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

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

[0001] This application claims priority to the Chinese patent application filed with the China Patent Office on September 25, 2023, with application number 202311245297.3 and invention name “Electronic device and method for wireless communication and computer-readable storage medium”, the entire contents of which are incorporated by reference into this application. Technical Field

[0002] The present disclosure relates to the field of wireless communication technology, and more particularly 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

[0003] To overcome the significant path loss in millimeter-wave and higher frequency bands, large-scale antenna arrays are typically deployed at the transceiver end, supplemented by beamforming technology. By adjusting the phase of the antenna array, beamforming technology enables the antenna to emit or receive beams in a directional manner, thereby achieving beamforming gain.

[0004] Typically, transmitters and receivers have a large number of available orthogonal beams. Therefore, finding the optimal beam pair from the Cartesian product of all transmit and receive beams is a challenging search problem. Current NR (New Radio) beam management schemes leverage the gain dependency between wide and narrow beams to implement a hierarchical beam search approach. This approach consists of three phases. This means that beam measurement overhead in traditional beam management methods is high, requiring multiple measurements across three phases. Figure 1 illustrates the first phase of NR beam scanning. As shown in Figure 1, in the first phase, the base station performs initial beam scanning using a wide beam, while the user uses a wide beam for reception. Traditional hierarchical beam scanning methods are highly sensitive to noise; if errors occur in the wide beam measurement during the first phase, overall performance can be severely impacted. Figure 2 illustrates the second phase of NR beam scanning. As shown in Figure 2, in the second phase, the base station selects a narrow beam for fine-tuning beam scanning based on the Channel State Information Reference Signal (CSI-RS), while the user continues to use a wide beam for reception. Figure 3 is a schematic diagram showing the third stage of NR beam scanning. As shown in Figure 3, 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 Second beam scan, where N w is the number of base station wide beams, N rN is the number of narrow beams under each wide beam of the base station, Rx is the number of narrow beams for the user, which will bring about a large beam measurement overhead.

[0005] With the development of artificial intelligence (AI), deep learning has emerged as a powerful approach to solving beam prediction problems. This approach primarily measures the Reference Signal Received Power (RSRP) of selected beam pairs and leverages the powerful fitting capabilities of deep learning to predict the RSRP of other beam pairs or directly predict the optimal beam. Generally speaking, deep learning methods can predict the optimal beam with only a very small number of K beam pairs' RSRP measurements, significantly reducing beam measurement overhead compared to NR beam management solutions.

[0006] Existing AI prediction solutions primarily focus on predicting a single transmit or receive beam. In traditional beam management solutions or single-beam prediction solutions, the measurement beam can be arbitrarily configured, and feedback on measurement results simply requires indicating the optimal measurement beam based on the resource blocks of the measurement beam. The difficulty of beam pair prediction when the model is deployed at a single base station (or user) is that, in AI-based beam pair prediction methods, the AI ​​model's input includes not only the RSRP of the measurement beam but also the relative relationship between the measurement beams. If the model and the measurement beam configuration module 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 measurement beam configuration in traditional beam management solutions requires adjustment. Furthermore, the optimal predicted beam output by the model is not necessarily included in the measurement beam. Therefore, the method of indicating the measurement beam's resource blocks in traditional beam management also requires adjustment.

[0007] Summary of the Invention

[0008] A brief overview of the present invention is provided below 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 aspects of the present invention, nor is it intended to limit the scope of the present invention. Its purpose is simply to present certain concepts in a simplified form as a prelude to the more detailed description discussed later.

[0009] According to one aspect of the present disclosure, an electronic device for wireless communication is provided, 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 multiple measurement beams having predetermined intervals to obtain measurement results for the multiple measurement beams; and obtain, via a prediction model for predicting a beam pair to be used by the electronic device for communication with 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 positional relationship with a specific measurement beam in the multiple 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 further, even if the predicted beam is not in the set of multiple measurement beams, the predicted beam can be correctly indicated.

[0010] According to one aspect of the present disclosure, an electronic device for wireless communication is provided, comprising a processing circuit, the processing circuit being configured to: perform beam measurement based on a plurality of measurement beams having predetermined intervals with a network-side device providing a service for the electronic device to obtain measurement results for the plurality of measurement beams; and obtain, 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 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 further, even if the predicted beam is not in the set of the plurality of measurement beams, the predicted beam can be correctly indicated.

[0011] According to one aspect of the present disclosure, a method for wireless communication is provided, comprising: performing beam measurement with a user equipment 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 equipment, a predicted beam in the predicted beam pair predicted by the prediction model based on the measurement results, wherein the predicted beam is indicated by a relative positional relationship with a specific measurement beam in the multiple measurement beams.

[0012] 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 that provides 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 the predicted beam pair predicted by the prediction model based on the measurement results, wherein the predicted beam is indicated by a relative positional relationship with a specific measurement beam in the multiple measurement beams.

[0013] According to other aspects of the present invention, a computer program code and a computer program product for implementing the above-mentioned method for wireless communication, as well as a computer-readable storage medium having the computer program code for implementing the above-mentioned method for wireless communication recorded thereon are also provided. BRIEF DESCRIPTION OF THE DRAWINGS

[0014] In order to further illustrate the above and other advantages and features of the present invention, the following is a further detailed description of specific embodiments of the present invention in conjunction with the accompanying drawings. The accompanying drawings, together with the detailed description below, 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 depict typical examples of the present invention and should not be regarded as limiting the scope of the present invention. In the drawings:

[0015] FIG1 is a schematic diagram illustrating the first stage of NR beam scanning;

[0016] FIG2 is a schematic diagram illustrating the second stage of NR beam scanning;

[0017] FIG3 is a schematic diagram illustrating the third stage of NR beam scanning;

[0018] FIG4 shows a functional module block diagram of an electronic device for wireless communication according to an embodiment of the present disclosure;

[0019] FIG5 is a schematic diagram illustrating a beam measurement configuration based on a beam ID according to an embodiment of the present disclosure;

[0020] FIG6 is a schematic diagram illustrating a beam measurement configuration based on beam angle according to an embodiment of the present disclosure;

[0021] FIG7 is a schematic diagram illustrating a beam measurement configuration supporting wide beams and narrow beams according to an embodiment of the present disclosure;

[0022] FIG8 is a schematic diagram illustrating a prediction model based on a neural network according to an embodiment of the present disclosure;

[0023] FIG9 is a schematic diagram illustrating an input of a prediction model according to an embodiment of the present disclosure;

[0024] FIG10 is a schematic diagram illustrating an output of a prediction model based on a beam ID according to an embodiment of the present disclosure;

[0025] FIG11 is a schematic diagram illustrating an output of a prediction model based on beam space angle according to an embodiment of the present disclosure;

[0026] FIG12 is an example of a flowchart illustrating information interaction between an electronic device and a user device when a prediction model is deployed on the electronic device side;

[0027] FIG13 is an example of a flowchart illustrating information interaction between an electronic device and a user device when a prediction model is deployed on the user device side;

[0028] FIG14 is a schematic diagram illustrating an O1 scenario of DeepMIMO;

[0029] FIG15 is a diagram showing simulation results regarding prediction accuracy;

[0030] FIG16 is a diagram showing simulation results regarding normalized beam gain;

[0031] FIG17 shows a functional module block diagram of an electronic device for wireless communication according to another embodiment of the present disclosure;

[0032] FIG18 shows a flowchart of a method for wireless communication according to one embodiment of the present disclosure;

[0033] FIG19 shows a flowchart of a method for wireless communication according to another embodiment of the present disclosure;

[0034] FIG20 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 may be applied;

[0035] FIG21 is a block diagram illustrating a second example of a schematic configuration of an eNB or gNB to which the technology of the present disclosure may be applied;

[0036] FIG22 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;

[0037] FIG23 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

[0038] 24 is a block diagram of an exemplary structure of a general-purpose personal computer in which the method and / or apparatus and / or system according to embodiments of the present invention may be implemented. DETAILED DESCRIPTION

[0039] Exemplary embodiments of the present invention are described below with reference to the accompanying drawings. For the sake of clarity and conciseness, not all features of an actual implementation are described in this specification. However, it should be understood that in the process of developing any such actual implementation, many implementation-specific decisions must be made in order to achieve the developer's specific goals, such as meeting system and business-related constraints, which may vary from implementation to implementation. Furthermore, it should be understood that while development work may be complex and time-consuming, it will be a routine task for those skilled in the art who benefit from this disclosure.

[0040] It is also necessary to explain here that, in order to avoid obscuring the present invention due to unnecessary details, the accompanying drawings only show the device structure and / or processing steps that are closely related to the solution according to the present invention, while other details that are not closely related to the present invention are omitted.

[0041] FIG4 shows a functional module block diagram of an electronic device 400 for wireless communication according to an embodiment of the present disclosure.

[0042] As shown in Figure 1, 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 can also be called an artificial intelligence model) for predicting the 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.

[0043] 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 chips or processors, for example. Furthermore, it should be understood that the various functional units in the electronic device 400 shown in FIG4 are merely logical modules divided according to the specific functions they implement, and are not intended to limit specific implementation methods.

[0044] The electronic device 400 can, for example, be arranged on the base station side or 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), etc. 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.

[0045] As an example, the base station may be, for example, an eNB or a gNB.

[0046] 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. Furthermore, 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). Furthermore, those skilled in the art will appreciate that the wireless communication system according to the present disclosure may also be a 4G or 3G communication system.

[0047] In the electronic device 400 according to an embodiment of the present disclosure, multiple measurement beams are set to have a predetermined interval, so that the multiple measurement beams meet a specific beam configuration (also referred to as a beam measurement configuration).

[0048] For example, the predetermined interval may be determined according to an application scenario.

[0049] 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.

[0050] In existing technologies, when using artificial intelligence (AI) to perform beam measurement, the transmitter transmits the entire transmit (Tx) beam set, while the receiver measures RSRP for only a subset of these beams. In this case, all Tx beams on the transmitter can be indicated by resource blocks. However, transmitting all Tx beams results in high transmission time overhead. This is because the beams to be measured often occupy a small portion of the entire beam set, resulting in high transmission overhead.

[0051] The beam pair referred to in the present invention includes a transmit beam and a receive beam that form a communication link. The transmitter and the receiver can simultaneously know which specific transmit beam and receive beam are, that is, the transmitter knows which receive beam is based on information provided by the receiver when it knows which transmit beam is, and the receiver knows which transmit beam is based on information provided by the transmitter when it knows which receive beam is. Alternatively, the transmitter and the receiver may only know which beam they are using, that is, the receiver does not provide information about the receive beam to the transmitter, so that the transmitter only knows which transmit beam is but not which receive beam is, and the transmitter does not provide information about the transmit beam to the receiver, so that the receiver only knows which receive beam is but not which transmit beam is.

[0052] According to embodiments of the present disclosure, during the beam measurement phase, measurements are performed using flexibly configured measurement beams that meet predetermined intervals, enabling the prediction model to clearly understand the relative relationships between measurement beams. During the predicted beam feedback phase, the predicted beam is indicated by its relative positional relationship with a specific measurement beam among multiple measurement beams. This ensures accurate prediction of the predicted beam even if the predicted beam is not included in the set of measurement beams.

[0053] As an example, the specific measurement beam may be the measurement beam (optimal measurement beam) with the highest corresponding reference signal received power (RSRP) among multiple measurement beams. The optimal measurement beam may be an example of a specific measurement beam. Those skilled in the art may also conceive of other examples of specific measurement beams, which are not detailed here. Hereinafter, the specific measurement beam may sometimes be referred to as the optimal measurement beam.

[0054] 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 scenarios where the prediction model is deployed on the user equipment side and the electronic device 400 side respectively.

[0055] 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 the predicted beam as the transmitting beam in the predicted beam pair, and the beam obtaining unit 403 can be configured to receive an indication about the predicted beam from the user device.

[0056] For example, when 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. The electronic device 400 can use the Tx beam to transmit in sequence (for example, in a clockwise or counterclockwise order), and the user equipment can receive using 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 predicted Tx beam (i.e., the predicted beam as the Tx beam) from the user equipment.

[0057] 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 the predicted beam as the receiving beam in the predicted beam pair, and feed back an indication of the predicted beam to the user device.

[0058] 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 sequence (for example, in a clockwise or counterclockwise order), while the electronic device 400 can transmit using any Tx beam. The predicted beam is the Rx beam in the predicted beam pair predicted by the prediction model. The electronic device 400 can feed back an indication of the predicted Rx beam (i.e., the predicted beam as the Rx beam) to the user equipment.

[0059] As an example, the above-mentioned interval is the interval between the 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.

[0060] 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 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 predicted beam based on the beam measurement configuration information and using the prediction model.

[0061] When the prediction model is deployed on the electronic device 400 side, the user equipment can, for example, select the starting beam ID and beam ID measurement interval in the measurement configuration information of the relevant Rx beam according to the application scenario. For example, the user equipment uses 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 to the beam ID and 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.

[0062] 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) uses 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.

[0063] Figure 5 is a schematic diagram illustrating a beam measurement configuration based on beam IDs according to an embodiment of the present disclosure. Figure 5 illustrates beams with beam IDs ranging from ID0 to ID8. Taking 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; and in beam measurement configuration 3, the starting beam ID is ID0, the beam ID measurement interval is 2, and K is 5.

[0064] As an example, the relative positional relationship between the prediction beam and the 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.

[0065] 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 solution, 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 relative predicted beam position information can be added to the reportQuantity CHOICE in the CSI-ReportConfig of the RRC.

[0066] For example, assuming the measurement beam IDs are 4, 6, and 8, and beam measurements are performed on resource blocks 1, 2, and 3, respectively, the optimal measurement beam has a beam ID of 6, the optimal predicted beam (e.g., the predicted beam with the highest prediction probability) has a beam ID of 7, and the suboptimal predicted beam (e.g., the predicted beam with the second highest prediction probability) has a beam ID of 9. During feedback, the optimal measurement beam is indicated by the second resource block, and the relative relationship between the optimal predicted beam and the measurement beam is indicated by feedback of +1 (+1 = 7 - 6) and +3 (+3 = 9 - 6).

[0067] As can be seen from the above description, 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).

[0068] 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.

[0069] 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 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.

[0070] When the prediction model is deployed on the electronic device 400 side, the user equipment can, for example, select the beam spatial angle and beam angle measurement interval of the starting beam in the measurement configuration information of the relevant Rx beam according to the application scenario. For example, the user equipment uses the beam spatial angle of the starting beam as the starting point and selects K beams as multiple Rx measurement beams at a determined fixed spatial angle interval. The user equipment sends the beam measurement configuration information to the electronic device 400, so that the electronic device 400 can match the beam spatial angle with 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.

[0071] 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.

[0072] FIG6 is a schematic diagram illustrating a beam measurement configuration based on beam angle according to an embodiment of the present disclosure. FIG6 shows beams with spatial angles of -60°, -45°, -30°, -15°, 0°, 15°, 30°, 45°, and 60°, respectively. Taking 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.

[0073] As an example, the relative positional relationship between the prediction beam and the 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.

[0074] In existing 5G solutions, the first phase (P1), second phase (P2), and third phase (P3) of beam scanning are defined in 3GPP TR 38.802-6.1.6.1. According to embodiments of the present disclosure, the order and selection of transmit or receive beams in these three phases can be modified through beam measurement configuration.

[0075] As an example, 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.

[0076] For example, during the beam measurement phase, the measurement beam can include both wide and narrow beams. If the measurement beam includes both wide and narrow beams, the beam measurement configuration information for the wide and narrow beams must be determined separately, and then measurements of the wide and narrow beams must be performed sequentially. The beam measurement configuration information for the wide beam and the beam measurement configuration information for the narrow beam can be selected independently. This supports beam sets defined by different beam measurement configurations, enabling convenient, flexible, and efficient beam measurement.

[0077] For example, in the beam ID method, 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 the measurement beams with beam IDs W2, W4, N4, N5, and N6 in turn for beam measurement.

[0078] FIG7 is a schematic diagram illustrating a beam measurement configuration supporting wide beams and narrow beams according to an embodiment of the present disclosure. FIG7 illustrates narrow beams with beam IDs ID0 to ID8 and wide beams with beam IDs WID 0 to WID 3. Taking the Tx beam as an example, in the wide beam measurement configuration 2 + narrow beam measurement configuration 1 shown in FIG7 , the wide beam has a starting beam ID of WID0, a beam angle measurement interval of 1, and a beam number of 4, while the narrow beam has a starting beam ID of ID0, a beam angle measurement interval of 4, and a beam number of 3. In the wide beam measurement configuration 1 + narrow beam measurement configuration 3 shown in FIG7 , the wide beam has a starting beam ID of WID0, a beam angle measurement interval of 2, and a beam number of 2, while the narrow beam has a starting beam ID of ID0, a beam angle measurement interval of 2, and a beam number of 5.

[0079] 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.

[0080] In the measurement, prediction, and feedback method for spatial beam angles, in scenarios supporting 3D beamforming, the directional angles of beam measurement and feedback, as well as the number of measurements, may be indicated by horizontal and vertical angles.

[0081] For example, if the beam measurement configuration information is: the starting beam angle is: 10° vertical, 30° horizontal (represented as (10°, 30°)), the beam angle measurement interval is: 5° vertical, 5° horizontal, and the number of measurements is 2 vertical, 3 horizontal, 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.

[0082] As an example, when the electronic device 400 and the user device do not support a beam pointing to the beam spatial angle of the predicted beam during communication, the beam with the smallest difference from the beam spatial angle of the predicted beam is used for communication. This makes it possible to determine the correspondence between the spatial angle of the predicted beam and the actual beam used for communication. 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 with the smallest difference from the beam spatial angle of the predicted beam for communication.

[0083] The user equipment can report its absolute geographical location by reporting its absolute geographical 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 geographical 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 geographical 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 geographical 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 geographical location of the user equipment in advance.

[0084] As can be seen from the above description, according to the embodiment 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).

[0085] As an example, the prediction model can 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. As shown in Figure 8, 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 dotted 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.

[0086] Figure 9 is a schematic diagram illustrating the input of a prediction model according to an embodiment of the present disclosure. As shown in Figure 9, 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). The corresponding input of unmeasured beam pairs is 0.

[0087] Figure 10 is a schematic diagram showing the output of a prediction model based on beam IDs according to an embodiment of the present disclosure. As shown in Figure 10, both the Tx beam and the Rx beam are indicated by beam IDs (e.g., ID0 to ID8), and the RSRP values ​​of the "measured beam pairs" shown in Figure 10 are the same as the RSRP values ​​of the corresponding positions in Figure 9. The output of the prediction model includes: a predicted RSRP value of 3.0 for the beam pair including the Tx beam of ID4 and the Rx beam of ID0, and a predicted RSRP value of 3.2 for the beam pair including the Tx beam of ID5 and the Rx beam of ID0. Since the predicted RSRP value of the beam pair including the Tx beam of ID5 and the Rx beam of ID0 is the largest, this beam pair can be predicted as the optimal predicted beam pair.

[0088] FIG11 is a schematic diagram illustrating the output of a prediction model based on beam spatial angle according to an embodiment of the present disclosure. As shown in FIG11 , both the Tx beam and the Rx beam are indicated by beam spatial angle, and the RSRP values ​​of the "measured beam pairs" shown in FIG11 are the same as the RSRP values ​​at the corresponding positions in FIG9 . The output of the prediction model includes: a predicted RSRP value of 3.0 for the beam pair including a Tx beam with a spatial angle of 0° and an Rx beam with a spatial angle of -45°, and a predicted RSRP value of 3.2 for the beam pair including a Tx beam with a spatial angle of 15° and an Rx beam with a spatial angle of -45°. Since the beam pair including a Tx beam with a spatial angle of 15° and an Rx beam with a spatial angle of -45° has the largest predicted RSRP value, this beam pair can be predicted as the optimal predicted beam pair.

[0089] For example, the specific beam prediction process of the prediction model can refer to the process of beam prediction based on a neural network. For example, the neural network can adopt a multi-channel convolutional neural network structure, using convolutional layers and fully connected layers to extract relevant information between beams. As an example, the prediction model can be based on a convolutional neural network, with measurement results for wide beams and measurement results for narrow beams used as inputs to different channels of the convolutional neural network for prediction.

[0090] As an example, if the difference between the RSRP corresponding to the predicted beam output by the prediction model and the RSPR obtained by measurement 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, if the difference between the RSRP corresponding to the predicted beam output by the prediction model and the RSPR obtained by measurement 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.

[0091] Existing AI-based beam prediction methods use a fixed beam configuration for measurement and prediction. The ID of each measurement beam and the order in which the beams are transmitted are fixed. This fixed beam measurement configuration results in limited flexibility. Because the measurement beams and the beams input into the prediction model are fixed, adaptive modification to changing wireless environments is difficult, impacting measurement overhead and prediction performance.

[0092] According to the embodiments of the present disclosure, dynamic configuration of the number of predicted beams and dynamic measurement beams is supported, thereby reducing measurement overhead and communication overhead while ensuring performance.

[0093] FIG12 is an example of a flowchart illustrating information interaction between the electronic device 400 and a user equipment (hereinafter referred to as a user) when a prediction model is deployed on the electronic device 400 (hereinafter referred to as a base station) side.

[0094] In S1, the user and base station perform function and model authentication. For example, the base station and user may exchange at least some of the following information: whether wide beams are 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 transmit beams, the number of receive beams, and the number of prediction model inputs.

[0095] At S2, the base station initializes / modifies the Tx beam pattern. For example, the Tx beam pattern 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 can transmit using any Tx beam.

[0096] 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 user's Rx beam meets the specific beam measurement configuration.

[0097] In S4, the user notifies the base station of beam measurement configuration information of the Rx beam serving as the measurement beam.

[0098] 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.

[0099] In S6 , the base station uses the prediction model to perform beam prediction using the measured RSRP values ​​of the beam pairs.

[0100] At S7, the base station feeds back information about the optimal measurement beam and the optimal predicted beam to the user. For example, the base station indicates the optimal measurement beam based on the resource block and feeds back the difference between the IDs of the optimal predicted beam and the optimal measurement beam, or the difference between the spatial angles of the optimal predicted beam and the optimal measurement beam.

[0101] In S8 , the base station and the user perform RSRP measurements on the predicted beam to obtain RSRP measurement results for the predicted beam, and notify the user of the measurement results.

[0102] 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.

[0103] 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 RSRP value corresponding to the predicted beam output by the prediction model and the actual measured RSRP value obtained in S8.

[0104] As can be seen from FIG12 , 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.

[0105] FIG13 is an example of a flowchart illustrating information interaction between an electronic device 400 (referred to as a base station for short) and a user equipment when a prediction model is deployed on the user equipment (referred to as a user for short) side.

[0106] In S1, the user and base station perform function and model authentication. For example, the base station and user may exchange at least some of the following information: whether wide beams are 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 transmit beams, the number of receive beams, and the number of prediction model inputs.

[0107] 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 meets the specific beam measurement configuration.

[0108] In S3, the user initializes / modifies 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 device side, the user can receive using any Rx beam.

[0109] In S4, the base station notifies the user of beam measurement configuration information of the Tx beam serving as the measurement beam.

[0110] 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 uses the beams in the Rx beam mode to measure the RSRP values ​​of the beam pairs.

[0111] In S6, the user uses the prediction model to perform beam prediction using the measured RSRP value.

[0112] At S7, the user feeds back information about the optimal measurement beam and the optimal predicted beam to the base station. For example, the user may indicate the optimal measurement beam based on the resource block and feed back the difference between the IDs of the optimal predicted beam and the optimal measurement beam, or the difference between the spatial angles of the optimal predicted beam and the optimal measurement beam.

[0113] In S8 , the base station and the user perform RSRP measurements on the predicted beam to obtain RSRP measurement results for the predicted beam, and notify the user of the measurement results.

[0114] In S9, the base station determines whether to adjust the Tx beam measurement configuration information (for example, adjust the number of Tx beams) based on the difference between the predicted RSRP value corresponding to the predicted beam output by the prediction model and the actual measured RSRP value obtained in S8.

[0115] 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.

[0116] As shown in FIG13 , 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.

[0117] In this disclosure, beam prediction is simulated. Considering the transmission scenario under millimeter wave, the O1 scenario of DeepMIMO is used to generate channel data. Figure 14 is a schematic diagram showing the O1 scenario of DeepMIMO. In Figure 14, BS represents a base station, for example, BS12 represents the 12th base station; R represents a 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.

[0118] In the simulation, it is assumed that users are randomly and evenly distributed between R1250 and R1800 (not shown) near "User Grid 1" in Figure 14 in the Deep MIMO scenario. The simulation parameters are shown in the following table.

[0119] In the simulation, three beam prediction methods were considered: 1) The traditional beam scanning method (traditional method): selects M×N beams, measures their RSRP, and selects the beam pair with the highest RSRP among the measured beam pairs. 2) The AI ​​K=1 method: selects M×N beam pairs, measures their RSRP, and feeds the measurement results into the prediction model as input. After obtaining the output, the beam pair with the highest predicted probability is selected as the optimal predicted beam pair. 3) The AI ​​K=3 method: selects M×N beam pairs, measures their RSRP, and feeds the measurement results into the prediction model as input. After obtaining the output, the three beam pairs with the highest predicted probabilities are selected. After beam measurements are performed on these three beams, the beam pair with the highest RSRP is selected as the optimal predicted beam pair.

[0120] Consider two evaluation metrics.

[0121] Evaluation metric 1 is the prediction accuracy: Assuming that the total 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:

[0122]

[0123] 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

[0124]

[0125] The upper limits of the above two evaluation indicators are both 1.

[0126] The loss function of the prediction model adopts the cross entropy loss function, which can be expressed as:

[0127]

[0128] 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 is the optimal prediction beam pair in the prediction output of the prediction model for the x-th sample. The optimizer can adopt the Adam optimizer in the prior art for optimization.

[0129] FIG. 15 is a diagram showing simulation results regarding prediction accuracy.

[0130] In Figure 15, the horizontal axis is written in the format of A×B, where A represents the number of transmit beams on the electronic device 400 side, B represents the number of receive beams on the user device side, 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 side is 8, the number of receive beams measured on the user device side 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 side is 64, and the total number of receive beams available on the user device side is 4. 8×2 means that 8 transmit beams are selected from the 64 transmit beams available on the electronic device 400 side, 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.

[0131] The vertical axis in Figure 15 represents the prediction accuracy.

[0132] As can be seen from FIG15 , in terms of prediction accuracy, the performance of both the AI ​​K=3 method and the AI ​​K=1 method is better than the traditional method, while 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.

[0133] FIG16 is a graph showing simulation results regarding normalized beam gain.

[0134] The representation of the abscissa in FIG16 is the same as that in FIG15 , and the ordinate represents the normalized beam gain.

[0135] As can be seen from FIG16 , in terms of normalized beam gain, both the AI ​​K=3 method and the AI ​​K=1 method perform better than the traditional method, while the AI ​​K=3 method performs better than the AI ​​K=1 method, and the AI ​​K=1 method performs better than the traditional method.

[0136] For each method, more measured beam pairs lead to better performance. However, it can be seen that for the 16×2 and 8×4 configurations, respectively, although the total number of measured beam pairs for both configurations is equal to 32, the normalized beam gain for the 16×2 configuration is better than that for the 8×4 configuration. This is because the 16×2 configuration has more transmit beams, while the 8×4 configuration has more receive beams. Given a fixed number of measured beam pairs, the predicted results for more measured transmit beams can lead to higher beam gains for the system.

[0137] Furthermore, 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.

[0138] The present disclosure further provides an electronic device for wireless communication according to another embodiment. FIG17 shows a functional module block diagram of an electronic device 1700 for wireless communication according to another embodiment of the present disclosure.

[0139] As shown in FIG17 , electronic device 1700 includes: a measurement result obtaining unit 1701, which may be configured to perform beam measurement based on a plurality of measurement beams with a predetermined interval with a network-side device serving electronic device 1700, to obtain measurement results for the plurality of measurement beams; and a predicted beam obtaining unit 1703, which may be configured to obtain, via a prediction model for predicting a beam pair to be used for communication between electronic device 1700 and the network-side device, a predicted beam in a predicted beam pair predicted by a prediction model based on the measurement results, wherein the predicted beam is indicated by a relative positional relationship with a specific measurement beam in the plurality of measurement beams. Furthermore, it should be understood that the various functional units in electronic device 1700 shown in FIG17 are merely logical modules divided according to the specific functions they implement, and are not intended to limit specific implementations.

[0140] The measurement result obtaining unit 1701 and the predicted beam obtaining unit 1703 may be implemented by one or more processing circuits, which may be implemented as a chip, for example.

[0141] The electronic device 1700 can, for example, be arranged on the user equipment side or 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 (for example, base stations, other user equipment, etc.), and the implementation form of the transceiver is not specifically limited here.

[0142] 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. Furthermore, the wireless communication system according to the present disclosure may include a non-terrestrial network. Alternatively, the wireless communication system according to the present disclosure may also include a terrestrial network. Furthermore, those skilled in the art will appreciate that the wireless communication system according to the present disclosure may also be a 4G or 3G communication system.

[0143] 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.

[0144] According to embodiments of the present disclosure, during the beam measurement phase, measurements are performed using flexibly configured measurement beams that meet predetermined intervals, enabling the prediction model to clearly understand the relative relationships between measurement beams. During the predicted beam feedback phase, the predicted beam is indicated by its relative positional relationship with a specific measurement beam among multiple measurement beams. This ensures accurate prediction of the predicted beam even if the predicted beam is not included in the set of measurement beams.

[0145] As an example, the specific measurement beam may be a measurement beam having the largest corresponding reference signal received power RSRP among multiple measurement beams.

[0146] As an example, the interval may be an interval between beam IDs of a plurality of measurement beams, and the configuration information about the plurality of measurement beams includes the beam ID of a starting beam among the plurality of measurement beams and the interval.

[0147] For an example of beam measurement configuration based on beam ID, please refer to the description of Figure 5, which will not be repeated here.

[0148] As an example, the relative positional 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.

[0149] 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.

[0150] For an example of beam measurement configuration based on beam angle, please refer to the description of FIG6 , which will not be repeated here.

[0151] As an example, the relative positional 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.

[0152] As an example, 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.

[0153] For an example of a beam measurement configuration supporting wide beams and narrow beams, please refer to the description of FIG7 , which will not be repeated here.

[0154] 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.

[0155] 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 from the beam space angle of the predicted beam is used for communication.

[0156] 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.

[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 measurement 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.

[0158] As an example, when the difference between the RSRP corresponding to the predicted beam output by the prediction model and the RSPR obtained by measurement 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.

[0159] 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 of the details already 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 adopt 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 computer-executable programs, although these methods can also adopt the hardware and / or firmware of the electronic device for wireless communication.

[0160] FIG18 illustrates a flowchart of a method S1800 for wireless communication according to an embodiment of the present disclosure. Method S1800 begins at step S1802. At step S1804, beam measurement is performed with a user equipment within a service range of the electronic device based on multiple measurement beams with predetermined intervals to obtain measurement results for the multiple measurement beams. At step S1806, a prediction model for predicting a beam pair to be used by the electronic device for communication with the user equipment is used to obtain a predicted beam from a predicted beam pair predicted by the prediction model based on the measurement results, wherein the predicted beam is indicated by its relative positional relationship with a specific measurement beam in the multiple measurement beams. Method S1800 ends at step S1808.

[0161] The method may be executed, for example, by the electronic device 400 described above. For specific details, please refer to the description of the related processing of the electronic device 400, which will not be repeated here.

[0162] FIG19 illustrates a flowchart of a method S1900 for wireless communication according to another embodiment of the present disclosure. Method S1900 begins at step S1902. At step S1904, beam measurement is performed with a network device serving an electronic device based on multiple measurement beams at predetermined intervals to obtain measurement results for the multiple measurement beams. At step S1906, a prediction model for predicting a beam pair to be used by the electronic device for communication with the network device is used to obtain a predicted beam from a predicted beam pair predicted by the prediction model based on the measurement results. The predicted beam is indicated by its relative positional relationship with a specific measurement beam in the multiple measurement beams. Method S1900 ends at step S1908.

[0163] The method may be executed, for example, by the electronic device 1700 described above. For specific details, please refer to the description of the related processing of the electronic device 1700, which will not be repeated here.

[0164] The technology of the present disclosure can be applied to various products.

[0165] 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, micro eNB, and 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 called a base station device) configured to control wireless communications; and one or more remote radio heads (RRHs) arranged at a different place 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.

[0166] The electronic device 1700 may be implemented as various user devices. The user device may be implemented as a mobile terminal (such as a smartphone, a tablet personal computer (PC), a notebook PC, a portable game terminal, a portable / dongle-type mobile router, and a digital camera) or an in-vehicle terminal (such as a car navigation device). The user device may also be implemented as a terminal that performs machine-to-machine (M2M) communication (also known 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.

[0167] [Application examples for base stations]

[0168] (First application example)

[0169] Figure 20 is a block diagram illustrating a first example of a schematic configuration of an eNB or gNB to which the techniques of this disclosure can be applied. Note that the following description uses an eNB as an example, but is equally applicable to gNBs. An 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.

[0170] 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 base station device 820 to transmit and receive wireless signals. As shown in FIG20 , eNB 800 may include multiple antennas 810. For example, multiple antennas 810 may be compatible with multiple frequency bands used by eNB 800. Although FIG20 shows an example in which eNB 800 includes multiple antennas 810, eNB 800 may also include a single antenna 810.

[0171] The base station device 820 includes a controller 821 , a memory 822 , a network interface 823 , and a wireless communication interface 825 .

[0172] 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 data packets based on the data in the signal processed by the wireless communication interface 825, and transmits the generated packets via the network interface 823. The controller 821 may bundle data from multiple baseband processors to generate bundled packets, and transmit the generated bundled packets. The controller 821 may have logic functions for performing the following controls: the control may be 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 RAM and 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).

[0173] 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 than the frequency band used by the wireless communication interface 825.

[0174] The wireless communication interface 825 supports any cellular communication scheme, such as Long Term Evolution (LTE) and LTE-Advanced, and provides wireless connectivity to terminals located in the cell of the eNB 800 via the antenna 810. The wireless communication interface 825 may typically include, for example, a baseband (BB) processor 826 and RF circuitry 827. The BB processor 826 can perform various signal processing functions, such as encoding / decoding, modulation / demodulation, and multiplexing / demultiplexing, and performs various types of signal processing for layers such as Layer 1, Medium Access Control (MAC), Radio Link Control (RLC), and Packet Data Convergence Protocol (PDCP). In place of the controller 821, the BB processor 826 may have some or all of the aforementioned logical functions. The BB processor 826 may be a memory that stores communication control programs, or a module including a processor configured to execute programs and associated circuitry. Program updates can modify the functionality of the BB processor 826. This module may be a card or blade inserted into a slot in the base station device 820. Alternatively, the module may be a chip mounted on the card or blade. Meanwhile, the RF circuit 827 may include, for example, a mixer, a filter, and an amplifier, and transmit and receive wireless signals via the antenna 810 .

[0175] As shown in FIG20 , the wireless communication interface 825 may include multiple BB processors 826. For example, multiple BB processors 826 may be compatible with multiple frequency bands used by the eNB 800. As shown in FIG20 , the wireless communication interface 825 may include multiple RF circuits 827. For example, multiple RF circuits 827 may be compatible with multiple antenna elements. Although FIG20 illustrates an example in which the wireless communication interface 825 includes multiple BB processors 826 and multiple RF circuits 827, the wireless communication interface 825 may also include a single BB processor 826 or a single RF circuit 827.

[0176] When the electronic device 400 is implemented as the eNB 800 shown in FIG. 20 , its transceiver may be implemented by the wireless communication interface 825. At least a portion of the functionality may also be implemented by the controller 821. For example, the controller 821 may execute the functions of the units in the electronic device 400 so that the prediction model can understand the relative relationship between measurement beams and correctly indicate the predicted beam even if the predicted beam is not included in the set of multiple measurement beams.

[0177] (Second application example)

[0178] FIG21 is a block diagram illustrating a second example of a schematic configuration of an eNB or gNB to which the techniques of this disclosure can be applied. Note that similarly, the following description uses an eNB as an example, but is equally applicable to a gNB. An 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.

[0179] 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 RRH 860 to transmit and receive wireless signals. As shown in FIG21, eNB 830 may include multiple antennas 840. For example, multiple antennas 840 may be compatible with multiple frequency bands used by eNB 830. Although FIG21 shows an example in which eNB 830 includes multiple antennas 840, eNB 830 may also include a single antenna 840.

[0180] 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 the same as the controller 821, the memory 822, and the network interface 823 described with reference to FIG.

[0181] The wireless communication interface 855 supports any cellular communication scheme (such as LTE and LTE-Advanced) and provides wireless communication to terminals located in the 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. The BB processor 856 is the same as the BB processor 826 described with reference to FIG. 21, except that the BB processor 856 is connected to the RF circuit 864 of the RRH 860 via the connection interface 857. As shown in FIG. 21, 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. Although FIG. 21 shows an example in which the wireless communication interface 855 includes multiple BB processors 856, the wireless communication interface 855 may also include a single BB processor 856.

[0182] 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 high-speed line.

[0183] The RRH 860 includes a connection interface 861 and a wireless communication interface 863 .

[0184] 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.

[0185] 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. As shown in FIG21 , the wireless communication interface 863 may include multiple RF circuits 864. For example, multiple RF circuits 864 may support multiple antenna elements. Although FIG21 shows an example in which the wireless communication interface 863 includes multiple RF circuits 864, the wireless communication interface 863 may also include a single RF circuit 864.

[0186] When the electronic device 400 is implemented as the eNB 830 shown in FIG. 21 , its transceiver may be implemented by the wireless communication interface 855. At least a portion of the functionality may also be implemented by the controller 851. For example, the controller 851 may execute the functions of the units in the electronic device 400 so that the prediction model can understand the relative relationship between measurement beams and correctly indicate the predicted beam even if the predicted beam is not included in the set of multiple measurement beams.

[0187] [Application examples on user devices]

[0188] (First application example)

[0189] 22 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 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.

[0190] The processor 901 may be, for example, a CPU or a system on a chip (SoC), and controls the functions of the application layer and other layers of the smartphone 900. The memory 902 includes RAM and ROM, and stores data and programs executed by the processor 901. The storage device 903 may include storage media such as semiconductor memories and hard disks. The external connection interface 904 is an interface for connecting external devices (such as memory cards and universal serial bus (USB) devices) to the smartphone 900.

[0191] 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 gyroscope sensor, a geomagnetic sensor, and an acceleration sensor. The microphone 908 converts the sound input to the smartphone 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 the 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 smartphone 900. The speaker 911 converts the audio signal output from the smartphone 900 into sound.

[0192] The wireless communication interface 912 supports any cellular communication scheme (such as LTE and LTE-Advanced) and performs wireless communications. The wireless communication interface 912 may typically 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 may also perform various types of signal processing for wireless communications. Meanwhile, the RF circuit 914 may include, for example, mixers, filters, and amplifiers, and transmit and receive wireless signals via an antenna 916. Note that while the figure shows a scenario where one RF link is connected to one antenna, this is merely illustrative, and also encompasses scenarios where one RF link is connected to multiple antennas via 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 FIG22 , the wireless communication interface 912 may include multiple BB processors 913 and multiple RF circuits 914. While FIG22 illustrates an example in which the wireless communication interface 912 includes multiple BB processors 913 and multiple RF circuits 914, the wireless communication interface 912 may also include a single BB processor 913 or a single RF circuit 914.

[0193] In addition, in addition to the cellular communication scheme, the wireless communication interface 912 can support other types of wireless communication schemes, such as a short-range wireless communication scheme, a near-field communication scheme, and a wireless local area network (LAN) scheme. In this case, the wireless communication interface 912 may include a BB processor 913 and an RF circuit 914 for each wireless communication scheme.

[0194] 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 .

[0195] 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 transmitting and receiving wireless signals via the wireless communication interface 912. As shown in FIG22, the smartphone 900 may include multiple antennas 916. Although FIG22 shows an example in which the smartphone 900 includes multiple antennas 916, the smartphone 900 may also include a single antenna 916.

[0196] 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.

[0197] 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. The battery 918 supplies power to the various blocks of the smartphone 900 shown in FIG. 22 via feeders, which are partially shown as dashed lines in the figure. The auxiliary controller 919 operates the minimum necessary functions of the smartphone 900, for example, in sleep mode.

[0198] When the electronic device 1700 is implemented as a smartphone serving as a user device, such as the smartphone 900 shown in FIG. 22 , the transceiver of the electronic device 1700 may be implemented by the wireless communication interface 912. At least a portion of the functionality may also be implemented by the processor 901 or the auxiliary controller 919. For example, by executing the functions of the aforementioned units in the electronic device 1700, the processor 901 or the auxiliary controller 919 enables the prediction model to clearly understand the relative relationship between measurement beams. Furthermore, even if a predicted beam is not included in the set of multiple measurement beams, the predicted beam can be correctly indicated.

[0199] (Second application example)

[0200] 23 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.

[0201] The processor 921 may be, for example, a CPU or an SoC, and controls a navigation function and other functions of the car navigation apparatus 920. The memory 922 includes a RAM and a ROM, and stores data and programs executed by the processor 921.

[0202] 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 gyroscope sensor, a geomagnetic sensor, and an air pressure sensor. The data interface 926 is connected to, for example, the in-vehicle network 941 via an unillustrated terminal and acquires data generated by the vehicle (such as vehicle speed data).

[0203] The content player 927 reproduces content stored in a storage medium (such as a CD or DVD) inserted into the storage medium interface 928. The input device 929 includes, for example, a touch sensor, button, or switch configured to detect a touch on the screen of the display device 930, and receives an operation or information input from the user. The display device 930 includes a screen such as an LCD or OLED display and displays an image of a navigation function or reproduced content. The speaker 931 outputs the sound of the navigation function or the reproduced content.

[0204] 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. As shown in Figure 23, the wireless communication interface 933 may include multiple BB processors 934 and multiple RF circuits 935. Although Figure 23 shows an example in which the wireless communication interface 933 includes multiple BB processors 934 and multiple RF circuits 935, the wireless communication interface 933 may also include a single BB processor 934 or a single RF circuit 935.

[0205] In addition, in addition to the cellular communication scheme, the wireless communication interface 933 can support other types of wireless communication schemes, such as a short-range wireless communication scheme, a near field communication scheme, and a wireless LAN scheme. In this case, for each wireless communication scheme, the wireless communication interface 933 can include a BB processor 934 and an RF circuit 935.

[0206] 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.

[0207] 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 transmitting and receiving wireless signals via the wireless communication interface 933. As shown in FIG23, the car navigation device 920 may include multiple antennas 937. Although FIG23 shows an example in which the car navigation device 920 includes multiple antennas 937, the car navigation device 920 may also include a single antenna 937.

[0208] 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.

[0209] The battery 938 supplies power to the respective blocks of the car navigation apparatus 920 shown in Fig. 23 via a feeder line, which is partially shown as a dotted line in the figure. The battery 938 accumulates the power supplied from the vehicle.

[0210] When electronic device 1700 is implemented as a user equipment-side car navigation device, such as car navigation device 920 shown in FIG. 23 , the transceiver of electronic device 1700 may be implemented by wireless communication interface 933. At least a portion of the functionality may also be implemented by processor 921. For example, processor 921, by executing the functions of the aforementioned units in electronic device 1700, enables the prediction model to clearly understand the relative relationship between measurement beams and accurately indicates a predicted beam even if the predicted beam is not included in the set of multiple measurement beams.

[0211] The technology of the present disclosure can 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 of 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.

[0212] The basic principles of the present invention are described above in conjunction with specific embodiments. However, it should be pointed out that those skilled in the art will understand that all or any steps or components of the methods and devices 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.

[0213] 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.

[0214] 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.

[0215] When the present invention is implemented through software or firmware, the programs constituting the software are installed from a storage medium or a network to a computer with a dedicated hardware structure (such as the general-purpose computer 2400 shown in Figure 24). When various programs are installed on the computer, it can perform various functions, etc.

[0216] In FIG24 , a central processing unit (CPU) 2401 executes 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 executes various processes, etc., 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.

[0217] 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.), and 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 in the drive 2410 as needed, so that a computer program read therefrom is installed in the storage section 2408 as needed.

[0218] 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 .

[0219] It should be understood by those skilled in the art that such storage media is not limited to the removable medium 2411 shown in FIG. 24 , which stores the program 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 memories (CD-ROMs) and digital versatile disks (DVDs)), magneto-optical disks (including minidiscs (MDs) (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 the program.

[0220] It should also be noted that in the apparatus, method, and system of the present invention, each component or step can be decomposed and / or recombined. Such decomposition and / or recombination should be considered equivalent solutions of the present invention. Furthermore, the steps of performing the above series of processes can naturally be performed in chronological order according to the order described, but do not necessarily need to be performed in chronological order. Certain steps can be performed in parallel or independently of each other.

[0221] Finally, it should be noted that the terms "comprises," "comprising," or any other variations thereof are intended to encompass non-exclusive inclusion, such that a process, method, article, or apparatus that includes a list of elements includes not only those elements but also other elements not explicitly listed, or elements inherent to such process, method, article, or apparatus. Furthermore, in the absence of further limitations, an element defined by the phrase "comprising a ..." does not preclude the presence of additional identical elements in the process, method, article, or apparatus that includes the element.

[0222] Although the embodiments of the present invention have been described in detail above with reference to the accompanying drawings, it should be understood that the embodiments described above are merely illustrative of the present invention and are not intended to limit the present invention. It will be apparent to those skilled in the art that various modifications and variations may be made to the embodiments described above without departing from the spirit and scope of the present invention. Therefore, the scope of the present invention is limited solely by the appended claims and their equivalents.

[0223] The present technology can also be implemented as follows.

[0224] Solution 1. An electronic device for wireless communication, comprising:

[0225] The processing circuit is configured to:

[0226] 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

[0227] 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.

[0228] Solution 2. An electronic device according to Solution 1, wherein the interval is the 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.

[0229] Option 3. An electronic device according to Option 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.

[0230] Solution 4. The electronic device according to Solution 2, 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.

[0231] Solution 5. The 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.

[0232] 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.

[0233] Solution 7. The 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.

[0234] Option 8. An electronic device according to Option 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 from the beam space angle of the predicted beam is used for the communication.

[0235] 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.

[0236] 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.

[0237] Solution 11. The electronic device according to Solution 10, wherein:

[0238] The prediction model is based on a convolutional neural network, and

[0239] 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.

[0240] Solution 12. The electronic device according to any one of Solutions 1 to 11, wherein:

[0241] 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 measurement 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.

[0242] Solution 13. The electronic device according to any one of Solutions 1 to 11, wherein:

[0243] 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 measurement based on the predicted beam is less than a predetermined difference threshold, the number of the predicted beams and / or the number of the multiple measurement beams are reduced.

[0244] Solution 14. The electronic device according to any one of Solutions 1 to 13, wherein:

[0245] When the prediction model is deployed on the electronic device side:

[0246] The multiple measurement beams are receiving beams on the user equipment side, and

[0247] The processing circuit is configured to predict the predicted beam as the receive beam in the predicted beam pair using the prediction model, and feed back an indication of the predicted beam to the user equipment.

[0248] Solution 15. The electronic device according to any one of Solutions 1 to 13, wherein:

[0249] In the case where the prediction model is deployed on the user equipment side:

[0250] The multiple measurement beams are transmission beams on the electronic device side, and the user equipment uses the prediction model to predict the predicted beam as the transmission beam in the predicted beam pair, and

[0251] The processing circuit is configured to receive an indication of the predicted beam from the user equipment.

[0252] Solution 16. An electronic device for wireless communication, comprising:

[0253] The processing circuit is configured to:

[0254] performing beam measurement with a network-side device providing a service for 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

[0255] 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.

[0256] 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.

[0257] 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.

[0258] 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.

[0259] 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.

[0260] Solution 21. The 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.

[0261] Solution 22. An electronic device according to Solution 18, wherein, in a 3D beamforming scenario, a beam space angle of the beam is indicated by a horizontal angle and a vertical angle.

[0262] 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 from the beam space angle of the predicted beam is used to carry out the communication.

[0263] Solution 24. The 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.

[0264] Solution 25. The electronic device according to Solution 24, wherein:

[0265] The prediction model is a convolutional neural network, and

[0266] 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 perform prediction.

[0267] Solution 26. The electronic device according to any one of Solution 16 to Solution 25, wherein:

[0268] 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 measurement 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.

[0269] Solution 27. The electronic device according to any one of Solution 16 to Solution 25, wherein:

[0270] 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 measurement based on the predicted beam is less than a predetermined difference threshold, the number of the predicted beams and / or the number of the multiple measurement beams are reduced.

[0271] Solution 28. A method for wireless communication, comprising:

[0272] 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

[0273] 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.

[0274] Solution 29. A method for wireless communication, comprising:

[0275] performing beam measurement with a network-side device providing a service for 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

[0276] 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.

[0277] Solution 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 Solution 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 corresponding reference signal received power RSRP among the multiple measurement beams.

7. The electronic device according to claim 3, wherein: In a 3D beamforming scenario, the beam space angle of a beam is indicated by a horizontal angle and a vertical angle.

8. The electronic device according to claim 5, wherein: When a beam pointing to the beam space angle of the predicted beam is not supported during communication between the electronic device and the user equipment, the communication is performed using a beam having a minimum difference from the beam space angle of the predicted beam.

9. The electronic device according to claim 3, wherein: In the case where the user equipment supports reporting its absolute geographical location direction, the beam space angle of the beam is the real angle of the beam.

10. The electronic device according to claim 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.

11. The electronic device according to claim 10, wherein: The prediction model is based on a convolutional neural network, and 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.

12. The electronic device according to any one of claims 1 to 11, wherein: 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.

13. The electronic device according to any one of claims 1 to 11, wherein: 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.

14. The electronic device according to any one of claims 1 to 13, wherein: In the case where the prediction model is deployed on the electronic device side: The multiple measurement beams are receiving beams on the user equipment side, and 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.

15. The electronic device according to any one of claims 1 to 13, wherein: In the case where the prediction model is deployed on the user equipment side: 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 The processing circuit is configured to receive an indication of the predicted beam from the user equipment.

16. 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.

17. The electronic device according to claim 16, 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.

18. The electronic device according to claim 16, 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.

19. The electronic device according to claim 17, 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.

20. The electronic device according to claim 18, 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.

21. The electronic device according to claim 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.

22. The electronic device according to claim 18, wherein: In a 3D beamforming scenario, the beam space angle of a beam is indicated by a horizontal angle and a vertical angle.

23. The electronic device according to claim 20, wherein: When a beam pointing to the beam space angle of the predicted beam is not supported during communication between the electronic device and the network side device, the communication is performed using a beam having a minimum difference with the beam space angle of the predicted beam.

24. The electronic device according to claim 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.

25. The electronic device according to claim 24, wherein: The prediction model is a convolutional neural network, and 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.

26. The electronic device according to any one of claims 16 to 25, wherein: 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.

27. The electronic device according to any one of claims 16 to 25, wherein: 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.

28. 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 The electronic device communicates with the user equipment by using a beam pair to be used. A predicted prediction model is used to obtain a predicted beam in a 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.

29. 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.

30. A computer-readable storage medium having computer-executable instructions stored thereon, which, when executed, perform the method for wireless communication according to claim 28 or 29.

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