from the user equipment.

[0251] Solution 16. An electronic device for wireless communication, comprising:

[0252] The processing circuit is configured to:

[0253] performing beam measurement based on a plurality of measurement beams having a predetermined interval with a network-side device providing a service for the electronic device to obtain measurement results for the plurality of measurement beams, and

[0254] Via a prediction model for predicting a beam pair to be used by the electronic device to communicate with the network side device, a predicted beam in the predicted beam pair predicted by the prediction model based on the measurement result is obtained, wherein the predicted beam is indicated by a relative position relationship with a specific measurement beam among the multiple measurement beams.

[0255] Solution 17. An electronic device according to Solution 16, wherein the interval is an interval between beam IDs of the multiple measurement beams, and the configuration information about the multiple measurement beams includes the beam ID of a starting beam among the multiple measurement beams and the interval.

[0256] Option 18. An electronic device according to Option 16, wherein the interval is the interval between the beam space angles of the multiple measurement beams, and the configuration information about the multiple measurement beams includes the beam space angle of the starting beam in the multiple measurement beams and the interval.

[0257] Solution 19. An electronic device according to Solution 17, wherein the relative position relationship is reflected by the difference between the beam ID of the predicted beam and the beam ID of the specific measurement beam.

[0258] Solution 20. An electronic device according to Solution 18, wherein the relative position relationship is reflected by the difference between the beam space angle of the predicted beam and the beam space angle of the specific measurement beam.

[0259] Solution 21. An electronic device according to Solution 19 or 20, wherein the specific measurement beam is a measurement beam having a maximum corresponding reference signal received power RSRP among the multiple measurement beams.

[0260] Embodiment 22. An electronic device according to Embodiment 18, wherein, in a 3D beamforming scenario, a beam space angle of the beam is indicated by a horizontal angle and a vertical angle.

[0261] Scheme 23. An electronic device according to Scheme 20, wherein, when a beam with a beam space angle pointing to the predicted beam is not supported during communication between the electronic device and the network side device, a beam with a minimum difference with the beam space angle of the predicted beam is used for the communication.

[0262] Solution 24. An electronic device according to Solution 17 or 18, wherein the multiple measurement beams include a wide beam and a narrow beam, and configuration information of the wide beam and the narrow beam are independent of each other.

[0263] Solution 25. The electronic device according to Solution 24, wherein:

[0264] The prediction model is a convolutional neural network, and

[0265] The measurement result for the wide beam and the measurement result for the narrow beam are used as inputs of different channels of the convolutional neural network for the convolutional neural network to make predictions.

[0266] Solution 26. The electronic device according to any one of Solution 16 to Solution 25, wherein:

[0267] When the difference between the reference signal received power RSRP corresponding to the predicted beam output by the prediction model and the RSPR obtained by measuring based on the predicted beam is greater than or equal to a predetermined difference threshold, the number of the predicted beams is increased and / or the number of the multiple measurement beams is increased.

[0268] Solution 27. The electronic device according to any one of Solution 16 to Solution 25, wherein:

[0269] When the difference between the reference signal received power RSRP corresponding to the predicted beam output by the prediction model and the RSPR obtained by measuring based on the predicted beam is less than a predetermined difference threshold, the number of predicted beams is reduced and / or the number of the multiple measurement beams is reduced.

[0270] Solution 28. A method for wireless communication, comprising:

[0271] performing beam measurement based on a plurality of measurement beams having a predetermined interval with a user equipment within a service range of the electronic equipment to obtain measurement results for the plurality of measurement beams, and

[0272] Via a prediction model for predicting a beam pair to be used by the electronic device to communicate with the user equipment, a predicted beam in the predicted beam pair predicted by the prediction model based on the measurement result is obtained, wherein the predicted beam is indicated by a relative position relationship with a specific measurement beam among the multiple measurement beams.

[0273] Solution 29. A method for wireless communication, comprising:

[0274] performing beam measurement based on a plurality of measurement beams having a predetermined interval with a network-side device providing a service for the electronic device to obtain measurement results for the plurality of measurement beams, and

[0275] Via a prediction model for predicting a beam pair to be used by the electronic device to communicate with the network side device, a predicted beam in the predicted beam pair predicted by the prediction model based on the measurement result is obtained, wherein the predicted beam is indicated by a relative position relationship with a specific measurement beam among the multiple measurement beams.

[0276] Embodiment 30: A computer-readable storage medium having computer-executable instructions stored thereon. When the computer-executable instructions are executed, the method for wireless communication according to Embodiment 28 or 29 is performed.

Claims

1. An electronic device for wireless communication, comprising: The processing circuit is configured to: performing beam measurement with a user equipment within a service range of the electronic device based on a plurality of measurement beams having a predetermined interval to obtain measurement results for the plurality of measurement beams, and Via a prediction model for predicting a beam pair to be used by the electronic device to communicate with the user equipment, a predicted beam in the predicted beam pair predicted by the prediction model based on the measurement result is obtained, wherein the predicted beam is indicated by a relative position relationship with a specific measurement beam among the multiple measurement beams.

2. The electronic device according to claim 1, wherein: The interval is an interval between beam IDs of the plurality of measurement beams, and the configuration information about the plurality of measurement beams includes the beam ID of a start beam among the plurality of measurement beams and the interval.

3. The electronic device according to claim 1, wherein: The interval is an interval between beam space angles of the plurality of measurement beams, and the configuration information about the plurality of measurement beams includes the beam space angle of a starting beam among the plurality of measurement beams and the interval.

4. The electronic device according to claim 2, wherein: The relative position relationship is reflected by the difference between the beam ID of the prediction beam and the beam ID of the specific measurement beam.

5. The electronic device according to claim 3, wherein: The relative position relationship is reflected by the difference between the beam space angle of the prediction beam and the beam space angle of the specific measurement beam.

6. The electronic device according to claim 4 or 5, wherein: The specific measurement beam is a measurement beam having a maximum reference signal received power RSRP corresponding to the specific measurement beam among the multiple measurement beams.

7. An electronic device for wireless communication, comprising: The processing circuit is configured to: performing beam measurement based on a plurality of measurement beams having a predetermined interval with a network-side device providing a service for the electronic device to obtain measurement results for the plurality of measurement beams, and Via a prediction model for predicting a beam pair to be used by the electronic device to communicate with the network side device, a predicted beam in the predicted beam pair predicted by the prediction model based on the measurement result is obtained, wherein the predicted beam is indicated by a relative position relationship with a specific measurement beam among the multiple measurement beams.

8. A method for wireless communication, comprising: performing beam measurement based on a plurality of measurement beams having a predetermined interval with a user equipment within a service range of the electronic equipment to obtain measurement results for the plurality of measurement beams, and Via a prediction model for predicting a beam pair to be used by the electronic device to communicate with the user equipment, a predicted beam in the predicted beam pair predicted by the prediction model based on the measurement result is obtained, wherein the predicted beam is indicated by a relative position relationship with a specific measurement beam among the multiple measurement beams.

9. A method for wireless communication, comprising: performing beam measurement based on a plurality of measurement beams having a predetermined interval with a network-side device providing a service for the electronic device to obtain measurement results for the plurality of measurement beams, and Via a prediction model for predicting a beam pair to be used by the electronic device to communicate with the network side device, a predicted beam in the predicted beam pair predicted by the prediction model based on the measurement result is obtained, wherein the predicted beam is indicated by a relative position relationship with a specific measurement beam among the multiple measurement beams.

10. A computer-readable storage medium having computer-executable instructions stored thereon, and when the computer-executable instructions are executed, the method for wireless communication according to claim 8 or 9 is executed.

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