WO2022213856A1 - 用于无线通信的电子设备和方法、计算机可读存储介质 - Google Patents

用于无线通信的电子设备和方法、计算机可读存储介质 Download PDF

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WO2022213856A1
WO2022213856A1 PCT/CN2022/083974 CN2022083974W WO2022213856A1 WO 2022213856 A1 WO2022213856 A1 WO 2022213856A1 CN 2022083974 W CN2022083974 W CN 2022083974W WO 2022213856 A1 WO2022213856 A1 WO 2022213856A1
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aggregated
beams
electronic device
optimal
aggregation
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PCT/CN2022/083974
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English (en)
French (fr)
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卓寅潇
周郑颐
王昭诚
曹建飞
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索尼集团公司
卓寅潇
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Priority to CN202280026182.2A priority Critical patent/CN117157905A/zh
Publication of WO2022213856A1 publication Critical patent/WO2022213856A1/zh

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    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04B—TRANSMISSION
    • H04B7/00—Radio transmission systems, i.e. using radiation field
    • H04B7/02—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas
    • H04B7/04—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas
    • H04B7/06—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas at the transmitting station
    • H04B7/0613—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas at the transmitting station using simultaneous transmission
    • H04B7/0615—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas at the transmitting station using simultaneous transmission of weighted versions of same signal
    • H04B7/0617—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas at the transmitting station using simultaneous transmission of weighted versions of same signal for beam forming
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04B—TRANSMISSION
    • H04B7/00—Radio transmission systems, i.e. using radiation field
    • H04B7/02—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas
    • H04B7/04—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas
    • H04B7/0408—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas using two or more beams, i.e. beam diversity
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04B—TRANSMISSION
    • H04B7/00—Radio transmission systems, i.e. using radiation field
    • H04B7/02—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas
    • H04B7/04—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas
    • H04B7/06—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas at the transmitting station
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04B—TRANSMISSION
    • H04B7/00—Radio transmission systems, i.e. using radiation field
    • H04B7/02—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas
    • H04B7/04—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas
    • H04B7/06—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas at the transmitting station
    • H04B7/0686—Hybrid systems, i.e. switching and simultaneous transmission
    • H04B7/0695—Hybrid systems, i.e. switching and simultaneous transmission using beam selection
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W74/00—Wireless channel access
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W74/00—Wireless channel access
    • H04W74/002—Transmission of channel access control information
    • H04W74/004—Transmission of channel access control information in the uplink, i.e. towards network
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W74/00—Wireless channel access
    • H04W74/08—Non-scheduled access, e.g. ALOHA
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W74/00—Wireless channel access
    • H04W74/08—Non-scheduled access, e.g. ALOHA
    • H04W74/0833—Random access procedures, e.g. with 4-step access

Definitions

  • the present application relates to the field of wireless communication technologies, in particular to beam training (Beam training) technology. More particularly, it relates to an electronic device and method for wireless communication and a computer-readable storage medium.
  • Beam training beam training
  • Beamforming is one of the key technologies used in large-scale antenna arrays. By adjusting the phase of each antenna, the electromagnetic wave signals emitted by the antennas have the same phase at the user and the interference is constructive, and the interference in other directions is destructive. As shown in Figure 1a, when the base station does not use beamforming, the transmitted beam angle covers a large area and the energy received by the user is low; while as shown in Figure 1b, when the base station uses beamforming technology, the transmitted beam is concentrated on the user Therefore, the beamforming gain is obtained, and the received power of the user is greatly improved.
  • 5G NR introduces a beam training process.
  • the codebook-based beam training process is adopted in the NR system.
  • the base station uses different beams in the codebook to send reference signals. After measuring these beams, the user feeds back the sequence number of the optimal beam to the base station to complete the beam training process.
  • FIG. 2 shows an example of a process of beam training based on Synchronization Signal Block (SSB).
  • the transmitter is a terrestrial base station
  • the receiver is a user equipment (User Equipment, UE).
  • UE User Equipment
  • the base station sends N SSB SSBs, each SSB is sent using a specific beam, and the UE feeds back the SSB sequence number corresponding to the optimal beam after signal measurement.
  • the duration of the SSB burst does not exceed 5ms, the interval period is T (default 20ms), and the optional parameters of T are ⁇ 5, 10, 20, 40, 80, 160ms ⁇ .
  • the number of beams to be scanned is large, so the above beam training process will occupy a large amount of time-frequency resources, resulting in a decrease in spectrum utilization and an increase in access delay. Therefore, an effective fast beam training method is required.
  • an electronic device for wireless communication comprising: a processing circuit configured to: based on a preset aggregated weight matrix, pair a preset beam codebook that is far away in an angular domain Perform beam aggregation on the plurality of beams to obtain an aggregated beam; and send the aggregated beam to the user equipment for identifying the optimal beam for the user equipment in the preset beam codebook.
  • a method for wireless communication comprising: performing beam aggregation on a plurality of beams in a preset beam codebook that are far away in an angular domain based on a preset aggregation weight matrix, to obtain an aggregated beam; and sending the aggregated beam to the user equipment for identifying the optimal beam for the user equipment in the preset beam codebook.
  • an electronic device for wireless communication comprising: a processing circuit configured to: receive an aggregated beam sent by a base station, wherein the aggregated beam is passed by the base station based on a preset aggregation weight
  • the matrix is obtained by performing beam aggregation on multiple beams in the preset beam codebook that are far away in the angular domain; and identifying the optimal beam for the user equipment in the preset beam codebook by receiving the aggregated beams.
  • a method for wireless communication comprising: receiving an aggregated beam sent by a base station, wherein the aggregated beam is determined by the base station through a preset beam codebook based on a preset aggregation weight matrix The multiple beams in the angular domain that are far away in the angular domain are obtained by beam aggregation; and the optimal beam for the user equipment in the preset beam codebook is identified by receiving the aggregated beams.
  • the electronic device and method according to the embodiments of the present application can reduce beam training overhead and access delay by using the aggregated weight matrix to form aggregated beams and use the aggregated beams to identify optimal beams.
  • Figure 1a shows a schematic diagram of a beam transmitted by a base station without beamforming
  • Figure 1b shows a schematic diagram of a beam transmitted by a base station using beamforming
  • Figure 2 shows an example of a process for SSB-based beam training
  • FIG. 3 shows a schematic example of a millimeter-wave multipath channel
  • FIG. 4 is a functional block diagram illustrating an electronic device for wireless communication according to an embodiment of the present application.
  • FIG. 5 shows a schematic example of beam aggregation
  • Figure 6 shows a schematic diagram of the composition of the aggregation weight matrix
  • FIG. 7 shows an example of beam grouping
  • FIG. 8 shows an example of forming an aggregated beam based on an aggregated weight matrix
  • FIG. 9 is a functional block diagram illustrating an electronic device for wireless communication according to another embodiment of the present application.
  • FIG. 10 is a schematic diagram showing the related information flow between the base station and the user equipment
  • FIG. 11 is a graph showing the performance comparison between the fast beam training (FBT) method of the present application and the existing beam training method;
  • FIG. 12 is another graph showing the performance comparison between the fast beam training (FBT) method of the present application and the existing beam training method;
  • FBT fast beam training
  • FIG. 13 shows a flowchart of a method for wireless communication according to an embodiment of the present application
  • 15 is a block diagram illustrating a first example of a schematic configuration of an eNB or gNB to which techniques of this disclosure may be applied;
  • 16 is a block diagram illustrating a second example of a schematic configuration of an eNB or gNB to which techniques of this disclosure may be applied;
  • 17 is a block diagram showing an example of a schematic configuration of a smartphone to which the techniques of the present disclosure may be applied;
  • FIG. 18 is a block diagram showing an example of a schematic configuration of a car navigation apparatus to which the technology of the present disclosure can be applied.
  • 19 is a block diagram of an exemplary structure of a general-purpose personal computer in which methods and/or apparatuses and/or systems according to embodiments of the present disclosure may be implemented.
  • FIG. 3 shows a schematic example of a millimeter-wave multipath channel.
  • the number of transmitter antennas is NT
  • the number of receiver (ie, UE) antennas is NR
  • the multipath channel H can be expressed as,
  • a(N, ⁇ ) [1, e -j ⁇ , e- 2j ⁇ , .
  • ⁇ AS the angle spread
  • the base station transmit symbol be s (s is a complex number), and the transmit steering vector used is f (f is an N T ⁇ 1 vector, hereinafter also referred to as transmit beamforming vector),
  • the transmit power is ⁇
  • the UE uses the receive steering vector as w (w is an NR ⁇ 1 vector, hereinafter also referred to as the receive beamforming vector)
  • the additive noise at the receiving end is n (n is an NR ⁇ 1 vector) vector)
  • the UE received signal y (y is a complex number) can be expressed as:
  • FIG. 4 shows a block diagram of functional modules of an electronic device 100 according to an embodiment of the present application.
  • the electronic device 100 includes: an aggregation unit 101 configured to be based on a preset aggregation weight matrix (Merging Weight Matrix).
  • Matrix, MWW performs beam aggregation on a plurality of beams in the preset beam codebook that are far away in the angular domain to obtain an aggregated beam; and the transceiver unit 102 is configured to send the aggregated beam to a user equipment (UE) to obtain an aggregated beam. It is used to identify the optimal beam for the UE in the preset beam codebook.
  • UE user equipment
  • the aggregation unit 201 and the transceiver unit 202 may be implemented by one or more processing circuits, and the processing circuits may be implemented as chips or processors, for example. Moreover, it should be understood that each functional unit in the electronic device shown in FIG. 4 is only a logical module divided according to the specific functions implemented by the functional units, and is not used to limit the specific implementation manner.
  • the electronic device 100 may be provided at the base station side or communicatively connected to the base station, for example.
  • the base station described in this application may also be a Transmit Receive Point (TRP) or an Access Point (Access Point, AP).
  • TRP Transmit Receive Point
  • AP Access Point
  • the electronic device 400 may be implemented at the chip level, or may also be implemented at the device level.
  • the electronic device 400 may function as the base station itself, and may also include external devices such as memory, transceivers (not shown).
  • the memory can be used to store the programs and related data information that the base station needs to execute to realize various functions.
  • the transceiver may include one or more communication interfaces to support communication with different devices (eg, UE, other base stations, etc.), and the implementation form of the transceiver is not particularly limited here.
  • the aggregation unit 101 aggregates multiple beams far away in the angular domain into aggregated beams that are not included in the preset beam codebook. For example, the angular separation between any two adjacent beams selected is greater than the aforementioned angular spread ⁇ AS .
  • Figure 5 shows a schematic example of beam aggregation.
  • 4 beams are selected from the preset beam codebook, and these beams are narrow beams, which become aggregated beams (wide beams) after aggregation.
  • the transceiver unit 102 sends the aggregated beam to the UE, and the UE measures the aggregated beam to identify the optimal beam (narrow beam) for the UE in the preset beam codebook.
  • a preset aggregation weight matrix is used to aggregate multiple beams to obtain multiple aggregated beams. This is because the UE cannot distinguish the above-mentioned multiple beams by only performing a single reception. In order to identify the optimal beam, the UE needs to perform two or more receptions, that is, the base station needs to aggregate the above-mentioned multiple beams two or more times to obtain two or more aggregated beams that are different from each other.
  • An aggregated beam can be represented as:
  • s is an N ⁇ 1-dimensional aggregated weight vector
  • s is the beamforming vector corresponding to the aggregated beam.
  • Send aggregated beams at the base station the signal received by the UE can be expressed as
  • MWM aggregation weight matrix
  • FIG. 6 shows a schematic diagram of the composition of the MWM, wherein each column represents an aggregated weight vector for one aggregated beam, and each element of the vector represents a weight for a corresponding beam.
  • the UE's received signal Y for the M aggregated beams aggregated based on the aggregated weight matrix is expressed as:
  • the UE can use each row of the aggregated weight matrix to perform correlation detection on the received signal Y.
  • the beam corresponding to the row is determined as the optimal beam, and the row number may be referred to as an aggregation weight index (Merging Weight Index, MWI).
  • MWI Merging Weight Index
  • the UE may report the obtained aggregate weight sequence number to the base station to indicate the optimal beam determined by the UE.
  • the used preset aggregation weight matrix is known to the base station and the UE.
  • the aggregated weight matrix may be written into the device as a factory setting, or may be notified to the UE by the base station in the initial access stage.
  • the transceiving unit 102 may also be configured to indicate the indication information of the applied aggregation weight matrix to the UE. For example, the transceiving unit 102 may indicate to the UE whether the aggregated weight matrix is applied through the indication information. When there are multiple preset aggregation weight matrices, the transceiving unit 102 may indicate to the UE which aggregation weight matrix is applied through the indication information.
  • each column of the aggregated weight matrix represents a weight vector for one aggregated beam.
  • the aggregated weight matrix may be set such that the inner product of different rows is minimized.
  • the aggregation weight matrix may be obtained based on a discrete Fourier transform (DFT) matrix of order N, where N is the number of multiple beams used for aggregation as described above.
  • DFT discrete Fourier transform
  • the DFT matrix of order N is denoted as F N
  • the element of the i-th row and the k-th column of F N is Then the first M columns of F N can be taken as the columns of the matrix, and the aggregated weight matrix S is formed after the column power is normalized.
  • the base station uses the aggregate weight matrix S to form M aggregate beams and transmit them.
  • the above-mentioned multiple beams may be beams in each of multiple beam groups obtained by grouping beams in a preset beam codebook.
  • the aggregating unit 101 may select beams at predetermined index intervals from a preset beam codebook to form one beam group, and form different beam groups by shifting the index of the first beam.
  • the NT beams can be divided into G groups, each group contains N beams, for the gth (1 ⁇ g ⁇ G) group of beams, the beams included in the index are ⁇ g, G+ g, 2G+g, ...(N-1)G+g ⁇ .
  • the number of beams in each beam group is the same is given here, this is not limiting, and the number of beams in each beam group may also be different. When the number of beams in each beam group is different, the corresponding aggregation weight matrix may be different.
  • the aggregation unit 101 is further configured to perform multiple beam aggregation on the beams in each beam group based on the aggregation weight matrix to obtain multiple aggregated beams, and the transceiver unit 102 sequentially sends the multiple aggregated beams to the UE.
  • the g-th group of beams as an example, which includes N g beams
  • the obtained M g aggregated beams are expressed as:
  • the base station can indicate to the UE through the indication information.
  • S 11 , S 12 , . . . shown in FIG. 8 represent weight values of the corresponding beams.
  • the transceiving unit 102 may respectively use each aggregated beam to carry SSBs with different indices. Taking FIG. 8 as an example, the obtained four aggregated beams are used to carry SSB#1 to SSB#4 respectively.
  • the received signals of the UE for multiple aggregated beams can be expressed as the following equation (10).
  • the UE acquires Mg received signals.
  • the UE uses the corresponding aggregated weight matrix to identify the optimal beam based on all received signals.
  • the UE may perform two-level identification, that is, first identify the optimal beam group, and then determine the optimal beam in the optimal beam group according to the property shown in equation (8).
  • the departure angles of mmWave multipath channels are angularly concentrated, only a few beams have high beamforming gain , and Qg can be considered as sparse.
  • the aggregated beam corresponding to the optimal beam group where the optimal beam is located will have a large received signal power. Therefore, in order to identify the optimal beam group, the received signal power of each beam group can be compared. For example, the M g received signal powers of each group may be averaged, and then the beam group with the largest average power may be selected. It is shown in the following formula (11).
  • g * is the optimal beam group sequence number selected by the UE.
  • the power of the received signal mainly comes from the optimal beam, namely:
  • the UE uses the aggregated weight matrix respectively For each row of the received signal correlation detection, the received signal and the aggregated weight matrix The n gth row of (corresponding to the beam ) correlation coefficient Calculated as:
  • the UE can take the beam corresponding to n g with the largest correlation coefficient as the optimal beam, namely:
  • the Merging Weight Index (MWI) of the optimal beam determined by the UE, and the optimal beam identified by the UE is That is, the UE identifies that the beam represented by the aggregate weight sequence number in the beam group corresponding to the optimal beam group sequence number is the optimal beam.
  • the transceiving unit 102 may also be configured to receive indication information of the identified optimal beam from the UE.
  • the indication information may include the above-mentioned optimal beam group sequence number and aggregation weight sequence number.
  • the optimal beam group sequence number may be indicated by the corresponding SSB index. It can be seen that the method for optimal beam identification based on beam aggregation according to this embodiment supports the beam training process using only SSB. Therefore, the base station can receive the above-mentioned indication information in the random access phase to complete the beam training.
  • the signaling overhead is denoted as NT ; and when the optimal beam identification method based on aggregated beams of the present application is used, the signaling overhead is (M/N) NT .
  • each group of beams includes N beams, and each group of beams forms M aggregated beams.
  • the electronic device 100 can form an aggregated beam by using an aggregated weight matrix, and use the aggregated beam to identify an optimal beam, which can reduce beam training overhead and access delay.
  • FIG. 9 shows a block diagram of functional modules of an electronic device 200 according to another embodiment of the present application.
  • the electronic device 200 includes: a transceiver unit 201 configured to receive an aggregated beam sent by a base station, wherein the aggregated beam The beams are obtained by the base station by performing beam aggregation on a plurality of beams that are far away in the angular domain in the preset beam codebook based on the preset aggregation weight matrix; and the identification unit 202 is configured to receive the aggregated beams. Identify the optimal beam for the UE in the preset beam codebook.
  • the transceiver unit 201 and the identification unit 202 may be implemented by one or more processing circuits, and the processing circuits may be implemented as a chip or a processor, for example. Moreover, it should be understood that each functional unit in the electronic device shown in FIG. 9 is only a logical module divided according to the specific functions implemented by the functional units, and is not used to limit the specific implementation manner.
  • the electronic device 200 may be provided on the UE side or communicatively connected to the UE, for example.
  • the electronic device 200 may be implemented at the chip level, or may also be implemented at the device level.
  • the electronic device 200 may function as the UE itself, and may also include external devices such as a memory, a transceiver (not shown in the figure), and the like.
  • the memory can be used to store programs and related data information that the user equipment needs to execute to achieve various functions.
  • the transceiver may include one or more communication interfaces to support communication with different devices (eg, base stations, other UEs, etc.), and the implementation form of the transceiver is not particularly limited here.
  • the beam aggregation performed by the base station has been described in detail in the first embodiment, and will not be repeated here.
  • the preset aggregation weight matrix is known to the base station and the UE. Therefore, the UE side can use the information of the preset aggregation weight matrix to identify the optimal beam.
  • the transceiving unit 201 may be further configured to receive indication information indicating the applied aggregation weight matrix from the base station. For example, when there are multiple aggregation weight matrices, the indication information may indicate which aggregation weight matrix the corresponding aggregation beam is obtained based on.
  • the multiple beams used for aggregation are beams in each of multiple beam groups obtained by grouping beams in a preset beam codebook.
  • the beams in each beam group are separated from each other in the angular domain, for example, the angular interval between any two adjacent beams in each beam group Should be greater than the aforementioned angular spread ⁇ AS .
  • beams can be selected from the beams in the preset beam codebook at predetermined index intervals to form a beam group, and different beam groups can be formed by offsetting the index of the first beam, as in the first embodiment Specific examples are described.
  • the base station Based on the aggregation weight matrix, the base station performs multiple aggregations on the beams in each beam group to obtain multiple aggregated beams and transmits the multiple aggregated beams in sequence, the receiving unit 201 receives the multiple aggregated beams of each beam group, and the identifying unit 202 Based on the reception of the aggregated beams for each beam group, an aggregated weight matrix is used to determine the optimal beam.
  • each column of the aggregated weight matrix represents a weight vector for one aggregated beam, and the aggregated weight matrix is set to minimize the inner product of the different rows.
  • the aggregated weight matrix can be obtained based on a DFT matrix of order N, where N is the number of beams in each beam group.
  • the received signals obtained by the receiving unit 201 receiving the aggregated beams of each beam group are as follows (details are as described in the first embodiment):
  • the identification unit 202 determines the optimal beam group based on the reception of the aggregated beams of the respective beam groups, and determines the optimal beam among the optimal beam groups. This is because, due to the angular concentration of the departure angle of the millimeter-wave multipath channel, only a few beams have high beamforming gain , so the obtained Qg can be considered as sparse, and it can be inferred that the most The average received power of the optimal beam group where the optimal beam is located should be the highest. Moreover, since the beams in each beam group are far away from each other in the angular domain, it can be inferred that the received power of the optimal beam group mainly comes from the optimal beam.
  • the identification unit 202 is configured to determine the optimal beam group based on the average received power of the plurality of aggregated beams for each beam group, and to determine the optimal beam group by comparing the received signals of the plurality of aggregated beams for the optimal beam group with the aggregation weight matrix Correlation detection is performed on each row to determine the optimal beam. For example, the identifying unit 202 may determine the beam group with the highest average received power as the optimal beam group, and determine the beam corresponding to the row with the highest detected correlation coefficient as the optimal beam.
  • the average received power of multiple aggregated beams in each beam group is shown in the following formula (16): is the average received power of group g.
  • the beam group with the highest average received power can be determined as That is, the optimal beam group sequence number determined by the UE.
  • the received signal of the g * group can be written as the following equation (17).
  • the identification unit 202 uses the aggregated weight matrix respectively For each row of the received signal correlation detection, the received signal and the aggregated weight matrix The n gth row of (corresponding to the beam ) correlation coefficient Calculated as:
  • the identification unit 202 identifies the beam corresponding to n g with the largest correlation coefficient as the optimal beam, that is:
  • the identifying unit 202 determines that the beam represented by the aggregation weight sequence number in the beam group corresponding to the optimal beam group sequence number is the optimal beam.
  • the transceiver unit 201 is further configured to send indication information of the identified optimal beam to the base station, where the indication information includes, for example, the optimal beam group sequence number and the aggregation weight sequence number.
  • the various aggregated beams may be carried by SSBs with different indices.
  • the optimal beam group sequence number may be indicated by the SSB index.
  • the transceiver unit 201 may send the above-mentioned indication information in the random access phase.
  • FIG. 10 shows a schematic diagram of the related information flow between the base station and the UE.
  • each group of narrow beams is aggregated into multiple wide aggregated beams using an aggregation weight matrix (MWW) at the base station side, and then the base station sends multiple aggregated beams of each group of beams to the UE through SSB transmission, where Indicative information about the aggregated weight matrix used may also be included.
  • the UE receives each aggregated beam, and uses the corresponding MWW to identify the optimal beam based on the indication information of the MWW. Next, the UE sends the identification information of the identified optimal beam to the base station in the random access process.
  • the indication information includes, for example, the SSB index and the aggregation weight sequence number MWI used to indicate the optimal beam group.
  • the signal-to-noise ratio is set to 10dB
  • the number of NLoS diameters is 3, and the NLoS diameter angle spread is 7.5°.
  • FIG. 11 and FIG. 12 respectively show the performance comparison between the fast beam training (FBT) method of the present application and the existing beam training method from two aspects.
  • the horizontal axis of Figure 11 and Figure 12 are Indicates the ratio of the attenuation power of the LoS path to the NLoS path. The smaller the ⁇ , the greater the influence of the NLoS path and the more obvious the multipath effect.
  • the vertical axis of Figure 11 is the beam misselect rate, that is, the probability that the selected beam is not the optimal beam
  • the vertical axis of Figure 12 is the mean value of beamforming gain, both of which reflect the performance of beam training.
  • the fast beam training method proposed in this application adopts two different MWWs respectively.
  • MWW1 adopts a partial DFT array design
  • the aggregated weight matrix is MWW2 uses an aggregated weight matrix in
  • the two beam training methods used for comparison are the exhaustive search method (BF) and the two-stage method.
  • BF exhaustive search method
  • the base station side first sends a wide beam, selects the optimal wide beam, and then scans the narrow beams included in the wide beam to select the optimal narrow beam.
  • the feedback of the optimal wide beam needs to be The random access phase is performed, and narrow beam scanning can be performed only after the connection is established, so the initial access delay is relatively large.
  • the asterisk represents the beam misselect rate in the case of using BF
  • the triangle represents the beam misselect rate in the case of using the FBT of the present application and using MWM1
  • the plus sign represents the FBT of the present application
  • the circles represent the beam mis-selection rate in the case of using the two-stage method.
  • the asterisk represents the beamforming gain in the case of using BF
  • the triangle represents the beamforming gain in the case of using the FBT of the present application and using MWM1
  • the plus sign represents the use of the present application.
  • FBT and beamforming gain with MWM2 circles represent beamforming gain with two-stage method. It can be seen from Figure 11 and Figure 12 that both suitable MWM designs can achieve good beam training performance.
  • the fast beam training algorithm in this embodiment has similar performance to the exhaustive search method and better performance than the two-stage method. .
  • the beam training method of this embodiment reduces the beam training overhead from NT to (in this simulation example down to ), which significantly reduces the beam training overhead while keeping the beam training performance basically unchanged.
  • the proposed method only needs one beam training and one feedback, which reduces the initial access delay, and the proposed method significantly reduces the beam mis-selection rate and achieves better beam training performance.
  • the electronic device 200 can identify the optimal beam by using the aggregated weight matrix, which can reduce beam training overhead and reduce access delay.
  • FIG. 13 shows a flowchart of a method for wireless communication according to one embodiment of the present application.
  • the method includes: performing beam aggregation on a plurality of beams in a preset beam codebook that are far away in an angular domain based on a preset aggregation weight matrix to obtain an aggregated beam ( S11 ); and The UE transmits the aggregated beams for identifying the optimal beam for the UE in the preset beam codebook (S12).
  • the method can be performed at the base station side, for example.
  • the multiple beams may be beams in each of multiple beam groups obtained by grouping beams in a preset beam codebook.
  • Beams may be selected from beams in a preset beam codebook at predetermined index intervals to form one beam group, and different beam groups may be formed by shifting the index of the first beam.
  • step S11 based on the aggregation weight matrix, multiple beam aggregation may be performed on the beams in each beam group to obtain multiple aggregated beams, and the multiple aggregated beams are sequentially sent to the UE.
  • indication information indicating the applied aggregation weight matrix may also be sent to the UE.
  • Each column of the aggregated weight matrix represents a weight vector for one aggregated beam, eg, the aggregated weight matrix is set such that the inner product of the different rows is minimized.
  • the aggregated weight matrix can be obtained based on a discrete Fourier transform matrix of order P, where P is the number of beams in each beam group.
  • the preset aggregation weight matrix is known to the base station and the UE.
  • Each aggregated beam may be used to carry synchronization signal blocks with different indices, respectively.
  • the above method further includes step S13 : receiving indication information of the identified optimal beam from the UE.
  • the indication information may include an optimal beam group sequence number and an aggregate weight sequence number, wherein the UE identifies that the beam represented by the aggregate weight sequence number in the beam group corresponding to the optimal beam group sequence number is the optimal beam.
  • FIG. 14 shows a flowchart of a method for wireless communication according to another embodiment of the present application.
  • the method includes: receiving an aggregated beam sent by a base station, wherein the aggregated beam is determined by the base station based on a preset aggregation weight matrix to multiple beams in a preset beam codebook that are far away in the angular domain Perform beam aggregation to obtain (S21); and identify the optimal beam for the UE in the preset beam codebook by receiving the aggregated beam (S22).
  • This method can be performed on the UE side, for example.
  • the multiple beams may be beams in each of multiple beam groups obtained by grouping beams in a preset beam codebook.
  • Beams may be selected from beams in a preset beam codebook at predetermined index intervals to form one beam group, and different beam groups may be formed by shifting the index of the first beam.
  • the base station based on the aggregation weight matrix, performs multiple beam aggregation on the beams in each beam group to obtain multiple aggregated beams and transmits the multiple aggregated beams in sequence, and the UE receives multiple aggregated beams in each beam group in step S21.
  • the beams are aggregated, and an optimal beam is determined in step S22 using an aggregated weight matrix based on the reception of the aggregated beams for each beam group.
  • step S21 indication information indicating the applied aggregation weight matrix may also be received from the base station.
  • the preset aggregation weight matrix is known to the base station and the UE.
  • Each column of the aggregated weight matrix represents a weight vector for one aggregated beam, where the aggregated weight matrix can be set such that the inner product of the different rows is minimized.
  • the aggregated weight matrix is obtained based on a discrete Fourier transform matrix of order P, where P is the number of beams in each beam group.
  • the optimal beam group is determined based on the reception of the aggregated beams of the respective beam groups, and the optimal beam is determined in the optimal beam group.
  • the optimal beam group may be determined based on the average received power of the plurality of aggregated beams for each beam group, and by correlating the received signals of the plurality of aggregated beams for the optimal beam group with each row of the aggregated weight matrix detection to determine the optimal beam.
  • the beam group with the largest average received power may be determined as the optimal beam group, and the beam corresponding to the row with the largest detected correlation coefficient may be determined as the optimal beam.
  • the above method may further include step S23 : sending indication information of the identified optimal beam to the base station.
  • the indication information includes the optimal beam group sequence number and the aggregation weight sequence number, wherein in step S22, it is determined that the beam represented by the aggregate weight sequence number in the beam group corresponding to the optimal beam group sequence number is the optimal beam.
  • each aggregated beam may be carried by synchronization signal blocks with different indices.
  • the optimal beam group sequence number may be indicated by the synchronization signal block index.
  • the above-mentioned indication information may be sent in the random access phase.
  • the electronic device 100 may be implemented as various base stations.
  • a base station may be implemented as any type of evolved Node B (eNB) or gNB (5G base station).
  • eNBs include, for example, macro eNBs and small eNBs. Small eNBs may be eNBs covering cells smaller than macro cells, such as pico eNBs, micro eNBs, and home (femto) eNBs. A similar situation can also be used for gNB.
  • the base station may be implemented as any other type of base station, such as NodeB and base transceiver station (BTS).
  • BTS base transceiver station
  • a base station may include: a subject (also referred to as a base station device) configured to control wireless communications; and one or more remote radio heads (RRHs) disposed at a different location than the subject.
  • a subject also referred to as a base station device
  • RRHs remote radio heads
  • various types of user equipment can operate as a base station by temporarily or semi-persistently performing a base station function.
  • the electronic device 200 may be implemented as various user devices.
  • User equipment may be implemented as mobile terminals such as smart phones, tablet personal computers (PCs), notebook PCs, portable game terminals, portable/dongle-type mobile routers, and digital cameras or vehicle-mounted terminals such as car navigation devices.
  • the user equipment may also be implemented as a terminal performing machine-to-machine (M2M) communication (also referred to as a machine type communication (MTC) terminal).
  • M2M machine-to-machine
  • MTC machine type communication
  • the user equipment may be a wireless communication module (such as an integrated circuit module comprising a single die) mounted on each of the aforementioned terminals.
  • eNB 800 includes one or more antennas 810 and base station equipment 820.
  • the base station apparatus 820 and each antenna 810 may be connected to each other via an RF cable.
  • 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 by the base station apparatus 820 to transmit and receive wireless signals.
  • eNB 800 may include multiple antennas 810.
  • multiple antennas 810 may be compatible with multiple frequency bands used by eNB 800.
  • FIG. 15 shows an example in which the eNB 800 includes multiple antennas 810, the eNB 800 may also include a single antenna 810.
  • the base station apparatus 820 includes a controller 821 , a memory 822 , a network interface 823 , and a wireless communication interface 825 .
  • the controller 821 may be, for example, a CPU or a DSP, and operates various functions of a higher layer of the base station apparatus 820 .
  • the controller 821 generates data packets from data in the signal processed by the wireless communication interface 825 and communicates the generated packets via the network interface 823 .
  • the controller 821 may bundle data from a plurality of baseband processors to generate a bundled packet, and deliver the generated bundled packet.
  • the controller 821 may have logical functions to perform controls such as radio resource control, radio bearer control, mobility management, admission control and scheduling. This control may be performed in conjunction with nearby eNB or core network nodes.
  • 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.
  • the network interface 823 is a communication interface for connecting the base station apparatus 820 to the core network 824 .
  • the controller 821 may communicate with core network nodes or further eNBs via the network interface 823 .
  • eNB 800 and core network nodes or other eNBs may be connected to each other through logical interfaces such as S1 interface and X2 interface.
  • the network interface 823 may also be a wired communication interface or a wireless communication interface for wireless backhaul. If the network interface 823 is a wireless communication interface, the network interface 823 may use a higher frequency band for wireless communication than the frequency band used by the wireless communication interface 825 .
  • 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 cells of eNB 800 via antenna 810.
  • the wireless communication interface 825 may generally include, for example, a baseband (BB) processor 826 and RF circuitry 827 .
  • the BB processor 826 may perform, for example, encoding/decoding, modulation/demodulation, and multiplexing/demultiplexing, and performs layers such as L1, Medium Access Control (MAC), Radio Link Control (RLC), and Packet Data Convergence Protocol (PDCP)) various types of signal processing.
  • the BB processor 826 may have some or all of the above-described logical functions.
  • the BB processor 826 may be a memory storing a communication control program, or a module including a processor and associated circuitry configured to execute the program.
  • the update procedure may cause the functionality of the BB processor 826 to change.
  • the module may be a card or blade that is inserted into a slot of the base station device 820 .
  • the module can also be a chip mounted on a card or blade.
  • 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 .
  • the wireless communication interface 825 may include multiple BB processors 826 .
  • multiple BB processors 826 may be compatible with multiple frequency bands used by eNB 800.
  • the wireless communication interface 825 may include a plurality of RF circuits 827 .
  • multiple RF circuits 827 may be compatible with multiple antenna elements.
  • FIG. 15 shows 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 .
  • the transceiver unit 102 and the transceiver of the electronic device 100 may be implemented by the wireless communication interface 825. At least a portion of the functionality may also be implemented by the controller 821 .
  • the controller 821 may implement the fast beam training method based on the aggregated beam by performing the functions of the aggregation unit 101 and the transceiving unit 102 .
  • eNB 830 includes one or more antennas 840, base station equipment 850, and RRH 860.
  • the RRH 860 and each antenna 840 may be connected to each other via RF cables.
  • the base station apparatus 850 and the RRH 860 may be connected to each other via high-speed lines such as fiber optic cables.
  • 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 by the RRH 860 to transmit and receive wireless signals.
  • the eNB 830 may include multiple antennas 840.
  • multiple antennas 840 may be compatible with multiple frequency bands used by eNB 830.
  • 16 shows an example in which the eNB 830 includes multiple antennas 840, the eNB 830 may also include a single antenna 840.
  • the base station apparatus 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. 15 .
  • Wireless communication interface 855 supports any cellular communication scheme, such as LTE and LTE-Advanced, and provides wireless communication via RRH 860 and antenna 840 to terminals located in a sector corresponding to RRH 860.
  • Wireless communication interface 855 may generally include, for example, BB processor 856 .
  • the BB processor 856 is the same as the BB processor 826 described with reference to FIG. 15, except that the BB processor 856 is connected to the RF circuit 864 of the RRH 860 via the connection interface 857.
  • the wireless communication interface 855 may include multiple BB processors 856 .
  • multiple BB processors 856 may be compatible with multiple frequency bands used by eNB 830.
  • FIG. 16 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 .
  • connection interface 857 is an interface for connecting the base station apparatus 850 (the wireless communication interface 855 ) to the RRH 860.
  • the connection interface 857 may also be a communication module for communication in the above-mentioned high-speed line connecting the base station apparatus 850 (the wireless communication interface 855) to the RRH 860.
  • RRH 860 includes connection interface 861 and wireless communication interface 863.
  • connection interface 861 is an interface for connecting the RRH 860 (the wireless communication interface 863 ) to the base station apparatus 850.
  • the connection interface 861 may also be a communication module for communication in the above-mentioned high-speed line.
  • the wireless communication interface 863 transmits and receives wireless signals via the antenna 840 .
  • Wireless communication interface 863 may typically include RF circuitry 864, for example.
  • RF circuitry 864 may include, for example, mixers, filters, and amplifiers, and transmit and receive wireless signals via antenna 840.
  • the wireless communication interface 863 may include a plurality of RF circuits 864 .
  • multiple RF circuits 864 may support multiple antenna elements.
  • FIG. 16 shows an example in which the wireless communication interface 863 includes a plurality of RF circuits 864
  • the wireless communication interface 863 may include a single RF circuit 864 .
  • the transceiver unit 102 and the transceiver of the electronic device 100 may be implemented by the wireless communication interface 855 and/or the wireless communication interface 863. At least a portion of the functionality may also be implemented by the controller 851 .
  • the controller 851 can implement the fast beam training method based on the aggregated beam by performing the functions of the aggregation unit 101 and the transceiving unit 102 .
  • FIG. 17 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.
  • Smartphone 900 includes processor 901, memory 902, storage device 903, external connection interface 904, camera device 906, sensor 907, microphone 908, input device 909, display device 910, speaker 911, wireless communication interface 912, one or more Antenna switch 915 , one or more antennas 916 , bus 917 , battery 918 , and auxiliary controller 919 .
  • 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 further 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 a storage medium such as a semiconductor memory and a hard disk.
  • the external connection interface 904 is an interface for connecting an external device such as a memory card and a Universal Serial Bus (USB) device to the smartphone 900 .
  • USB Universal Serial Bus
  • 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.
  • Sensors 907 may include a set of sensors, such as measurement sensors, gyroscope sensors, geomagnetic sensors, and acceleration sensors.
  • 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 operations or information input from a user.
  • the display device 910 includes a screen such as a liquid crystal display (LCD) and an organic light emitting diode (OLED) display, and displays an output image of the smartphone 900 .
  • the speaker 911 converts the audio signal output from the smartphone 900 into sound.
  • the wireless communication interface 912 supports any cellular communication scheme, such as LTE and LTE-Advanced, and performs wireless communication.
  • Wireless communication interface 912 may typically include, for example, BB processor 913 and RF circuitry 914 .
  • the BB processor 913 can perform, for example, encoding/decoding, modulation/demodulation, and multiplexing/demultiplexing, and performs various types of signal processing for wireless communication.
  • the RF circuit 914 may include, for example, mixers, filters, and amplifiers, and transmit and receive wireless signals via the antenna 916 .
  • the wireless communication interface 912 may be a chip module on which the BB processor 913 and the RF circuit 914 are integrated. As shown in FIG. 17 , the wireless communication interface 912 may include a plurality of BB processors 913 and a plurality of RF circuits 914 . Although FIG. 17 shows 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 .
  • the wireless communication interface 912 may support additional types of wireless communication schemes, such as short-range wireless communication schemes, near field communication schemes, and wireless local area network (LAN) schemes.
  • the wireless communication interface 912 may include the BB processor 913 and the RF circuit 914 for each wireless communication scheme.
  • Each of the antenna switches 915 switches the connection destination of the antenna 916 among a plurality of circuits included in the wireless communication interface 912 (eg, circuits for different wireless communication schemes).
  • Each of the antennas 916 includes a single or multiple antenna elements (such as multiple antenna elements included in a MIMO antenna), and is used for the wireless communication interface 912 to transmit and receive wireless signals.
  • smartphone 900 may include multiple antennas 916 .
  • FIG. 17 shows an example in which the smartphone 900 includes multiple antennas 916
  • the smartphone 900 may include a single antenna 916 as well.
  • the smartphone 900 may include an antenna 916 for each wireless communication scheme.
  • the antenna switch 915 can be omitted from the configuration of the smartphone 900 .
  • the bus 917 connects the processor 901, the memory 902, the storage device 903, the external connection interface 904, the camera device 906, the sensor 907, the microphone 908, the input device 909, the display device 910, the speaker 911, the wireless communication interface 912, and the auxiliary controller 919 to each other connect.
  • the battery 918 provides power to the various blocks of the smartphone 900 shown in Figure 17 via feeders, which are partially shown in phantom in the figure.
  • the auxiliary controller 919 operates the minimum necessary functions of the smartphone 900, eg, in a sleep mode.
  • the transceiver unit 201 and the transceiver of the electronic device 200 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 .
  • the processor 901 or the auxiliary controller 919 may implement the fast beam training method based on the aggregated beam by performing the functions of the transceiving unit 201 and the identifying unit 202 .
  • FIG. 18 is a block diagram showing an example of a schematic configuration of a car navigation apparatus 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 A communication interface 933 , one or more antenna switches 936 , one or more antennas 937 , and a battery 938 .
  • GPS global positioning system
  • the processor 921 may be, for example, a CPU or a SoC, and controls the navigation function and other functions of the car navigation device 920 .
  • the memory 922 includes RAM and ROM, and stores data and programs executed by the processor 921 .
  • 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.
  • Sensors 925 may include a set of sensors such as gyroscope sensors, geomagnetic sensors, and air pressure sensors.
  • the data interface 926 is connected to, for example, the in-vehicle network 941 via a terminal not shown, and acquires data generated by the vehicle, such as vehicle speed data.
  • the content player 927 reproduces content stored in storage media such as CDs and DVDs, which are inserted into the storage media interface 928 .
  • the input device 929 includes, for example, a touch sensor, a button, or a switch configured to detect a touch on the screen of the display device 930, and receives operations or information input from a 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.
  • the wireless communication interface 933 supports any cellular communication scheme such as LTE and LTE-Advanced, and performs wireless communication.
  • Wireless communication interface 933 may typically include, for example, BB processor 934 and RF circuitry 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.
  • the RF circuit 935 may include, for example, mixers, filters, and amplifiers, and transmit and receive wireless signals via the antenna 937 .
  • the wireless communication interface 933 can also be a chip module on which the BB processor 934 and the RF circuit 935 are integrated. As shown in FIG.
  • the wireless communication interface 933 may include multiple BB processors 934 and multiple RF circuits 935 .
  • FIG. 18 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 include a single BB processor 934 or a single RF circuit 935 .
  • the wireless communication interface 933 may support another type of wireless communication scheme, such as a short-range wireless communication scheme, a near field communication scheme, and a wireless LAN scheme.
  • the wireless communication interface 933 may include the BB processor 934 and the RF circuit 935 for each wireless communication scheme.
  • Each of the antenna switches 936 switches the connection destination of the antenna 937 among a plurality of circuits included in the wireless communication interface 933, such as circuits for different wireless communication schemes.
  • Each of the antennas 937 includes a single or multiple antenna elements (such as multiple antenna elements included in a MIMO antenna), and is used for the wireless communication interface 933 to transmit and receive wireless signals.
  • the car navigation device 920 may include a plurality of antennas 937 .
  • FIG. 18 shows an example in which the car navigation device 920 includes a plurality of antennas 937
  • the car navigation device 920 may include a single antenna 937 .
  • the car navigation device 920 may include an antenna 937 for each wireless communication scheme.
  • the antenna switch 936 may be omitted from the configuration of the car navigation apparatus 920 .
  • the battery 938 provides power to the various blocks of the car navigation device 920 shown in FIG. 18 via feeders, which are partially shown as dashed lines in the figure.
  • the battery 938 accumulates power supplied from the vehicle.
  • the transceiver unit 201 and the transceiver of the electronic device 200 may be implemented by the wireless communication interface 933 . At least a portion of the functionality may also be implemented by the processor 921 .
  • the processor 921 may implement the fast beam training method based on the aggregated beam by performing the functions of the transceiving unit 201 and the identifying unit 202 .
  • the techniques of this disclosure may also be implemented as an in-vehicle system (or vehicle) 940 that includes one or more blocks of a car navigation device 920 , an in-vehicle network 941 , and 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 .
  • the present disclosure also proposes a program product storing machine-readable instruction codes.
  • the instruction code is read and executed by a machine, the above method according to the embodiment of the present disclosure can be executed.
  • a storage medium for carrying the above-mentioned program product storing the machine-readable instruction code is also included in the disclosure of the present disclosure.
  • 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.
  • programs constituting the software are installed from a storage medium or a network to a computer having a dedicated hardware configuration (for example, a general-purpose computer 1900 shown in FIG. 19 ) in which various programs are installed can perform various functions, etc.
  • a central processing unit (CPU) 1901 executes various processes according to a program stored in a read only memory (ROM) 1902 or a program loaded from a storage section 1908 to a random access memory (RAM) 1903.
  • ROM read only memory
  • RAM random access memory
  • data required when the CPU 1901 executes various processes and the like is also stored as needed.
  • the CPU 1901, ROM 1902, and RAM 1903 are connected to each other via a bus 1904.
  • Input/output interface 1905 is also connected to bus 1904.
  • the following components are connected to the input/output interface 1905: an input section 1906 (including a keyboard, mouse, etc.), an output section 1907 (including a display such as a cathode ray tube (CRT), a liquid crystal display (LCD), etc., and a speaker, etc.), A storage section 1908 (including a hard disk, etc.), a communication section 1909 (including a network interface card such as a LAN card, a modem, etc.). The communication section 1909 performs communication processing via a network such as the Internet.
  • a driver 1910 may also be connected to the input/output interface 1905 as desired.
  • a removable medium 1911 such as a magnetic disk, an optical disk, a magneto-optical disk, a semiconductor memory, etc. is mounted on the drive 1910 as needed, so that a computer program read therefrom is installed into the storage section 1908 as needed.
  • a program constituting the software is installed from a network such as the Internet or a storage medium such as the removable medium 1911 .
  • such a storage medium is not limited to the removable medium 1911 shown in FIG. 19 in which the program is stored and distributed separately from the device to provide the program to the user.
  • the removable media 1911 include magnetic disks (including floppy disks (registered trademark)), optical disks (including compact disk read only memory (CD-ROM) and digital versatile disk (DVD)), magneto-optical disks (including minidisc (MD) (registered trademark) trademark)) and semiconductor memory.
  • the storage medium may be the ROM 1902, a hard disk included in the storage section 1908, or the like, in which programs are stored and distributed to users together with the devices that include them.
  • each component or each step can be decomposed and/or recombined. These disaggregations and/or recombinations should be considered equivalents of the present disclosure. Also, the steps of executing the above-described series of processes can naturally be executed in chronological order in the order described, but need not necessarily be executed in chronological order. Certain steps may be performed in parallel or independently of each other.

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Abstract

本公开提供了一种用于无线通信的电子设备、方法和计算机可读存储介质，该电子设备包括：处理电路，被配置为：基于预先设定的聚合权重矩阵对预设的波束码本中的在角度域上远离的多个波束进行波束聚合，以获得聚合波束；以及向用户设备发送聚合波束，以用于识别预设的波束码本中针对该用户设备的最优波束。

Description

用于无线通信的电子设备和方法、计算机可读存储介质
本申请要求于2021年4月6日提交中国专利局、申请号为202110366924.3、发明名称为“用于无线通信的电子设备和方法、计算机可读存储介质”的中国专利申请的优先权，其全部内容通过引用结合在本申请中。
技术领域
本申请涉及无线通信技术领域，具体地涉及波束训练(Beam training)技术。更具体地，涉及一种用于无线通信的电子设备和方法以及计算机可读存储介质。
背景技术
波束赋形(Beamforming)是大规模天线阵使用的关键技术之一。通过调整各天线的相位，使得天线发射的电磁波信号在用户处相位一致干涉相长，其他方向干涉相消，可以使发射信号的能量集中在用户方向，提高用户的接收功率。如图1a所示，基站不使用波束赋形时，发送的波束角度覆盖范围大，用户接收到的能量低；而如图1b所示，基站使用波束赋形技术时，发送的波束集中在用户方向，从而获得了波束赋形增益，大大提高了用户的接收功率。
为了挑选出合适的发射/接收波束对，5G NR引入了波束训练过程。为了减小反馈开销，NR系统中采用基于码本的波束训练过程，基站使用码本中不同的波束发送参考信号，用户测量这些波束后将最优波束的序号反馈给基站，完成波束训练过程。图2示出了基于同步信号块(Synchronization Signal Block,SSB)的波束训练的过程的示例。其中，发射机为地面基站，接收机为用户设备(User Equipment，UE)。在一个SSB突发(SSB burst)周期内，基站发送N SSB个SSB，每个SSB使用一个特定的波束发送，UE进行信号测量后反馈最佳波束对应的SSB序号。SSB突发持续时间不超过5ms，间隔周期为T(默认20ms)，T的可选参数为{5,10,20,40,80,160ms}。
在大规模天线阵系统中，需要扫描的波束数量大，因此上述波束训练过程会占用大量的时频资源，造成频谱利用率下降，接入时延增加，因此需要有效的快速波束训练方法。
发明内容
在下文中给出了关于本公开的简要概述，以便提供关于本公开的某些方面的基本理解。应当理解，这个概述并不是关于本公开的穷举性概述。它并不是意图确定本公开的关键或重要部分，也不是意图限定本公开的范围。其目的仅仅是以简化的形式给出某些概念，以此作为稍后论述的更详细描述的前序。
根据本申请的一个方面，提供了一种用于无线通信的电子设备，包括：处理电路，被配置为：基于预先设定的聚合权重矩阵对预设的波束码本中的在角度域上远离的多个波束进行波束聚合，以获得聚合波束；以及向用户设备发送聚合波束，以用于识别预设的波束码本中针对该用户设备的最优波束。
根据本申请的一个方面，提供了一种用于无线通信的方法，包括：基于预先设定的聚合权重矩阵对预设的波束码本中的在角度域上远离的多个波束进行波束聚合，以获得聚合波束；以及向用户设备发送聚合波束，以用于识别预设的波束码本中针对该用户设备的最优波束。
根据本申请的另一个方面，提供了一种用于无线通信的电子设备，包括：处理电路，被配置为：接收基站发送的聚合波束，其中，聚合波束由基站通过基于预先设定的聚合权重矩阵对预设的波束码本中的在角度域上远离的多个波束进行波束聚合获得；以及通过对聚合波束的接收来识别预设的波束码本中针对用户设备的最优波束。
根据本申请的另一个方面，提供了一种用于无线通信的方法，包括：接收基站发送的聚合波束，其中，聚合波束由基站通过基于预先设定的聚合权重矩阵对预设的波束码本中的在角度域上远离的多个波束进行波束聚合获得；以及通过对聚合波束的接收来识别预设的波束码本中针对用户设备的最优波束。
根据本公开的其它方面，还提供了用于实现上述用于无线通信的方法的计算机程序代码和计算机程序产品以及其上记录有该用于实现上述 用于无线通信的方法的计算机程序代码的计算机可读存储介质。
根据本申请的实施例的电子设备和方法通过使用聚合权重矩阵来形成聚合波束，并且使用聚合波束来进行最优波束的识别，能够降低波束训练开销，减小接入时延。
通过以下结合附图对本公开的优选实施例的详细说明，本公开的这些以及其他优点将更加明显。
附图说明
为了进一步阐述本公开的以上和其它优点和特征，下面结合附图对本公开的具体实施方式作进一步详细的说明。所述附图连同下面的详细说明一起包含在本说明书中并且形成本说明书的一部分。具有相同的功能和结构的元件用相同的参考标号表示。应当理解，这些附图仅描述本公开的典型示例，而不应看作是对本公开的范围的限定。在附图中：
图1a示出了基站不使用波束赋形时发送的波束的示意图；
图1b示出了基站使用波束赋形时发送的波束的示意图；
图2示出了基于SSB的波束训练的过程的示例；
图3示出了毫米波多径信道的一个示意性示例；
图4是示出了根据本申请的一个实施例的用于无线通信的电子设备的功能模块框图；
图5示出了波束聚合的一个示意性示例；
图6示出了聚合权重矩阵的构成的示意图；
图7示出了波束分组的一个示例；
图8示出了基于聚合权重矩阵形成聚合波束的一个示例；
图9是示出了根据本申请的另一个实施例的用于无线通信的电子设备的功能模块框图；
图10是示出了基站与用户设备之间的相关信息流程的一个示意图；
图11是示出了本申请的快速波束训练(FBT)方法与已有的波束训练方法的性能对比的一个曲线图；
图12是示出了本申请的快速波束训练(FBT)方法与已有的波束训练方法的性能对比的另一个曲线图；
图13示出了根据本申请的一个实施例的用于无线通信的方法的流程图；
图14示出了根据本申请的另一个实施例的用于无线通信的方法的流程图；
图15是示出可以应用本公开内容的技术的eNB或gNB的示意性配置的第一示例的框图；
图16是示出可以应用本公开内容的技术的eNB或gNB的示意性配置的第二示例的框图；
图17是示出可以应用本公开内容的技术的智能电话的示意性配置的示例的框图；
图18是示出可以应用本公开内容的技术的汽车导航设备的示意性配置的示例的框图；以及
图19是其中可以实现根据本公开的实施例的方法和/或装置和/或系统的通用个人计算机的示例性结构的框图。
具体实施方式
在下文中将结合附图对本发明的示范性实施例进行描述。为了清楚和简明起见，在说明书中并未描述实际实施方式的所有特征。然而，应该了解，在开发任何这种实际实施例的过程中必须做出很多特定于实施方式的决定，以便实现开发人员的具体目标，例如，符合与系统及业务相关的那些限制条件，并且这些限制条件可能会随着实施方式的不同而有所改变。此外，还应该了解，虽然开发工作有可能是非常复杂和费时的，但对得益于本公开内容的本领域技术人员来说，这种开发工作仅仅是例行的任务。
在此，还需要说明的一点是，为了避免因不必要的细节而模糊了本发明，在附图中仅仅示出了与根据本发明的方案密切相关的设备结构和/或处理步骤，而省略了与本发明关系不大的其他细节。
<第一实施例>
图3示出了毫米波多径信道的一个示意性示例。假设发射机天线数为N T，接收机(即，UE)天线数为N R，发射机到接收机的信道记为H(H是一个N R×N T维的矩阵)，包含一条视距径(Line of Sight,LoS)H 0(H 0是一个N R×N T维的矩阵)和P条非视距径(Non Line of Sight,NLoS)H k(H k是一个N R×N T维的矩阵)k＝1，...，P。记路径H k的衰减因子为γ k，k＝0，1，...，P，(γ k是一个复数)，则多径信道H可表示为，
Figure PCTCN2022083974-appb-000001
假设第k条路径的出发角(Angle of departure,AoD)为
Figure PCTCN2022083974-appb-000002
到达角(Angle of arrival,AoA)为
Figure PCTCN2022083974-appb-000003
则第k条路径可以表示为：
Figure PCTCN2022083974-appb-000004
其中，a(N，θ)＝[1，e -jθ，e -2jθ，...，e -(N-1)jθ] T为N天线θ角方向的导向向量。一般而言，多径的基站侧出发角具有角度集中性，NLoS径的出发角
Figure PCTCN2022083974-appb-000005
都集中在LoS径
Figure PCTCN2022083974-appb-000006
附近，记θ AS为为角度扩散，则角度集中性可以表示为：
Figure PCTCN2022083974-appb-000007
以单流传输为例，设基站发送符号为s(s是一个复数)，使用的发送导向向量为f(f是一个N T×1的向量，下文中也称为发送波束赋形向量)，发送功率为β，UE使用接收导向向量为w(w是一个N R×1的向量，下文中也称为接收波束赋形向量)，接收端的加性噪声为n(n是一个N R×1的向量)，则UE接收信号y(y是一个复数)可表示为：
Figure PCTCN2022083974-appb-000008
如果记为q＝w HHf，则|q| 2为波束赋形增益。在波束训练过程中，基站和UE试图选取合适的导向向量f，w以获得高波束赋形增益。如前所述，当天线数量大时，备选波束数量大，因此为了确定合适的导向向量f，w(即，为了确定最优波束)，需要的UE测量次数多，这导致了大的波束训练开销和初始接入时延。为此，本实施例提出了一种基于波束聚合和波束识别的快速波束训练方案。应该理解，虽然将以上述波束训练场景为例描述本申请的实施例，但是本申请的实施例的应用范围并不限于此，而是可以适当地应用于其他需要确定最优波束的场景。
图4示出了根据本申请的一个实施例的电子设备100的功能模块框图，如图4所示，电子设备100包括：聚合单元101，被配置为基于预先设定的聚合权重矩阵(Merging Weight Matrix，MWW)对预设的波束码本中的在角度域上远离的多个波束进行波束聚合，以获得聚合波束；以及收发单元102，被配置为向用户设备(UE)发送聚合波束，以用于识别预设的波束码本中针对该UE的最优波束。
其中，聚合单元201和收发单元202可以由一个或多个处理电路实现，该处理电路例如可以实现为芯片、处理器。并且，应该理解，图4中所示的电子设备中的各个功能单元仅是根据其所实现的具体功能而划分的逻辑模块，而不是用于限制具体的实现方式。
电子设备100例如可以设置在基站侧或者可通信地连接到基站。本申请中所述的基站也可以是收发点(Transmit Receive Point，TRP)或者接入点(Access Point,AP)。这里，还应指出，电子设备400可以以芯片级来实现，或者也可以以设备级来实现。例如，电子设备400可以工作为基站本身，并且还可以包括诸如存储器、收发器(未示出)等外部设备。存储器可以用于存储基站实现各种功能需要执行的程序和相关数 据信息。收发器可以包括一个或多个通信接口以支持与不同设备(例如，UE、其他基站等等)间的通信，这里不具体限制收发器的实现形式。
在预设的波束码本中，例如指定了用于波束训练的多个波束，这些波束分布在不同角度方向上，例如分别可以用波束赋形向量f i表示(i为表示序号的自然数)。为了利用毫米波多径信道的出发角度集中性，以利于波束的区分，聚合单元101将角度域上远离的多个波束聚合为不包含在预设的波束码本中的聚合波束。例如，所选择的任意两个相邻波束之间的角度间隔大于前述角度扩散θ AS。图5示出了波束聚合的一个示意性示例。其中，从预设的波束码本中选择4个波束，这些波束为窄波束，聚合后成为聚合波束(宽波束)。收发单元102将该聚合波束发送至UE，UE对聚合波束进行测量，以识别预设的波束码本中的针对UE的最优波束(窄波束)。
在上述聚合过程中，使用预先设定的聚合权重矩阵对多个波束进行聚合，以获得多个聚合波束。这是因为，UE只进行单次接收是无法区分上述多个波束的。为了进行最优波束的识别，UE需要进行两次或多次接收，即，基站需要对上述多个波束进行两次或多次聚合，以获得彼此不同的两个或多个聚合波束。
假设对N个波束进行聚合，N个波束的波束赋形向量分别为f 1，...，f N，以波束矩阵形式表示为F＝[f 1，...，f N]，维度为N T×N。一个聚合波束例如可以表示为：
Figure PCTCN2022083974-appb-000009
其中，s是N×1维的聚合权重向量，
Figure PCTCN2022083974-appb-000010
是聚合波束对应的波束赋形向量。在基站发送聚合波束
Figure PCTCN2022083974-appb-000011
时，UE接收到的信号可以表示为
Figure PCTCN2022083974-appb-000012
Figure PCTCN2022083974-appb-000013
这里，s为功率归一化(模长为1)的N×1的聚合权重向量，h为归一化的多径信道向量，q i＝h Hf i，i＝1，...，N，Q＝[q 1，...，q N]，n为接收端加性噪声。
假设要获得M个聚合波束，使用的聚合权重向量分别为s 1，s 2，...，s M，定义S＝[s 1，s 2，...，s M]为聚合权重矩阵(MWM)(S是N×M的矩阵)。为了便于理解，图6示出了MWM的构成的示意图，其中，每一列代表针对一个聚合波束的聚合权重向量，其中的每一个元素代表针对相应的波束的权重。UE针对基于聚合权重矩阵聚合得到的M个聚合波束的接收信号Y表示为：
Figure PCTCN2022083974-appb-000014
由于用于聚合的N个波束在角度域上是相互远离的，因此，可以认为UE的接收信号的功率主要来源于最优波束。即，Q被认为具有稀疏性。根据该性质，可以将式(7)写为下式(8)
Figure PCTCN2022083974-appb-000015
其中，假设第n *个波束为最优波束，
Figure PCTCN2022083974-appb-000016
为聚合权重矩阵的第n *行。根据该性质，UE可以使用聚合权重矩阵的每一行对接收信号Y进行相关检测，所得到的相关系数越大，说明接收信号功率来自相应的波束的可能性越大，从而可以将相关系数最大的行对应的波束确定为最优波束，该行号可以称为聚合权重序号(Merging Weight Index，MWI)。UE可以将所得到的聚合权重序号上报给基站，以指示其确定的最优波束。
如上所述，所使用的预设的聚合权重矩阵对于基站和UE而言是已知的。例如，聚合权重矩阵可以是作为出厂设置写入设备中，也可以在初始接入阶段由基站通知UE。
此外，收发单元102还可以被配置为向UE指示所应用的聚合权重矩阵的指示信息。例如，收发单元102可以通过该指示信息向UE指示是否应用了聚合权重矩阵。在存在多个预设的聚合权重矩阵的情况下，收发单元102可以通过该指示信息向UE指示应用了哪个聚合权重矩阵。
如上所述，聚合权重矩阵的每一列代表针对一个聚合波束的权重向量。作为一个示例，聚合权重矩阵可以被设置为使得不同行的内积最小化。例如，聚合权重矩阵可以基于N阶的离散傅里叶变换(DFT)矩阵获得，其中，N为前文所述的用于聚合的多个波束的数量。
具体地，记N阶的DFT矩阵为F N，F N的第i行第k列的元素为
Figure PCTCN2022083974-appb-000017
则可以取F N前M列作为矩阵的列，将列功率归一化后，构成聚合权重矩阵S。对于N个波束，基站使用聚合权重矩阵S形成M个聚合波束并发送。
在一个示例中，上述多个波束可以为通过对预设的波束码本中的波束进行分组而获得的多个波束组中的每一个波束组中的波束。例如，聚 合单元101可以从预设的波束码本中以预定索引间隔选择波束来构成一个波束组，并且通过偏移第一个波束的索引来构成不同的波束组。
例如，假设预设的波束码本中总共有N T个波束，取一正整数N，使得
Figure PCTCN2022083974-appb-000018
亦为正整数，则可将这N T个波束分为G组，每组包含N个波束，对于第g(1≤g≤G)组波束，其包含的波束的索引为{g，G+g，2G+g，…(N-1)G+g}。图7示出了N T＝8，N＝4，G＝2的一个示例，其中，将8个波束分为2组，每组包括角度域上远离的4个波束并且这四个波束聚合成为聚合波束(宽波束)，图7示出了分别得到的2个聚合波束。应该理解，这里虽然给出了各个波束组的波束数量相同的示例，但是，这并不是限制性的，各个波束组的波束数量也可以不同。在各个波束组的波束数量不同的情况下，对应的聚合权重矩阵可能不同。
聚合单元101还被配置为基于聚合权重矩阵，对每一个波束组中的波束进行多次波束聚合，以获得多个聚合波束，收发单元102向UE依次发送多个聚合波束。以第g组波束为例，其包括N g个波束，所得到的M g个聚合波束表示为：
Figure PCTCN2022083974-appb-000019
其中，
Figure PCTCN2022083974-appb-000020
为第g组中的第n g个波束的波束向量，S g为N g×M g的聚合权重矩阵，其每一列代表针对一个聚合波束的权重向 量。所得到的
Figure PCTCN2022083974-appb-000021
的每一列代表一个聚合波束的波束向量。应该理解，对于各个波束组，可以采用相同的聚合权重矩阵，也可以采用不同的聚合权重矩阵，这都不是限制性的。具体采用哪种方式以及采用了哪个或哪些权重矩阵，基站可以通过指示信息向UE指出。
为了便于理解，图8示出了N T＝8，G＝2，N 1＝N 2＝4，M 1＝M 2＝2的一个示例，聚合权重矩阵S 1＝S 2＝S，为4×2矩阵，根据聚合权重矩阵S，每组波束形成2个聚合波束并发送，其中，第一个和第二个聚合波束是对第一组波束聚合得到，第三个和第四个聚合波束是对第二组波束聚合得到。图8中所示出的S 11、S 12、……代表相应波束的权重值。
此外，收发单元102可以分别使用各个聚合波束承载具有不同索引的SSB。以图8为例，分别使用所得到的四个聚合波束承载SSB#1至SSB#4。
仍以第g组波束为例，UE针对多个聚合波束的接收信号可以表示为下式(10)。
Figure PCTCN2022083974-appb-000022
其中，h为归一化的多径信道向量，
Figure PCTCN2022083974-appb-000023
Figure PCTCN2022083974-appb-000024
为接收端加性噪声。因此，对于每一个波束组，UE获取M g个接收信号。UE基于所有接收信号，使用相应的聚合权重矩阵进行最优波束的识别。
例如，UE可以进行两级识别，即，首先识别出最优波束组，然后根据式(8)所示的性质在最优波束组中确定最优波束。具体地，由于毫米 波多径信道的出发角具有角度集中性，因此只有少数波束具有较高的波束赋形增益，Q g可以被认为是稀疏的。可以理解，最优波束所在的最优波束组所对应的聚合波束将具有大的接收信号功率。因此，为了识别出最优波束组，可以各个波束组的接收信号功率进行比较。例如，可以对每一组的M g个接收信号功率取平均，然后选择平均功率最大的波束组。如下式(11)所示。
Figure PCTCN2022083974-appb-000025
Figure PCTCN2022083974-appb-000026
为第g组的平均接收功率，g *即为UE选择的最优波束组序号。
在组内的波束足够相互远离的情况下，由于Q g的稀疏性，可以认为接收信号的功率主要来自于最优波束，即：
Figure PCTCN2022083974-appb-000027
其中，
Figure PCTCN2022083974-appb-000028
为聚合权重矩阵
Figure PCTCN2022083974-appb-000029
的第
Figure PCTCN2022083974-appb-000030
行，UE分别使用聚合权重矩阵
Figure PCTCN2022083974-appb-000031
的每一行进行对接收信号相关检测，接收信号与聚合权重矩阵
Figure PCTCN2022083974-appb-000032
的第n g行(对应波束
Figure PCTCN2022083974-appb-000033
)的相关系数
Figure PCTCN2022083974-appb-000034
计算为：
Figure PCTCN2022083974-appb-000035
相关系数越高，说明接收信号功率来自对应的波束的可能性越大，因此，UE可以取相关系数最大的n g对应的波束作为最优波束，即：
Figure PCTCN2022083974-appb-000036
其中，
Figure PCTCN2022083974-appb-000037
为UE确定的最优波束的聚合权重序号(Merging Weight Index,MWI)，UE所识别的最优波束为
Figure PCTCN2022083974-appb-000038
即，UE识别出在最优波束组序号对应的波束组中的由聚合权重序号代表的波束为最优波束。
收发单元102还可以被配置为从UE接收所识别的最优波束的指示信息。例如，该指示信息可以包括上述最优波束组序号和聚合权重序号。在使用各个聚合波束承载具有不同索引的SSB的情况下，最优波束组序号可以用相应的SSB索引指示。可以看出，根据本实施例的基于波束聚合的最优波束识别的方法支持仅使用SSB的波束训练过程。因此，基站可以在随机接入阶段接收上述指示信息，以完成波束训练。
对于波束训练过程，在采用穷举搜索法时，信令开销记为N T；而在采用本申请的基于聚合波束的最优波束识别方法时，信令开销为(M/N)N T。其中，每一组波束中包括N个波束，每一组波束形成M个聚合波束。在适当地选择M和N的情况下，可以有效地降低信令开销，减小时延。
综上所述，根据本实施例的电子设备100能够通过使用聚合权重矩阵来形成聚合波束，并且使用聚合波束来进行最优波束的识别，能够降低波束训练开销，减小接入时延。
<第二实施例>
图9示出了根据本申请的另一个实施例的电子设备200的功能模块框图，如图9所示，电子设备200包括：收发单元201，被配置为接收基站发送的聚合波束，其中，聚合波束由基站通过基于预先设定的聚合权重矩阵对预设的波束码本中的在角度域上远离的多个波束进行波束聚合获得；以及识别单元202，被配置为通过对聚合波束的接收来识别预设的波束码本中针对UE的最优波束。
其中，收发单元201和识别单元202可以由一个或多个处理电路实现，该处理电路例如可以实现为芯片、处理器。并且，应该理解，图9中所示的电子设备中的各个功能单元仅是根据其所实现的具体功能而划分的逻辑模块，而不是用于限制具体的实现方式。
电子设备200例如可以设置在UE侧或者可通信地连接到UE。这里，还应指出，电子设备200可以以芯片级来实现，或者也可以以设备级来实现。例如，电子设备200可以工作为UE本身，并且还可以包括诸如存储器、收发器(图中未示出)等外部设备。存储器可以用于存储用户设备实现各种功能需要执行的程序和相关数据信息。收发器可以包括一个或多个通信接口以支持与不同设备(例如，基站、其他UE等等)间的通信，这里不具体限制收发器的实现形式。
有关基站执行的波束聚合在第一实施例中已经给出了详细描述，在此不再重复。其中，预先设定的聚合权重矩阵对于基站和UE是已知的。因此，UE侧可以利用预设的聚合权重矩阵的信息来进行最优波束的识别。此外，收发单元201还可以被配置为从基站接收指示所应用的聚合权重矩阵的指示信息。例如，在存在多个聚合权重矩阵的情况下，该指示信息可以指示相应的聚合波束是基于哪个聚合权重矩阵得到的。
在一个示例中，用于聚合的多个波束是通过对预设的波束码本中的波束进行分组而获得的多个波束组中的每一个波束组中的波束。如第一实施例中所述，为了能够进行波束识别，每一个波束组中的波束在角度域上是相互远离的，例如，每一个波束组中的任意两个相邻波束之间的角度间隔应大于前述角度扩散θ AS。
例如，可以从预设的波束码本中的波束中以预定索引间隔选择波束来构成一个波束组，并且通过偏移第一个波束的索引来构成不同的波束组，如第一实施例中的具体示例所述。基站基于聚合权重矩阵，对每一 个波束组中的波束进行多次聚合而获得多个聚合波束并且依次发送该多个聚合波束，接收单元201接收每一个波束组的多个聚合波束，识别单元202基于对各个波束组的聚合波束的接收，使用聚合权重矩阵来确定最优波束。
作为一个示例，聚合权重矩阵的每一列代表针对一个聚合波束的权重向量，聚合权重矩阵被设置为使得不同行的内积最小化。例如，聚合权重矩阵可以基于N阶的DFT矩阵获得，其中，N为每个波束组中的波束数量。
接收单元201针对各个波束组的聚合波束进行接收所得到的接收信号如下(细节如第一实施例中所述)：
Figure PCTCN2022083974-appb-000039
其中，h为归一化的多径信道向量，
Figure PCTCN2022083974-appb-000040
Figure PCTCN2022083974-appb-000041
为接收端加性噪声。
识别单元202基于对各个波束组的聚合波束的接收来确定最优波束组，并且在最优波束组中确定最优波束。这是因为，由于毫米波多径信道的出发角具有角度集中性，因此只有少数波束具有较高的波束赋形增益，因此所得到的Q g可以认为是稀疏的，利用该稀疏性可以推断，最优波束所在的最优波束组的平均接收功率应该最高。并且，由于每一个波束组中的波束在角度域上是相互远离的，因此可以推断该最优波束组的接收功率主要来源于最优波束。
因此，识别单元202被配置为基于针对每一个波束组的多个聚合波束的平均接收功率来确定最优波束组，并且通过针对最优波束组的多个 聚合波束的接收信号与聚合权重矩阵的每一行进行相关检测来确定最优波束。例如，识别单元202可以将平均接收功率最大的波束组确定为最优波束组，将检测的相关系数最大的行对应的波束确定为最优波束。
具体地，每一个波束组的多个聚合波束的平均接收功率如下式(16)所示，
Figure PCTCN2022083974-appb-000042
为第g组的平均接收功率。
Figure PCTCN2022083974-appb-000043
平均接收功率最大的波束组可以确定为
Figure PCTCN2022083974-appb-000044
即为UE确定的最优波束组序号。
考虑Q g的稀疏性，可以将第g *组的接收信号写为下式(17)。
Figure PCTCN2022083974-appb-000045
其中，
Figure PCTCN2022083974-appb-000046
为聚合权重矩阵
Figure PCTCN2022083974-appb-000047
的第
Figure PCTCN2022083974-appb-000048
行，识别单元202分别使用聚合权重矩阵
Figure PCTCN2022083974-appb-000049
的每一行进行对接收信号相关检测，接收信号与聚合权重矩阵
Figure PCTCN2022083974-appb-000050
的第n g行(对应波束
Figure PCTCN2022083974-appb-000051
)的相关系数
Figure PCTCN2022083974-appb-000052
计算为：
Figure PCTCN2022083974-appb-000053
识别单元202将相关系数最大的n g对应的波束识别为最优波束，即：
Figure PCTCN2022083974-appb-000054
其中，
Figure PCTCN2022083974-appb-000055
为识别单元202确定的最优波束的聚合权重序号(MWI)，即，所识别的最优波束为
Figure PCTCN2022083974-appb-000056
换言之，识别单元202确定在最优波束组序号对应的波束组中的由聚合权重序号代表的波束为最优波束。
收发单元201还被配置为向基站发送所识别的最优波束的指示信息，该指示信息例如包括最优波束组序号和聚合权重序号。
在一个示例中，各个聚合波束可以由具有不同索引的SSB承载。最优波束组序号可以由SSB索引指示。并且，收发单元201可以在随机接入阶段发送上述指示信息。
为了便于理解，图10示出了基站与UE之间的相关信息流程的示意图。如图10所示，在基站侧使用聚合权重矩阵(MWW)将每一组窄波束聚合成为多个宽的聚合波束，然后基站通过SSB传输向UE发送每一组波束的多个聚合波束，其中还可以包括关于所使用的聚合权重矩阵的指示信息。UE对各个聚合波束进行接收，并且基于MWW的指示信息利用相应的MWW识别出最优波束。接下来，UE在随机接入过程中将所识别的最优波束的指示信息发送给基站。该指示信息例如包括用于指示最优波束组的SSB索引和聚合权重序号MWI。
注意，图10所示的信息流程仅是示例性的，而不是限制性的。
此外，为了便于理解本实施例的技术的优点，还给出了如下仿真示例。其中，信噪比设置为10dB，NLoS径数量为3，NLoS径角度扩散7.5°。根据本实施例的基于聚合波束的最优波束识别的方法(也称为快速波束训练方法)中，参数设置为：N T＝32，G＝8，N＝4，M 1＝…＝M 8＝M＝2,所有波束组使用相同的聚合权重矩阵S。
图11和图12从两个方面分别示出了本申请的快速波束训练(FBT)方法与已有的波束训练方法的性能对比。其中，图11和图12的横轴均 为
Figure PCTCN2022083974-appb-000057
表示LoS径与NLoS径的衰减功率比，ρ越小，说明NLoS径影响越大，多径效应越明显。图11的纵轴为波束误选率，即选择波束不是最优波束的概率，图12的纵轴为波束赋形增益的均值，两者均反映了波束训练的性能。
其中，本申请提出的快速波束训练方法分别采用了两种不同的MWW，其中，MWW1采用部分DFT阵设计，聚合权重矩阵为
Figure PCTCN2022083974-appb-000058
MWW2采用聚合权重矩阵
Figure PCTCN2022083974-appb-000059
其中
Figure PCTCN2022083974-appb-000060
用于比较的两种波束训练方法分别为穷举搜索法(BF)和两阶段法。其中，在BF方法中，通过穷举扫描所有波束对的方式来进行波束训练。在两阶段法中，基站侧先发送宽波束，选出最优宽波束，然后再扫描宽波束包含的窄波束选出最优窄波束，在该方法中，由于最优宽波束的反馈需要在随机接入阶段进行，建立连接后才能进行窄波束扫描，因此初始接入时延较大。
在图11中，星号代表了采用BF的情况下的波束误选率，三角形代表了采用本申请的FBT并且采用MWM1的情况下的波束误选率，加号代表了采用本申请的FBT并且采用MWM2的情况下的波束误选率，圆圈代表采用两阶段法的情况下的波束误选率。类似地，在图12中，星号代表了采用BF的情况下的波束赋形增益，三角形代表了采用本申请的FBT并且采用MWM1的情况下的波束赋形增益，加号代表了采用本申请的FBT并且采用MWM2的情况下的波束赋形增益，圆圈代表采用两阶段法的情况下的波束赋形增益。从图11和图12中可以看出，两种合适的MWM设计都可以获得很好的波束训练性能，本实施例的快速波束训练算法与穷举搜索法性能接近，较两阶段法性能更好。
相比于穷举搜索法，本实施例的波束训练方法将波束训练开销由N T降低为
Figure PCTCN2022083974-appb-000061
(本仿真示例中降为
Figure PCTCN2022083974-appb-000062
)，显著降低了波束训练开销，而能够保持波束训练性能基本不变。
相比于两阶段法，所提方法仅需一次波束训练一次反馈，降低了初始接入时延，且所提方法显著降低了波束误选率，获得更好的波束训练性能。
综上所述，根据本实施例的电子设备200能够通过使用聚合权重矩阵来进行最优波束的识别，能够降低波束训练开销，减小接入时延。
<第三实施例>
在上文的实施方式中描述用于无线通信的电子设备的过程中，显然还公开了一些处理或方法。下文中，在不重复上文中已经讨论的一些细节的情况下给出这些方法的概要，但是应当注意，虽然这些方法在描述用于无线通信的电子设备的过程中公开，但是这些方法不一定采用所描述的那些部件或不一定由那些部件执行。例如，用于无线通信的电子设备的实施方式可以部分地或完全地使用硬件和/或固件来实现，而下面讨论的用于无线通信的方法可以完全由计算机可执行的程序来实现，尽管这些方法也可以采用用于无线通信的电子设备的硬件和/或固件。
图13示出了根据本申请的一个实施例的用于无线通信的方法的流程图。如图13所示，该方法包括：基于预先设定的聚合权重矩阵对预设的波束码本中的在角度域上远离的多个波束进行波束聚合，以获得聚合波束(S11)；以及向UE发送聚合波束，以用于识别预设的波束码本中针对UE的最优波束(S12)。该方法例如可以在基站侧执行。
例如，多个波束可以为通过对预设的波束码本中的波束进行分组而获得的多个波束组中的每一个波束组中的波束。可以从预设的波束码本中的波束中以预定索引间隔选择波束来构成一个波束组，并且通过偏移第一个波束的索引来构成不同的波束组。
在步骤S11中，可以基于聚合权重矩阵，对每一个波束组中的波束 进行多次波束聚合，以获得多个聚合波束，并且向UE依次发送多个聚合波束。此外，还可以向UE发送指示所应用的聚合权重矩阵的指示信息。
聚合权重矩阵的每一列代表针对一个聚合波束的权重向量，例如，聚合权重矩阵被设置为使得不同行的内积最小化。例如，聚合权重矩阵可以基于P阶的离散傅里叶变换矩阵获得，其中，P为每个波束组中的波束数量。预先设定的聚合权重矩阵对于基站和UE是已知的。
可以分别使用各个聚合波束承载具有不同索引的同步信号块。
如图13中的虚线框所示，上述方法还包括步骤S13：从UE接收所识别的最优波束的指示信息。例如，该指示信息可以包括最优波束组序号和聚合权重序号，其中，UE识别出在最优波束组序号对应的波束组中的由聚合权重序号代表的波束为最优波束。
图14示出了根据本申请的另一个实施例的用于无线通信的方法的流程图。如图14所示，该方法包括：接收基站发送的聚合波束，其中，聚合波束由基站通过基于预先设定的聚合权重矩阵对预设的波束码本中的在角度域上远离的多个波束进行波束聚合获得(S21)；以及通过对聚合波束的接收来识别预设的波束码本中针对UE的最优波束(S22)。该方法例如可以在UE侧执行。
例如，多个波束可以为通过对预设的波束码本中的波束进行分组而获得的多个波束组中的每一个波束组中的波束。可以从预设的波束码本中的波束中以预定索引间隔选择波束来构成一个波束组，并且通过偏移第一个波束的索引来构成不同的波束组。
其中，基站基于聚合权重矩阵，对每一个波束组中的波束进行多次波束聚合而获得多个聚合波束并且依次发送所述多个聚合波束，UE在步骤S21中接收每一个波束组的多个聚合波束，并且在步骤S22中基于对各个波束组的聚合波束的接收，使用聚合权重矩阵来确定最优波束。
此外，在步骤S21中还可以从基站接收指示所应用的聚合权重矩阵的指示信息。预先设定的聚合权重矩阵对于基站和UE是已知的。
聚合权重矩阵的每一列代表针对一个聚合波束的权重向量，其中，聚合权重矩阵可以被设置为使得不同行的内积最小化。例如，聚合权重 矩阵基于P阶的离散傅里叶变换矩阵获得，其中，P为每个波束组中的波束数量。
在步骤S22中，基于对各个波束组的聚合波束的接收来确定最优波束组，并且在最优波束组中确定最优波束。例如，可以基于针对每一个波束组的多个聚合波束的平均接收功率来确定最优波束组，并且通过对针对最优波束组的多个聚合波束的接收信号与聚合权重矩阵的每一行进行相关检测来确定最优波束。
可以将平均接收功率最大的波束组确定为最优波束组，并且将检测的相关系数最大的行对应的波束确定为最优波束。
如图14中的虚线框所示，上述方法还可以包括步骤S23：向基站发送所识别的最优波束的指示信息。例如，该指示信息包括最优波束组序号和聚合权重序号，其中，在步骤S22中确定在最优波束组序号对应的波束组中的由聚合权重序号代表的波束为最优波束。例如，各个聚合波束可以由具有不同索引的同步信号块承载。最优波束组序号可以由同步信号块索引指示。并且，可以在随机接入阶段发送上述指示信息。
注意，上述各个方法可以结合或单独使用，其细节在第一至第二实施例中已经进行了详细描述，在此不再重复。
本公开内容的技术能够应用于各种产品。
例如，电子设备100可以被实现为各种基站。基站可以被实现为任何类型的演进型节点B(eNB)或gNB(5G基站)。eNB例如包括宏eNB和小eNB。小eNB可以为覆盖比宏小区小的小区的eNB，诸如微微eNB、微eNB和家庭(毫微微)eNB。对于gNB也可以由类似的情形。代替地，基站可以被实现为任何其他类型的基站，诸如NodeB和基站收发台(BTS)。基站可以包括：被配置为控制无线通信的主体(也称为基站设备)；以及设置在与主体不同的地方的一个或多个远程无线头端(RRH)。另外，各种类型的用户设备均可以通过暂时地或半持久性地执行基站功能而作为基站工作。
电子设备200可以被实现为各种用户设备。用户设备可以被实现为移动终端(诸如智能电话、平板个人计算机(PC)、笔记本式PC、便携 式游戏终端、便携式/加密狗型移动路由器和数字摄像装置)或者车载终端(诸如汽车导航设备)。用户设备还可以被实现为执行机器对机器(M2M)通信的终端(也称为机器类型通信(MTC)终端)。此外，用户设备可以为安装在上述终端中的每个终端上的无线通信模块(诸如包括单个晶片的集成电路模块)。
[关于基站的应用示例]
(第一应用示例)
图15是示出可以应用本公开内容的技术的eNB或gNB的示意性配置的第一示例的框图。注意，以下的描述以eNB作为示例，但是同样可以应用于gNB。eNB 800包括一个或多个天线810以及基站设备820。基站设备820和每个天线810可以经由RF线缆彼此连接。
天线810中的每一个均包括单个或多个天线元件(诸如包括在多输入多输出(MIMO)天线中的多个天线元件)，并且用于基站设备820发送和接收无线信号。如图15所示，eNB 800可以包括多个天线810。例如，多个天线810可以与eNB 800使用的多个频带兼容。虽然图15示出其中eNB 800包括多个天线810的示例，但是eNB 800也可以包括单个天线810。
基站设备820包括控制器821、存储器822、网络接口823以及无线通信接口825。
控制器821可以为例如CPU或DSP，并且操作基站设备820的较高层的各种功能。例如，控制器821根据由无线通信接口825处理的信号中的数据来生成数据分组，并经由网络接口823来传递所生成的分组。控制器821可以对来自多个基带处理器的数据进行捆绑以生成捆绑分组，并传递所生成的捆绑分组。控制器821可以具有执行如下控制的逻辑功能：该控制诸如为无线资源控制、无线承载控制、移动性管理、接纳控制和调度。该控制可以结合附近的eNB或核心网节点来执行。存储器822包括RAM和ROM，并且存储由控制器821执行的程序和各种类型的控制数据(诸如终端列表、传输功率数据以及调度数据)。
网络接口823为用于将基站设备820连接至核心网824的通信接口。 控制器821可以经由网络接口823而与核心网节点或另外的eNB进行通信。在此情况下，eNB 800与核心网节点或其他eNB可以通过逻辑接口(诸如S1接口和X2接口)而彼此连接。网络接口823还可以为有线通信接口或用于无线回程线路的无线通信接口。如果网络接口823为无线通信接口，则与由无线通信接口825使用的频带相比，网络接口823可以使用较高频带用于无线通信。
无线通信接口825支持任何蜂窝通信方案(诸如长期演进(LTE)和LTE-先进)，并且经由天线810来提供到位于eNB 800的小区中的终端的无线连接。无线通信接口825通常可以包括例如基带(BB)处理器826和RF电路827。BB处理器826可以执行例如编码/解码、调制/解调以及复用/解复用，并且执行层(例如L1、介质访问控制(MAC)、无线链路控制(RLC)和分组数据汇聚协议(PDCP))的各种类型的信号处理。代替控制器821，BB处理器826可以具有上述逻辑功能的一部分或全部。BB处理器826可以为存储通信控制程序的存储器，或者为包括被配置为执行程序的处理器和相关电路的模块。更新程序可以使BB处理器826的功能改变。该模块可以为插入到基站设备820的槽中的卡或刀片。可替代地，该模块也可以为安装在卡或刀片上的芯片。同时，RF电路827可以包括例如混频器、滤波器和放大器，并且经由天线810来传送和接收无线信号。
如图15所示，无线通信接口825可以包括多个BB处理器826。例如，多个BB处理器826可以与eNB 800使用的多个频带兼容。如图15所示，无线通信接口825可以包括多个RF电路827。例如，多个RF电路827可以与多个天线元件兼容。虽然图15示出其中无线通信接口825包括多个BB处理器826和多个RF电路827的示例，但是无线通信接口825也可以包括单个BB处理器826或单个RF电路827。
在图15所示的eNB 800中，电子设备100的收发单元102、收发器可以由无线通信接口825实现。功能的至少一部分也可以由控制器821实现。例如，控制器821可以通过执行聚合单元101和收发单元102的功能来实现基于聚合波束的快速波束训练方法。
(第二应用示例)
图16是示出可以应用本公开内容的技术的eNB或gNB的示意性配 置的第二示例的框图。注意，类似地，以下的描述以eNB作为示例，但是同样可以应用于gNB。eNB 830包括一个或多个天线840、基站设备850和RRH 860。RRH 860和每个天线840可以经由RF线缆而彼此连接。基站设备850和RRH 860可以经由诸如光纤线缆的高速线路而彼此连接。
天线840中的每一个均包括单个或多个天线元件(诸如包括在MIMO天线中的多个天线元件)并且用于RRH 860发送和接收无线信号。如图16所示，eNB 830可以包括多个天线840。例如，多个天线840可以与eNB 830使用的多个频带兼容。虽然图16示出其中eNB 830包括多个天线840的示例，但是eNB 830也可以包括单个天线840。
基站设备850包括控制器851、存储器852、网络接口853、无线通信接口855以及连接接口857。控制器851、存储器852和网络接口853与参照图15描述的控制器821、存储器822和网络接口823相同。
无线通信接口855支持任何蜂窝通信方案(诸如LTE和LTE-先进)，并且经由RRH 860和天线840来提供到位于与RRH 860对应的扇区中的终端的无线通信。无线通信接口855通常可以包括例如BB处理器856。除了BB处理器856经由连接接口857连接到RRH 860的RF电路864之外，BB处理器856与参照图15描述的BB处理器826相同。如图16所示，无线通信接口855可以包括多个BB处理器856。例如，多个BB处理器856可以与eNB 830使用的多个频带兼容。虽然图16示出其中无线通信接口855包括多个BB处理器856的示例，但是无线通信接口855也可以包括单个BB处理器856。
连接接口857为用于将基站设备850(无线通信接口855)连接至RRH 860的接口。连接接口857还可以为用于将基站设备850(无线通信接口855)连接至RRH 860的上述高速线路中的通信的通信模块。
RRH 860包括连接接口861和无线通信接口863。
连接接口861为用于将RRH 860(无线通信接口863)连接至基站设备850的接口。连接接口861还可以为用于上述高速线路中的通信的通信模块。
无线通信接口863经由天线840来传送和接收无线信号。无线通信接口863通常可以包括例如RF电路864。RF电路864可以包括例如混 频器、滤波器和放大器，并且经由天线840来传送和接收无线信号。如图16所示，无线通信接口863可以包括多个RF电路864。例如，多个RF电路864可以支持多个天线元件。虽然图16示出其中无线通信接口863包括多个RF电路864的示例，但是无线通信接口863也可以包括单个RF电路864。
在图16所示的eNB 830中，电子设备100的收发单元102、收发器可以由无线通信接口855和/或无线通信接口863实现。功能的至少一部分也可以由控制器851实现。例如，控制器851可以通过执行聚合单元101和收发单元102的功能来实现基于聚合波束的快速波束训练方法。
[关于用户设备的应用示例]
(第一应用示例)
图17是示出可以应用本公开内容的技术的智能电话900的示意性配置的示例的框图。智能电话900包括处理器901、存储器902、存储装置903、外部连接接口904、摄像装置906、传感器907、麦克风908、输入装置909、显示装置910、扬声器911、无线通信接口912、一个或多个天线开关915、一个或多个天线916、总线917、电池918以及辅助控制器919。
处理器901可以为例如CPU或片上系统(SoC)，并且控制智能电话900的应用层和另外层的功能。存储器902包括RAM和ROM，并且存储数据和由处理器901执行的程序。存储装置903可以包括存储介质，诸如半导体存储器和硬盘。外部连接接口904为用于将外部装置(诸如存储卡和通用串行总线(USB)装置)连接至智能电话900的接口。
摄像装置906包括图像传感器(诸如电荷耦合器件(CCD)和互补金属氧化物半导体(CMOS))，并且生成捕获图像。传感器907可以包括一组传感器，诸如测量传感器、陀螺仪传感器、地磁传感器和加速度传感器。麦克风908将输入到智能电话900的声音转换为音频信号。输入装置909包括例如被配置为检测显示装置910的屏幕上的触摸的触摸传感器、小键盘、键盘、按钮或开关，并且接收从用户输入的操作或信息。显示装置910包括屏幕(诸如液晶显示器(LCD)和有机发光二极管(OLED)显示器)，并且显示智能电话900的输出图像。扬声器911 将从智能电话900输出的音频信号转换为声音。
无线通信接口912支持任何蜂窝通信方案(诸如LTE和LTE-先进)，并且执行无线通信。无线通信接口912通常可以包括例如BB处理器913和RF电路914。BB处理器913可以执行例如编码/解码、调制/解调以及复用/解复用，并且执行用于无线通信的各种类型的信号处理。同时，RF电路914可以包括例如混频器、滤波器和放大器，并且经由天线916来传送和接收无线信号。注意，图中虽然示出了一个RF链路与一个天线连接的情形，但是这仅是示意性的，还包括一个RF链路通过多个移相器与多个天线连接的情形。无线通信接口912可以为其上集成有BB处理器913和RF电路914的一个芯片模块。如图17所示，无线通信接口912可以包括多个BB处理器913和多个RF电路914。虽然图17示出其中无线通信接口912包括多个BB处理器913和多个RF电路914的示例，但是无线通信接口912也可以包括单个BB处理器913或单个RF电路914。
此外，除了蜂窝通信方案之外，无线通信接口912可以支持另外类型的无线通信方案，诸如短距离无线通信方案、近场通信方案和无线局域网(LAN)方案。在此情况下，无线通信接口912可以包括针对每种无线通信方案的BB处理器913和RF电路914。
天线开关915中的每一个在包括在无线通信接口912中的多个电路(例如用于不同的无线通信方案的电路)之间切换天线916的连接目的地。
天线916中的每一个均包括单个或多个天线元件(诸如包括在MIMO天线中的多个天线元件)，并且用于无线通信接口912传送和接收无线信号。如图17所示，智能电话900可以包括多个天线916。虽然图17示出其中智能电话900包括多个天线916的示例，但是智能电话900也可以包括单个天线916。
此外，智能电话900可以包括针对每种无线通信方案的天线916。在此情况下，天线开关915可以从智能电话900的配置中省略。
总线917将处理器901、存储器902、存储装置903、外部连接接口904、摄像装置906、传感器907、麦克风908、输入装置909、显示装置910、扬声器911、无线通信接口912以及辅助控制器919彼此连接。电 池918经由馈线向图17所示的智能电话900的各个块提供电力，馈线在图中被部分地示为虚线。辅助控制器919例如在睡眠模式下操作智能电话900的最小必需功能。
在图17所示的智能电话900中，电子设备200的收发单元201、收发器可以由无线通信接口912实现。功能的至少一部分也可以由处理器901或辅助控制器919实现。例如，处理器901或辅助控制器919可以通过执行收发单元201和识别单元202的功能来实现基于聚合波束的快速波束训练方法。
(第二应用示例)
图18是示出可以应用本公开内容的技术的汽车导航设备920的示意性配置的示例的框图。汽车导航设备920包括处理器921、存储器922、全球定位系统(GPS)模块924、传感器925、数据接口926、内容播放器927、存储介质接口928、输入装置929、显示装置930、扬声器931、无线通信接口933、一个或多个天线开关936、一个或多个天线937以及电池938。
处理器921可以为例如CPU或SoC，并且控制汽车导航设备920的导航功能和另外的功能。存储器922包括RAM和ROM，并且存储数据和由处理器921执行的程序。
GPS模块924使用从GPS卫星接收的GPS信号来测量汽车导航设备920的位置(诸如纬度、经度和高度)。传感器925可以包括一组传感器，诸如陀螺仪传感器、地磁传感器和空气压力传感器。数据接口926经由未示出的终端而连接到例如车载网络941，并且获取由车辆生成的数据(诸如车速数据)。
内容播放器927再现存储在存储介质(诸如CD和DVD)中的内容，该存储介质被插入到存储介质接口928中。输入装置929包括例如被配置为检测显示装置930的屏幕上的触摸的触摸传感器、按钮或开关，并且接收从用户输入的操作或信息。显示装置930包括诸如LCD或OLED显示器的屏幕，并且显示导航功能的图像或再现的内容。扬声器931输出导航功能的声音或再现的内容。
无线通信接口933支持任何蜂窝通信方案(诸如LTE和LTE-先进)，并且执行无线通信。无线通信接口933通常可以包括例如BB处理器934 和RF电路935。BB处理器934可以执行例如编码/解码、调制/解调以及复用/解复用，并且执行用于无线通信的各种类型的信号处理。同时，RF电路935可以包括例如混频器、滤波器和放大器，并且经由天线937来传送和接收无线信号。无线通信接口933还可以为其上集成有BB处理器934和RF电路935的一个芯片模块。如图18所示，无线通信接口933可以包括多个BB处理器934和多个RF电路935。虽然图18示出其中无线通信接口933包括多个BB处理器934和多个RF电路935的示例，但是无线通信接口933也可以包括单个BB处理器934或单个RF电路935。
此外，除了蜂窝通信方案之外，无线通信接口933可以支持另外类型的无线通信方案，诸如短距离无线通信方案、近场通信方案和无线LAN方案。在此情况下，针对每种无线通信方案，无线通信接口933可以包括BB处理器934和RF电路935。
天线开关936中的每一个在包括在无线通信接口933中的多个电路(诸如用于不同的无线通信方案的电路)之间切换天线937的连接目的地。
天线937中的每一个均包括单个或多个天线元件(诸如包括在MIMO天线中的多个天线元件)，并且用于无线通信接口933传送和接收无线信号。如图18所示，汽车导航设备920可以包括多个天线937。虽然图18示出其中汽车导航设备920包括多个天线937的示例，但是汽车导航设备920也可以包括单个天线937。
此外，汽车导航设备920可以包括针对每种无线通信方案的天线937。在此情况下，天线开关936可以从汽车导航设备920的配置中省略。
电池938经由馈线向图18所示的汽车导航设备920的各个块提供电力，馈线在图中被部分地示为虚线。电池938累积从车辆提供的电力。
在图18示出的汽车导航设备920中，电子设备200的收发单元201、收发器可以由无线通信接口933实现。功能的至少一部分也可以由处理器921实现。例如，处理器921可以通过执行收发单元201和识别单元202的功能来实现基于聚合波束的快速波束训练方法。
本公开内容的技术也可以被实现为包括汽车导航设备920、车载网络941以及车辆模块942中的一个或多个块的车载系统(或车辆)940。 车辆模块942生成车辆数据(诸如车速、发动机速度和故障信息)，并且将所生成的数据输出至车载网络941。
以上结合具体实施例描述了本公开的基本原理，但是，需要指出的是，对本领域的技术人员而言，能够理解本公开的方法和装置的全部或者任何步骤或部件，可以在任何计算装置(包括处理器、存储介质等)或者计算装置的网络中，以硬件、固件、软件或者其组合的形式实现，这是本领域的技术人员在阅读了本公开的描述的情况下利用其基本电路设计知识或者基本编程技能就能实现的。
而且，本公开还提出了一种存储有机器可读取的指令代码的程序产品。所述指令代码由机器读取并执行时，可执行上述根据本公开实施例的方法。
相应地，用于承载上述存储有机器可读取的指令代码的程序产品的存储介质也包括在本公开的公开中。所述存储介质包括但不限于软盘、光盘、磁光盘、存储卡、存储棒等等。
在通过软件或固件实现本公开的情况下，从存储介质或网络向具有专用硬件结构的计算机(例如图19所示的通用计算机1900)安装构成该软件的程序，该计算机在安装有各种程序时，能够执行各种功能等。
在图19中，中央处理单元(CPU)1901根据只读存储器(ROM)1902中存储的程序或从存储部分1908加载到随机存取存储器(RAM)1903的程序执行各种处理。在RAM 1903中，也根据需要存储当CPU 1901执行各种处理等等时所需的数据。CPU 1901、ROM 1902和RAM 1903经由总线1904彼此连接。输入/输出接口1905也连接到总线1904。
下述部件连接到输入/输出接口1905：输入部分1906(包括键盘、鼠标等等)、输出部分1907(包括显示器，比如阴极射线管(CRT)、液晶显示器(LCD)等，和扬声器等)、存储部分1908(包括硬盘等)、通信部分1909(包括网络接口卡比如LAN卡、调制解调器等)。通信部分1909经由网络比如因特网执行通信处理。根据需要，驱动器1910也可连接到输入/输出接口1905。可移除介质1911比如磁盘、光盘、磁光盘、半导体存储器等等根据需要被安装在驱动器1910上，使得从中读出的计算机程序根据需要被安装到存储部分1908中。
在通过软件实现上述系列处理的情况下，从网络比如因特网或存储介质比如可移除介质1911安装构成软件的程序。
本领域的技术人员应当理解，这种存储介质不局限于图19所示的其中存储有程序、与设备相分离地分发以向用户提供程序的可移除介质1911。可移除介质1911的例子包含磁盘(包含软盘(注册商标))、光盘(包含光盘只读存储器(CD-ROM)和数字通用盘(DVD))、磁光盘(包含迷你盘(MD)(注册商标))和半导体存储器。或者，存储介质可以是ROM 1902、存储部分1908中包含的硬盘等等，其中存有程序，并且与包含它们的设备一起被分发给用户。
还需要指出的是，在本公开的装置、方法和系统中，各部件或各步骤是可以分解和/或重新组合的。这些分解和/或重新组合应该视为本公开的等效方案。并且，执行上述系列处理的步骤可以自然地按照说明的顺序按时间顺序执行，但是并不需要一定按时间顺序执行。某些步骤可以并行或彼此独立地执行。
最后，还需要说明的是，术语“包括”、“包含”或者其任何其他变体意在涵盖非排他性的包含，从而使得包括一系列要素的过程、方法、物品或者设备不仅包括那些要素，而且还包括没有明确列出的其他要素，或者是还包括为这种过程、方法、物品或者设备所固有的要素。此外，在没有更多限制的情况下，由语句“包括一个……”限定的要素，并不排除在包括所述要素的过程、方法、物品或者设备中还存在另外的相同要素。
以上虽然结合附图详细描述了本公开的实施例，但是应当明白，上面所描述的实施方式只是用于说明本公开，而并不构成对本公开的限制。对于本领域的技术人员来说，可以对上述实施方式作出各种修改和变更而没有背离本公开的实质和范围。因此，本公开的范围仅由所附的权利要求及其等效含义来限定。

Claims (30)

  1. 一种用于无线通信的电子设备，包括：
    处理电路，被配置为：
    基于预先设定的聚合权重矩阵对预设的波束码本中的在角度域上远离的多个波束进行波束聚合，以获得聚合波束；以及
    向用户设备发送所述聚合波束，以用于识别所述预设的波束码本中针对所述用户设备的最优波束。
  2. 根据权利要求1所述的电子设备，其中，所述多个波束为通过对所述预设的波束码本中的波束进行分组而获得的多个波束组中的每一个波束组中的波束。
  3. 根据权利要求2所述的电子设备，其中，所述处理电路被配置为从所述预设的波束码本中的波束中以预定索引间隔选择波束来构成一个波束组，并且通过偏移第一个波束的索引来构成不同的波束组。
  4. 根据权利要求2所述的电子设备，其中，所述处理电路被配置为基于所述聚合权重矩阵，对每一个波束组中的波束进行多次波束聚合，以获得多个聚合波束，并且向所述用户设备依次发送所述多个聚合波束。
  5. 根据权利要求1所述的电子设备，其中，所述处理电路还被配置为向所述用户设备发送指示所应用的聚合权重矩阵的指示信息。
  6. 根据权利要求4所述的电子设备，其中，所述聚合权重矩阵的每一列代表针对一个聚合波束的权重向量，其中，所述聚合权重矩阵被设置为使得不同行的内积最小化。
  7. 根据权利要求6所述的电子设备，其中，所述聚合权重矩阵基于P阶的离散傅里叶变换矩阵获得，其中，所述P为每个波束组中的波束数量。
  8. 根据权利要求4所述的电子设备，其中，所述处理电路被配置为分别使用各个聚合波束承载具有不同索引的同步信号块。
  9. 根据权利要求4所述的电子设备，其中，所述处理电路还被配置为从所述用户设备接收所识别的最优波束的指示信息。
  10. 根据权利要求9所述的电子设备，其中，所述指示信息包括最优波束组序号和聚合权重序号，其中，所述用户设备识别出在所述最优波束组序号对应的波束组中的由所述聚合权重序号代表的波束为最优波束。
  11. 根据权利要求1所述的电子设备，其中，所述预先设定的聚合权重矩阵对于基站和所述用户设备是已知的。
  12. 一种用于无线通信的电子设备，包括：
    处理电路，被配置为：
    接收基站发送的聚合波束，其中，所述聚合波束由所述基站通过基于预先设定的聚合权重矩阵对预设的波束码本中的在角度域上远离的多个波束进行波束聚合获得；以及
    通过对所述聚合波束的接收来识别所述预设的波束码本中针对用户设备的最优波束。
  13. 根据权利要求12所述的电子设备，其中，所述多个波束为通过对所述预设的波束码本中的波束进行分组而获得的多个波束组中的每一个波束组中的波束。
  14. 根据权利要求13所述的电子设备，其中，从所述预设的波束码本中的波束中以预定索引间隔选择波束来构成一个波束组，并且通过偏移第一个波束的索引来构成不同的波束组。
  15. 根据权利要求13所述的电子设备，其中，所述基站基于所述聚合权重矩阵，对每一个波束组中的波束进行多次波束聚合而获得多个聚合波束并且依次发送所述多个聚合波束，
    所述处理电路被配置为接收每一个波束组的所述多个聚合波束，并且基于对各个波束组的聚合波束的接收使用所述聚合权重矩阵来确定所述最优波束。
  16. 根据权利要求12所述的电子设备，其中，所述处理电路还被配置为从所述基站接收指示所应用的聚合权重矩阵的指示信息。
  17. 根据权利要求15所述的电子设备，其中，所述聚合权重矩阵的每一列代表针对一个聚合波束的权重向量，其中，所述聚合权重矩阵被设置为使得不同行的内积最小化。
  18. 根据权利要求17所述的电子设备，其中，所述聚合权重矩阵基于P阶的离散傅里叶变换矩阵获得，其中，所述P为每个波束组中的波束数量。
  19. 根据权利要求15所述的电子设备，其中，所述处理电路被配置为基于对各个波束组的聚合波束的接收来确定最优波束组，并且在所述最优波束组中确定最优波束。
  20. 根据权利要求19所述的电子设备，其中，所述处理电路被配置为基于针对每一个波束组的多个聚合波束的平均接收功率来确定所述最优波束组，并且通过对针对所述最优波束组的多个聚合波束的接收信号与所述聚合权重矩阵的每一行进行相关检测来确定所述最优波束。
  21. 根据权利要求20所述的电子设备，其中，所述处理电路被配置为将平均接收功率最大的波束组确定为所述最优波束组，并且将检测的相关系数最大的行对应的波束确定为所述最优波束。
  22. 根据权利要求15所述的电子设备，其中，所述处理电路还被配置为向所述基站发送所识别的最优波束的指示信息。
  23. 根据权利要求22所述的电子设备，其中，所述指示信息包括最优波束组序号和聚合权重序号，其中，所述处理电路确定在所述最优波束组序号对应的波束组中的由所述聚合权重序号代表的波束为最优波束。
  24. 根据权利要求23所述的电子设备，其中，所述最优波束组序号由同步信号块索引指示。
  25. 根据权利要求22所述的电子设备，其中，所述处理电路被配置为在随机接入阶段发送所述指示信息。
  26. 根据权利要求15所述的电子设备，其中，各个聚合波束由具有不同索引的同步信号块承载。
  27. 根据权利要求12所述的电子设备，其中，所述预先设定的聚合权重矩阵对于所述基站和所述用户设备是已知的。
  28. 一种用于无线通信的方法，包括：
    基于预先设定的聚合权重矩阵对预设的波束码本中的在角度域上远离的多个波束进行波束聚合，以获得聚合波束；以及
    向用户设备发送所述聚合波束，以用于识别所述预设的波束码本中针对所述用户设备的最优波束。
  29. 一种用于无线通信的方法，包括：
    接收基站发送的聚合波束，其中，所述聚合波束由所述基站通过基于预先设定的聚合权重矩阵对预设的波束码本中的在角度域上远离的多个波束进行波束聚合获得；以及
    通过对所述聚合波束的接收来识别所述预设的波束码本中针对用户设备的最优波束。
  30. 一种计算机可读存储介质，其上存储有计算机可执行指令，当所述计算机可执行指令被执行时，执行根据权利要求28或权利要求29所述的用于无线通信的方法。
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