Beam alignment training method and apparatus

Abstract

The present application provides a beam alignment training method and apparatus. The method comprises: an initiator sends M pieces of first beam measurement data, wherein the M pieces of first beam measurement data correspond to M measurement beams; the initiator receives a combined coefficient set, wherein the combined coefficient set is determined by a responder on the basis of the M pieces of first beam measurement data, the combined coefficient set comprises M beam weighting coefficients, an m-th beam weighting coefficient corresponds to m-th piece of first beam measurement data, the m-th beam weighting coefficient represents a weight value of an m-th measurement beam among the M measurement beams, 1≤m≤M, and m and M are positive integers; and the initiator determines a combined beam on the basis of the combined coefficient set and the M measurement beams. In this way, the combined beam can better match the actual air interface channel direction and better utilizes channel gain, thereby achieving precision beam alignment and improving the coverage performance.

Description

Beam alignment training method and device

[0001] This application claims priority to the Chinese patent application with application number 202311289449.X filed with the State Intellectual Property Office of China on September 27, 2023, and priority to the Chinese patent application with the invention name “Beam Alignment Training Method and Device”, all contents of which are incorporated by reference into this application. Technical Field

[0002] The present application relates to the field of communications, and more particularly, to a beam alignment training method and apparatus. Background Art

[0003] Currently, IEEE 802.11ad / ay is one of the standards for wireless local area network (WLAN) communications in the millimeter wave frequency band. Hybrid analog-digital beamforming (HAD-BF) is a technology used to overcome signal attenuation in the millimeter wave band. HAD-BF selects the optimal beam through beam alignment training.

[0004] However, the beams sent by the transmitter (initiator) of HAD-BF technology are pre-set codebook beams with fixed directions. Because the codebook beams divide the angular space in a predetermined manner, if the main lobes of the codebook beams sent by the receiver (responder) during simulated beam alignment training and the transmitter are not perfectly aligned, the receiver will not achieve maximum beam gain. Similarly, when millimeter wave signals have reflection paths, a single beam cannot cover all channel angles, and the receiver will not be able to obtain full channel gain.

[0005] Therefore, how to improve the performance of beam alignment training is an urgent problem to be solved.

[0006] Summary of the Invention

[0007] The present application provides a beam alignment training method and device, which can better match the actual air interface channel direction, better utilize the channel gain, and thus achieve precise beam alignment and improve coverage performance.

[0008] In a first aspect, a beam alignment training method is provided. The method includes: a transmitting end transmitting M first beam measurement data, where the M first beam measurement data correspond to M measurement beams. The transmitting end receives a combining coefficient set, where the combining coefficient set is determined by the receiving end based on the M first beam measurement data, and the combining coefficient set includes M beam weighting coefficients, where the mth beam weighting coefficient corresponds to the mth first beam measurement data, and the mth beam weighting coefficient represents the weight of the mth measurement beam among the M measurement beams, where 1≤m≤M, and m and M are positive integers. The transmitting end determines a combining beam based on the combining coefficient set and the M measurement beams.

[0009] In the above technical solution, the transmitter obtains the beam weighting coefficients corresponding to multiple measurement beams and combines them with the original measurement beam to synthesize a new combined beam. The combined beam can better match the actual air interface channel direction and better utilize the channel gain, thereby achieving precise beam alignment and improving coverage performance. For example, in a scenario where the receiver is not fully aligned with the main lobe of the measurement beam, the combined beam obtained by combining the coefficient set can better utilize the channel gain to achieve precise beam alignment. For another example, in the presence of NLOS scenarios in the millimeter wave channel, when a single beam cannot cover all channel angles, the combined beam obtained by combining the coefficient set comprehensively considers the channel gain of all beams, achieves precise beam alignment, and improves coverage performance.

[0010] In conjunction with the first aspect, in certain implementations of the first aspect, before the transmitting end transmits M first beam measurement data, the method further includes: the transmitting end transmitting N second beam measurement data, where the N second beam measurement data correspond to N measurement beams. The transmitting end receives N second signal-to-noise ratios, where the nth second signal-to-noise ratio corresponds to the nth measurement beam. Among the N second signal-to-noise ratios, measurement beams corresponding to second signal-to-noise ratios greater than a preset threshold are determined as M measurement beams, where 1 ≤ n ≤ N, n and N are positive integers, and M < N.

[0011] In the above technical solution, the measurement beam obtained after one round of beam alignment training is used for the next round of beam alignment training, which can reduce the beam overhead and the computational complexity of the receiving end, and can limit the signal-to-noise ratio fluctuation of the measurement beam during the next round of intra-packet beam alignment training, thereby making the calculated merging coefficient set more accurate.

[0012] In conjunction with the first aspect, in certain implementations of the first aspect, the method further includes: the transmitting end receiving M first signal-to-noise ratios and an estimated combined signal-to-noise ratio, where the M first signal-to-noise ratios are obtained by the receiving end based on M first beam measurement data, and the estimated combined signal-to-noise ratio is determined by the receiving end based on the M first beam measurement data and a combining coefficient set. The transmitting end determines, based on the M first signal-to-noise ratios and the estimated combined signal-to-noise ratio, to use the combined beam for data transmission, or determines to use the measurement beam corresponding to the largest first signal-to-noise ratio among the M first signal-to-noise ratios for data transmission.

[0013] In the above technical solution, the transmitter comprehensively considers the M first signal-to-noise ratios and the estimated combined signal-to-noise ratio to select a more reasonable beam for subsequent data transmission, thereby achieving precise beam alignment and improving coverage performance.

[0014] In combination with the first aspect, in certain implementations of the first aspect, M first beam measurement data are carried in a non-data packet NDP, or M first beam measurement data are carried in one or M protocol data unit PPDU data packets.

[0015] When the M first beam measurement data are carried in one NDP or one PPDU data packet, the M first beam measurement data may be M training fields.

[0016] In the above technical solution, when M first beam measurement data are carried in one NDP, the channel measurement compression feedback method of the current mainstream Wi-Fi protocol can be used, which is compatible with high- and low-frequency fusion scenarios.

[0017] In a second aspect, a beam alignment training method is provided, including: a receiving end receiving M first beam measurement data, where the M first beam measurement data correspond to the M measurement beams. The receiving end determines a combining coefficient set based on the M first beam measurement data, where the combining coefficient set includes M beam weighting coefficients, where the mth beam weighting coefficient corresponds to the mth first beam measurement data, and the mth beam weighting coefficient represents the weight of the mth measurement beam among the M measurement beams, where 1≤m≤M, and m and M are positive integers. The receiving end transmits the combining coefficient set.

[0018] It should be understood that the beneficial effects corresponding to the solution of the second aspect are similar to those of the first aspect. For detailed description, reference can be made to the first aspect and no further details will be given here.

[0019] In conjunction with the second aspect, in certain implementations of the second aspect, the receiving end determining the merging coefficient set based on the M first beam measurement data includes: the receiving end determining M first channel estimation results based on the M first beam measurement data. The receiving end determines a full-band channel covariance matrix corresponding to the M first channel estimation results, where the full-band channel covariance matrix is ​​obtained by summing and averaging K M×M dimensional channel covariance matrices corresponding to K subcarriers, where K is a positive integer. The receiving end performs singular value decomposition on the full-band channel covariance matrix to obtain the merging coefficient set.

[0020] In the above technical solution, for millimeter wave high-frequency beam alignment training, the full-band channel covariance matrix is ​​subjected to singular value decomposition to obtain a combined coefficient set. This not only reduces complexity but also can continue to use the channel measurement compression feedback method of the current mainstream Wi-Fi protocol, with good compatibility.

[0021] In conjunction with the second aspect, in certain implementations of the second aspect, before receiving the M first beam measurement data, the method further includes: the receiving end receiving N second beam measurement data, where the N second beam measurement data correspond to N measurement beams, 1≤n≤N, and n and N are positive integers. The receiving end determines N second signal-to-noise ratios based on the N second beam measurement data, where the nth second signal-to-noise ratio corresponds to the nth measurement beam. The receiving end transmits the N second signal-to-noise ratios.

[0022] In conjunction with the second aspect, in certain implementations of the second aspect, the method further includes: the receiving end determining a combined estimation result based on the combining coefficient set and the M first channel estimation results; the receiving end determining an estimated combined signal-to-noise ratio based on the combined estimation result; the receiving end determining M first signal-to-noise ratios based on the M first channel estimation results; and the receiving end transmitting the M first signal-to-noise ratios and the estimated combined signal-to-noise ratio.

[0023] In combination with the second aspect, in certain implementations of the second aspect, M first beam measurement data are carried in a non-data packet NDP, or M first beam measurement data are carried in one or M protocol data unit PPDU data packets.

[0024] In a third aspect, a beam alignment training device is provided, comprising a transceiver unit and a processing unit: the transceiver unit is configured to transmit M first beam measurement data, where the M first beam measurement data correspond to the M measurement beams. The transceiver unit is configured to receive a merging coefficient set, where the merging coefficient set is determined by a receiving end based on the M first beam measurement data, the merging coefficient set including M beam weighting coefficients, where the mth beam weighting coefficient corresponds to the mth first beam measurement data, and the mth beam weighting coefficient represents the weight of the mth measurement beam among the M measurement beams, where 1≤m≤M, and m and M are positive integers. The processing unit is configured to determine a merging beam based on the merging coefficient set and the M measurement beams.

[0025] It should be understood that the beneficial effects corresponding to the solution of the third aspect are similar to those of the first aspect and will not be elaborated here.

[0026] In conjunction with the third aspect, in certain implementations of the third aspect, before the transceiver unit is configured to transmit M first beam measurement data, the transceiver unit is further configured to: transmit N second beam measurement data, where the N second beam measurement data correspond to the N measurement beams; and receive N second signal-to-noise ratios, where the nth second signal-to-noise ratio corresponds to the nth measurement beam. The processing unit is further configured to: determine the measurement beams corresponding to the second signal-to-noise ratios greater than a preset threshold among the N second signal-to-noise ratios as M measurement beams, where 1≤n≤N, n and N are positive integers, and M<N.

[0027] In conjunction with the third aspect, in certain implementations of the third aspect, the transceiver unit is further configured to: receive M first signal-to-noise ratios and an estimated combined signal-to-noise ratio, where the M first signal-to-noise ratios are obtained by the receiving end based on M first beam measurement data, and the estimated combined signal-to-noise ratio is determined by the receiving end based on the M first beam measurement data and a combining coefficient set. The processing unit is further configured to: determine, based on the M first signal-to-noise ratios and the estimated combined signal-to-noise ratio, to use the combined beam for data transmission, or to determine to use the measurement beam corresponding to the largest first signal-to-noise ratio among the M first signal-to-noise ratios for data transmission.

[0028] In combination with the third aspect, in certain implementations of the third aspect, M first beam measurement data are carried in a non-data packet NDP, or M first beam measurement data are carried in one or M protocol data unit PPDU data packets.

[0029] In a fourth aspect, a beam alignment training device is provided, comprising a transceiver unit and a processing unit: the transceiver unit is configured to receive M first beam measurement data, where the M first beam measurement data correspond to the M measurement beams. The processing unit is configured to determine a combining coefficient set based on the M first beam measurement data, where the combining coefficient set includes M beam weighting coefficients, where the mth beam weighting coefficient corresponds to the mth first beam measurement data, and the mth beam weighting coefficient represents the weight of the mth measurement beam among the M measurement beams, where 1≤m≤M, and m and M are positive integers. The transceiver unit is configured to transmit the combining coefficient set.

[0030] It should be understood that the beneficial effects corresponding to the solution of the fourth aspect are similar to those of the second aspect and will not be elaborated here.

[0031] In conjunction with the fourth aspect, in certain implementations of the fourth aspect, the processing unit is specifically configured to: determine M first channel estimation results based on the M first beam measurement data; determine a full-band channel covariance matrix corresponding to the M first channel estimation results, where the full-band channel covariance matrix is ​​obtained by summing and averaging K M×M dimensional channel covariance matrices corresponding to K subcarriers, where K is a positive integer; and perform singular value decomposition on the full-band channel covariance matrix to obtain a combined coefficient set.

[0032] In conjunction with the fourth aspect, in certain implementations of the fourth aspect, before the transceiver unit receives M first beam measurement data, the transceiver unit is further configured to: receive N second beam measurement data, where the N second beam measurement data correspond to N measurement beams, where 1 ≤ n ≤ N, and n and N are positive integers. The processing unit is further configured to determine N second signal-to-noise ratios based on the N second beam measurement data, where the nth second signal-to-noise ratio corresponds to the nth measurement beam. The transceiver unit is further configured to transmit the N second signal-to-noise ratios.

[0033] In conjunction with the fourth aspect, in certain implementations of the fourth aspect, the processing unit is further configured to: determine a combined estimation result based on the combining coefficient set and the M first channel estimation results; determine an estimated combined signal-to-noise ratio based on the combined estimation result; and determine M first signal-to-noise ratios based on the M first channel estimation results. The transceiver unit is further configured to transmit the M first signal-to-noise ratios and the estimated combined signal-to-noise ratio.

[0034] In combination with the fourth aspect, in certain implementations of the fourth aspect, M first beam measurement data are carried in a non-data packet NDP, or M first beam measurement data are carried in one or M protocol data unit PPDU data packets.

[0035] In a fifth aspect, a beam alignment training device is provided, which includes: a memory for storing programs; a processor for executing computer programs or instructions stored in the memory, and when the computer program or instructions stored in the memory are executed, the processor is used to execute the method provided in any one of the implementation methods of the first or second aspect above.

[0036] In one implementation, the device is a transmitter or receiver in beam alignment training.

[0037] In another implementation, the device is a chip, a chip system, or a circuit in a transmitter or receiver in beam alignment training.

[0038] In a sixth aspect, the present application provides a processor for executing the method provided by any one of the implementation modes of the first to second aspects above. In the process of executing these methods, the process of sending the above information and obtaining / receiving the above information in the above methods can be understood as the process of the processor outputting the above information, and the process of the processor receiving the input above information. When outputting the above information, the processor outputs the above information to the interface and transmits it through the interface. After being output by the processor, the above information may also need to undergo other processing before reaching the interface. Similarly, when the processor receives the input above information, the interface obtains / receives the above information and inputs it into the processor. Furthermore, after the interface receives the above information, the above information may need to undergo other processing before being input into the processor.

[0039] For the operations involved, such as transmission, sending, and acquisition / reception, unless otherwise specified, or if they do not conflict with their actual functions or internal logic in the relevant descriptions, they can be understood as output and reception, input and other operations, and can also be understood as transmission, sending and receiving operations performed by radio frequency circuits and antennas. This application does not limit this.

[0040] During implementation, the processor may be a processor specifically configured to execute the methods, or may be a processor that executes computer programs or instructions in a memory to execute the methods, such as a general-purpose processor. The memory may be a non-transitory memory, such as a read-only memory (ROM), which may be integrated with the processor on the same chip or disposed on separate chips. The embodiments of the present application do not limit the type of memory or the configuration of the memory and the processor.

[0041] In a seventh aspect, a computer-readable storage medium is provided, which stores a program code for execution by a device, and the program code includes a method for executing any one of the implementations of the first to second aspects above.

[0042] In an eighth aspect, a computer program product comprising instructions is provided, which, when run on a computer, enables the computer to execute the method provided in any one of the implementations of the first to second aspects above.

[0043] In the ninth aspect, a chip is provided, which includes a processor and a communication interface. The processor reads instructions stored in a memory through the communication interface and executes the method provided in any one of the implementation methods of the first to second aspects above.

[0044] Optionally, as an implementation method, the chip may also include a memory, in which a computer program or instruction is stored, and the processor is used to execute the computer program or instruction stored in the memory. When the computer program or instruction is executed, the processor is used to execute the method provided in any one of the implementation methods of the first to second aspects above. BRIEF DESCRIPTION OF THE DRAWINGS

[0045] FIG1 is a schematic diagram of a wireless communication application scenario provided by an embodiment of the present invention;

[0046] FIG2 is a schematic diagram of an analog-digital hybrid beamforming structure provided in an embodiment of the present application;

[0047] FIG3 is a schematic diagram of a beam alignment training method provided in an embodiment of the present application;

[0048] FIG4 is a schematic diagram of a beam alignment training scenario provided in an embodiment of the present application;

[0049] FIG5 is a flow chart of an interactive beam alignment training method according to an embodiment of the present application;

[0050] FIG6 is an interactive schematic diagram of another beam alignment training method provided in an embodiment of the present application;

[0051] FIG7 is an interactive schematic diagram of another beam alignment training method provided in an embodiment of the present application;

[0052] FIG8 is an interactive schematic diagram of yet another beam alignment training method provided in an embodiment of the present application;

[0053] FIG9 is a schematic diagram of a beam alignment training device 900 provided in an embodiment of the present application;

[0054] FIG10 is a schematic structural diagram of a beam alignment training device 1000 provided in an embodiment of the present application;

[0055] FIG11 is a schematic diagram of a chip system 1100 provided in an embodiment of the present application. DETAILED DESCRIPTION

[0056] The technical solution in this application will be described below with reference to the accompanying drawings.

[0057] To facilitate understanding of the embodiments of the present application, the following points are explained:

[0058] First, in this application, unless otherwise specified or there is a logical conflict, the terms and / or descriptions between different embodiments are consistent and can be referenced by each other. The technical features in different embodiments can be combined to form new embodiments based on their internal logical relationships.

[0059] Second, in this application, "at least one" means one or more, and "more" means two or more. "And / or" describes the association relationship of associated objects, indicating that three relationships may exist. For example, A and / or B can mean: A exists alone, A and B exist at the same time, and B exists alone, where A and B can be singular or plural. In the text description of this application, the character " / " generally indicates that the previous and next associated objects are in an "or" relationship. "At least one of the following" or similar expressions refers to any combination of these items, including any combination of single or plural items. For example, at least one of a, b and c can mean: a, or b, or c, or a and b, or a and c, or b and c, or a, b and c. Wherein a, b and c can be single or multiple, respectively.

[0060] Third, throughout this application, the terms "first," "second," and various numerical references (e.g., #1, #2, etc.) are used for ease of description and are not intended to limit the scope of the embodiments of this application. For example, they are used to distinguish between different beam measurement data, rather than to describe a specific order or precedence. It should be understood that these terms are interchangeable where appropriate to describe solutions beyond the embodiments of this application.

[0061] It should be noted that, in the following text, information #1, resource indication information #1, and resource request information #1 have different meanings. It should be understood that the names of the various information are merely examples and are not intended to limit this application and should not constitute any limitation on the technical solution of this application.

[0062] Fourth, in this application, expressions such as "when," "under the circumstances of," and "if" all imply that a corresponding action will be taken under certain objective circumstances. They do not limit the timeframe, do not require a judgment action to be taken when the action is taken, and do not imply any other limitations. Furthermore, the judgment action following these conditional conjunctions does not imply that the judgment action following the conditional conjunctions is the only condition for achieving the result; additional conditions may also be included to achieve the result.

[0063] Fifth, in this application, the terms "include" and "have" and any variations thereof are intended to cover non-exclusive inclusions. For example, a process, method, system, product or apparatus that includes a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units that are not explicitly listed or are inherent to these processes, methods, products or apparatuses.

[0064] Sixth, in this application, "used to indicate" can include being used for direct indication and being used for indirect indication. When describing that a certain indication information is used to indicate A, it can include that the indication information directly indicates A or indirectly indicates A, and it does not mean that the indication information must carry A.

[0065] The indication methods involved in the embodiments of this application should be understood to encompass various methods that enable the party to be indicated to obtain information to be indicated. The information to be indicated can be sent as a whole or divided into multiple sub-information and sent separately. The transmission period and / or timing of these sub-information can be the same or different. This application does not limit the specific transmission method.

[0066] In the embodiments of the present application, the "indication information" may be an explicit indication, i.e., a direct indication via signaling, or may be obtained based on parameters indicated by the signaling, in combination with other rules, other parameters, or by deduction. It may also be an implicit indication, i.e., based on a rule or relationship, or based on other parameters, or by deduction. This application does not impose specific limitations on this.

[0067] Seventh, in this application, "storage" may refer to storage in one or more memories. The one or more memories may be provided separately or integrated into an encoder or decoder, a processor, or a communication device. The one or more memories may also be provided in part separately and in part integrated into a decoder, a processor, or a communication device. The memory may be any type of storage medium and is not limited in this application.

[0068] The technical solution provided in the embodiments of the present application can be applied to wireless local area network (WLAN) scenarios, for example, supporting IEEE 802.11 related standards, such as 802.11be, 802.11ad, 802.11ay or 802.11bf, and Wi-Fi 8, etc. It can also be applied to wireless personal area network systems based on ultra-wide band (UWB), such as the 802.15 series of standards, and can also be applied to sensing systems, such as the 802.11bf series of standards, and can also be applied to millimeter wave (mmWave), such as the 802.11ad series of standards, and can also be applied to wireless fidelity artificial intelligence (Wi-Fi AI). Among them, the 802.11be standard is called extremely high throughput (EHT). Among them, 802.11bf includes two major categories of standards: low frequency (Sub-7GHz) and high frequency (60GHz). Sub-7GHz implementations primarily rely on standards such as 802.11ax, 802.11be, and their next generations, while 60GHz implementations primarily rely on standards such as 802.11ad, 802.11ay, and their next generations. 802.11ad is also known as the directional multi-gigabit (DMG) standard, and 802.11ay is also known as the enhanced directional multi-gigabit (EDMG) standard.

[0069] Although the embodiments of the present application are primarily described using the deployment of a WLAN network, particularly a network using the IEEE 802.11 system standard, as an example, those skilled in the art will readily appreciate that the various aspects of the embodiments of the present application can be extended to other networks using various standards or protocols, such as a high-performance wireless local area network (HIPERLAN), a wireless wide area network (WWAN), a wireless personal area network (WPAN), or other networks now known or developed in the future. Therefore, regardless of the coverage area and wireless access protocol used, the various aspects provided in the embodiments of the present application can be applied to any suitable wireless network.

[0070] The technical solutions of the embodiments of the present application can also be applied to various communication systems, such as WLAN communication systems, Wi-Fi systems, fifth-generation (5G) systems or new radio (NR), future sixth-generation (6G) systems, Internet of Things (IoT) networks, or vehicle-to-everything (V2X) networks.

[0071] The above-mentioned communication system applicable to the present application is only an example, and the communication system applicable to the present application is not limited to this. It is described uniformly here and will not be repeated below.

[0072] Figure 1 is a schematic diagram of a wireless communication application scenario provided by the embodiment itself. The millimeter wave communication scenario shown in Figure 1 can support communication between a transmitter and at least one receiver. For example, the transmitter communicates with receiver #1, and receiver #2 communicates with receiver #3. The embodiment of the present application does not limit the number of receivers. The embodiment of the present application is not only applicable to communication between a transmitter and at least one receiver, but also to mutual communication between a receiver and at least one transmitter. For ease of description, this application only takes the communication between a transmitter and at least one receiver as an example, but this description method does not have any limiting effect on the actual application scope of the technical solution of this application. This is explained uniformly here and will not be repeated later.

[0073] The transmitting end in the present application can be a device for communicating with the receiving end, and the network device can be a base station (base transceiver station, BTS) in the global system of mobile communication (GSM) system or code division multiple access (CDMA), or a base station (nodeB, NB) in a wideband code division multiple access (WCDMA) system, or an evolved base station (eNB or eNodeB) in an LTE system, or a wireless controller in a cloud radio access network (CRAN) scenario, or the network device can be a relay station, an access point, a vehicle-mounted device, a wearable device, a network device in a 5G network, and a network device in a future 6G network or a network device in a PLMN network, etc., and the embodiments of the present application are not limited.

[0074] The transmitter can be an access point (AP) that connects a receiver (such as a mobile phone) to a wired (or wireless) network. These devices are primarily deployed in homes, buildings, and campuses, with a typical coverage radius of tens to hundreds of meters. They can also be deployed outdoors. The transmitter acts as a bridge between wired and wireless networks, connecting wireless network clients and then connecting the wireless network to the Ethernet. Specifically, the transmitter can be a terminal device (such as a mobile phone) or a network device (such as a router) equipped with a Wi-Fi chip. The transmitter can be a device that supports the 802.11be standard. Access points can also be devices that support various WLAN standards within the 802.11 family, including 802.11ax, 802.11ac, 802.11n, 802.11g, 802.11b, 802.11a, 802.11ad, 802.11ay, 802.11aj, 802.11bf, and the next generation of 802.11be. The transmitter in this application can be a device that supports mmWave communication, or it can be a transmitter that is applicable to a future generation of Wi-Fi standards.

[0075] The receiving end in this application may refer to user equipment (UE), access terminal, user unit, user station, mobile station, mobile station, remote station, remote terminal, mobile device, user terminal, terminal, wireless communication device, user agent or user device. The terminal may also be a cellular phone, a cordless phone, a session initiation protocol (SIP) phone, a wireless local loop (WLL) station, a personal digital assistant (PDA), a handheld device with wireless communication function, a computing device or other processing device connected to a wireless modem, a vehicle-mounted device, a wearable device, a terminal device in a 5G network, a terminal device in a future 6G network or a terminal device in a public land mobile network (PLMN), etc., and the embodiments of this application are not limited to this.

[0076] The receiving end can be a wireless communication chip, a wireless sensor, or a wireless communication terminal, also referred to as a user. For example, the receiving end can be a mobile phone that supports Wi-Fi communication, a tablet that supports Wi-Fi communication, a set-top box that supports Wi-Fi communication, a smart TV that supports Wi-Fi communication, a smart wearable device that supports Wi-Fi communication, an in-vehicle communication device that supports Wi-Fi communication, or a computer that supports Wi-Fi communication. Optionally, the station can support the 802.11be standard. The station can also support 802.11ax, 802.11ac, 802.11n, 802.11g, 802.11b, 802.11a, 802.11ad, 802.11ay, 802.11aj, 802.11bf, and 802.11be next generation WLAN standards within the 802.11 family.

[0077] For example, the transmitter and receiver can be devices used in the Internet of Vehicles, IoT nodes and sensors in the IoT, smart cameras and remote controls in smart homes, smart water and electricity meters, and sensors in smart cities.

[0078] As described above, in order to overcome the signal attenuation in the millimeter wave band, the millimeter wave band generally adopts analog beams of analog-digital hybrid beamforming. Figure 2 is a schematic diagram of an analog-digital hybrid beamforming structure provided in an embodiment of the present application. As shown in Figure 2, digital beamforming is a baseband signal, and the frequency conversion and digital-to-analog conversion between the baseband signal and the radio frequency signal are respectively realized through the intermediate frequency unit and the digital-to-analog converter. Each digital domain channel will correspond to a phase shifter network, and each phase shifter network can generate different analog beams. In the embodiment of the present application, the analog beam can also be called a measurement beam, a codebook beam or a beam. The embodiment of the present application does not limit the names of the beams involved.

[0079] FIG3 is a schematic diagram of a beam alignment training method provided in an embodiment of the present application.

[0080] The IEEE 802.11.ad / ay standard applies to millimeter wave frequency band communications. Figure 3 shows two beam alignment training methods: Figure 3(a) shows the packet-by-packet beam alignment training method, and Figure 3(b) shows the in-packet beam alignment training method.

[0081] As shown in Figure 3(a), in the time domain, in the first step, the transmitter can continuously send multiple data packets. Each data packet is a complete presentation protocol data unit (PPDU), including a preamble and data. Each data packet can be sent using a different beam, with the direction of each beam determined by a pre-stored beam angle. As shown in Figure 3, data packet #1 is sent to the receiver via beam #1, data packet #2 is sent via beam #2, and so on. Data packet #N is sent to the receiver via beam #N. Each data packet can be a sector sweep packet (SSW packet) or a short sector sweep packet (short-SSW packet). In the second step, the receiver measures the signal-to-noise ratio (SNR) of each data packet. In the third step, the receiver feeds back the measured SNR and the corresponding beam identifier to the transmitter. In the fourth step, the transmitter selects the optimal transmission beam based on the feedback from the receiver.

[0082] To reduce beam overhead, a training (TRN) field is added to the PPDU. As shown in Figure 3(b), the process of intra-packet beam alignment training is similar to that of per-packet beam alignment training. The difference is that in the first step of intra-packet beam alignment training, only one PPDU is sent, and multiple training fields are added to the PPDU, each sent using a different beam.

[0083] Both of the aforementioned beam alignment training methods select the optimal beam based on the measured signal-to-noise ratio (SNR) and corresponding beam identifiers fed back by the receiver. However, since the measured beams are codebook beams with predetermined directions by the transmitter, and the number of predefined codebook beams is limited, in some scenarios, they cannot fully match the channel direction, preventing the receiver from achieving maximum beam gain and, consequently, the transmitter from determining the optimal beam based on the measurement results.

[0084] One scenario involves the main lobe of the transmitter's codebook beam not being perfectly aligned with that of the receiver, such as the positional relationship between transmitter and receiver #1 shown in Figure 1. In this scenario, the transmitter's predefined codebook beam divides the angular space. The transmitter's position is fixed, while the receiver's position is random. Since the main lobe of the transmitter's codebook beam is not perfectly aligned with that of the receiver, the receiver cannot achieve maximum beam gain. In this case, the transmitter cannot obtain the optimal beam based on feedback.

[0085] Another scenario involves non-line-of-sight (NLOS) scenarios in millimeter wave channels. Figure 4 is a schematic diagram of a beam alignment training scenario provided by an embodiment of the present application. As shown in Figure 4, beam #1 reflects off an obstacle and reaches the receiver. A single beam cannot cover all channel angles, resulting in the receiver being unable to obtain all channel gains. Consequently, the receiver cannot obtain the optimal beam based on the feedback results.

[0086] To solve the above problems, the present invention provides a beam alignment training method and apparatus, which will be described in detail below with reference to Figures 5 to 11 .

[0087] Figure 5 is a flow chart of a beam alignment training method provided by an embodiment of the present application. It should be understood that the interaction diagram of the present application uses the transmitter and receiver as examples of the execution subjects of the interaction diagram to illustrate the corresponding method, but the present application does not limit the execution subjects of the interaction diagram. For example, the transmitter in Figure 5 can also be a chip, chip system or processor that supports the transmitter to implement the corresponding method, or a logic module or software that can implement all or part of the functions of the transmitter. The receiver in Figure 5 can also be a chip, chip system or processor that supports the receiver to implement the corresponding method, or a logic module or software that can implement all or part of the functions of the receiver.

[0088] S501: A transmitting end sends M first beam measurement data to a receiving end, wherein the M first beam measurement data correspond to M measurement beams, and the mth measurement beam corresponds to the mth first beam measurement data.

[0089] It should be understood that the M measurement beams are a subset of the N measurement beams, where N=M, or 1≤M<N. The N measurement beams are all measurement beams corresponding to one digital domain transmission channel of the transmitter.

[0090] Different measurement beams correspond to different fixed directions. It should be understood that the M measurement beams are a proper subset of the N measurement beams, and in the case of 1≤M<N, the specific implementation will be described in detail in conjunction with FIG6 .

[0091] As a possible implementation manner, the M first beam measurement data may be carried in a null data packet (NDP), or the M first beam measurement data may be carried in one or M protocol data unit PPDU data packets.

[0092] For example, when M first beam measurement data are carried in M ​​PPDUs, the transmitter uses M measurement beams to send M PPDUs at equal intervals. This can also be understood as a packet-by-packet beam alignment training method, and the detailed process is described in conjunction with Figure 7(a).

[0093] For another example, when M first beam measurement data are carried in a non-data packet NDP or a PPBU data packet, the first beam measurement data can be a training field. The transmitter uses M measurement beams to send M training fields in a data packet. This can also be understood as an intra-packet beam alignment training method, or combined with a low-frequency NDP measurement method. The detailed process is described in detail in conjunction with Figure 7(b) and Figure 8.

[0094] S502. The receiving end determines a merging coefficient set based on the M first beam measurement data, where the merging coefficient set includes M beam weighting coefficients, the mth beam weighting coefficient corresponds to the mth first beam measurement data, and the mth beam weighting coefficient represents the weight of the mth measurement beam in the M measurement beams, 1≤m≤M, and m and M are positive integers.

[0095] As a possible implementation method, M first channel estimation results are determined based on M first beam measurement data; based on the M first channel estimation results, a full-band channel covariance matrix is ​​determined, and the full-band channel covariance matrix is ​​obtained by summing and averaging K M×M dimensional channel covariance matrices corresponding to K subcarriers, where K is a positive integer; the full-band channel covariance matrix is ​​singular value delimited to obtain a merging coefficient set.

[0096] It should be understood that the specific form of the first channel estimation result can be an estimation matrix for the first beam measurement data. The full-band channel covariance matrix represents the channel feature space information. Each effective subcarrier can correspond to a channel covariance matrix obtained based on the first channel estimation result. The full-band channel covariance matrix can also be called the full-bandwidth channel covariance matrix, which is obtained by summing and averaging K M×M dimensional channel covariance matrices corresponding to K subcarriers.

[0097] As a possible implementation, when the receiving end has multi-stream transmission capability, the receiving end jointly calculates a combination coefficient set of multiple digital domain transmission channels based on the M first beam measurement data based on the system total capacity maximization criterion.

[0098] Specifically, a similar serial interference cancellation method is adopted to sequentially calculate the combining coefficient sets of each digital channel according to the M first beam measurement data to coordinate the interference between streams and maximize the system capacity.

[0099] As a possible implementation method, when the receiving end has a multi-beam measurement capability, the receiving end calculates the merging coefficient set corresponding to the multi-beam using a joint iterative method of the receiving end and the transmitting end.

[0100] S503: The receiving end sends the combining coefficient set to the transmitting end.

[0101] S504: The transmitting end determines a combined beam according to the combining coefficient set and the M measurement beams.

[0102] Specifically, the M measurement beams are weightedly combined by using M beam weighting coefficients in the combining coefficient set, and a combined beam is obtained after processing based on hardware limitation constraints.

[0103] In the above technical solution, the transmitter obtains the beam weighting coefficients corresponding to multiple measurement beams and combines them with the original measurement beam to synthesize a new combined beam. The combined beam can better match the actual air interface channel direction and better utilize the channel gain, thereby achieving precise beam alignment and improving coverage performance. For example, in a scenario where the receiver is not fully aligned with the main lobe of the measurement beam, the combined beam obtained by combining the coefficient set can better utilize the channel gain to achieve precise beam alignment. For another example, in the presence of NLOS scenarios in the millimeter wave channel, when a single beam cannot cover all channel angles, the combined beam obtained by combining the coefficient set comprehensively considers the channel gain of all beams, achieves precise beam alignment, and improves coverage performance.

[0104] Figure 6 is an interactive diagram of another beam alignment training method provided by an embodiment of the present application. It should be understood that the description of the execution body shown in Figure 6 can refer to Figure 5 and will not be repeated here.

[0105] S601: A transmitting end sends N second beam measurement data to a receiving end, where the N second beam measurement data correspond to N measurement beams.

[0106] It should be understood that the N second beam measurement data can be specifically carried in a PPDU data packet in the packet-by-packet beam alignment training method shown in FIG3(a), or the N second beam measurement data can also be carried as N training fields in a PPDU data packet in the intra-packet beam alignment training method shown in FIG3(b). Different measurement beams correspond to different fixed directions.

[0107] Specifically, the transmitting end traverses and uses N measurement beams to send N second beam measurement data to the receiving end.

[0108] S602: The receiving end determines N second signal-to-noise ratios according to the N second beam measurement data.

[0109] S603: The receiving end sends N second signal-to-noise ratios to the transmitting end.

[0110] S604: The transmitting end determines M measurement beams according to the N second signal-to-noise ratios.

[0111] Specifically, the transmitting end determines measurement beams corresponding to second signal-to-noise ratios greater than the first threshold among the N second signal-to-noise ratios as M measurement beams.

[0112] It should be understood that S601 to S604 are the process of determining M measurement beams when the M measurement beams are a subset of the N measurement beams and 1≤M<N. The M measurement beams can be understood as the better ones among the N measurement beams.

[0113] S605: The transmitting end sends M first beam measurement data to the receiving end, where the M first beam measurement data correspond to M measurement beams, and the m-th measurement beam corresponds to the m-th first beam measurement data.

[0114] It should be understood that the detailed process of S605 can be referred to S501 and will not be described in detail here.

[0115] S606. The receiving end determines a merging coefficient set based on the M first beam measurement data, where the merging coefficient set includes M beam weighting coefficients, the mth beam weighting coefficient corresponds to the mth first beam measurement data, and the mth beam weighting coefficient represents the weight coefficient of the mth measurement beam in the M measurement beams, 1≤m≤M, and m and M are positive integers.

[0116] As a possible implementation method, M first channel estimation results are determined based on M first beam measurement data; based on the M first channel estimation results, a full-band channel covariance matrix is ​​determined, and singular value demarcation is performed on the full-band channel covariance matrix to obtain a merging coefficient set.

[0117] Specifically, for a scenario where the transmitter has only a single digital domain transmission channel, the transmitter sends M first beam measurement data through the digital domain transmission channel, and the mth first channel estimation result corresponding to the mth measurement beam is recorded as H m (k), where 1≤m≤M, m is a positive integer, k represents the number of K valid subcarriers in the bandwidth, 1≤k≤K, k and K are positive integers. The M first channel estimation results are recorded as H(k)=[H1(k)...H M (k)].

[0118] Specifically, for a scenario where the transmitter has only a single digital domain transmission channel, the full-band channel covariance matrix can be obtained using formula (1), and its dimension is M×M.

[0119] Perform singular value decomposition on the full-band channel covariance matrix, R = USV T . Among them, the first column vector v of the V matrix is ​​the merged coefficient set, and its dimension is M×1.

[0120] As a possible implementation manner, M first signal-to-noise ratios are determined according to the M first channel estimation results.

[0121] As a possible implementation manner, a combined estimation result is obtained according to the combined coefficient set and the M first channel estimation results; and an estimated combined signal-to-noise ratio is determined according to the combined estimation result.

[0122] Specifically, the M first channel estimation results are multiplied by the merging coefficient set to obtain a merging estimation result, which can be specifically recorded as

[0123] For a scenario where the transmitting end has multiple digital domain transmitting channels, each digital domain transmitting channel can send multiple first beam measurement data. Accordingly, each digital domain transmitting channel corresponds to multiple first channel estimation results.

[0124] For scenarios where the transmitter has multiple digital domain transmission channels, the receiver can calculate a full-band channel covariance matrix for each digital domain transmission channel, denoted as R i Accordingly, the singular value decomposition R is performed on each full-band channel covariance matrix i =U i S i V i T . Among them, each V i The first column vector v of the matrix i A set of combining coefficients corresponding to each digital domain transmission channel.

[0125] S607: The receiving end sends the combining coefficient set, M first signal-to-noise ratios, and the estimated combined signal-to-noise ratio to the transmitting end.

[0126] Specifically, the receiving end may compress the combining coefficient set, the M first signal-to-noise ratios, and the estimated combined signal-to-noise ratio, and feed back the compression result to the sending end.

[0127] S608: The transmitting end obtains a combined beam according to the combining coefficient set and the M measurement beams.

[0128] Specifically, the M measurement beams are weightedly combined by using M beam weighting coefficients in the combining coefficient set, and a combined beam is obtained after processing based on hardware limitation constraints.

[0129] S609: The transmitting end determines whether to use a combined beam or a target beam for data transmission based on the M first signal-to-noise ratios and the estimated combined signal-to-noise ratio, and the first signal-to-noise ratio corresponding to the target beam is the largest among the M first signal-to-noise ratios.

[0130] As a possible implementation manner, if the estimated combined signal-to-noise ratio is greater than the largest first signal-to-noise ratio among the M first signal-to-noise ratios, it is determined to use the combined beam for data transmission.

[0131] As a possible implementation manner, if the estimated combined signal-to-noise ratio is less than or equal to the largest first signal-to-noise ratio among the M first signal-to-noise ratios, it is determined to use the target beam for data transmission.

[0132] The difference between the beam alignment training method shown in FIG6 and the beam alignment training method shown in FIG5 is that the M measurement beams used in S605 of sending M first beam measurement data in FIG6 are obtained by screening through S601 to S604.

[0133] In the above technical solution, the measurement beam obtained after one round of beam alignment training is used for the next round of beam alignment training, which can reduce the beam overhead and the computational complexity of the receiving end, and can limit the signal-to-noise ratio fluctuation of the measurement beam during the next round of intra-packet beam alignment training, thereby making the calculated merging coefficient set more accurate.

[0134] The beam alignment training methods for different types of first beam measurement data will be described in detail below with reference to FIG. 7 and FIG. 8 .

[0135] Figure 7 is an interactive diagram of another beam alignment training method provided by an embodiment of the present application. Figure 7 (a) shows a packet-by-packet beam alignment training method in which M first beam measurement data are carried in M ​​data packets (e.g., M PPDU data packets).

[0136] In step S1, the transmitter uses M measurement beams to continuously send M data packets to the receiver, each of which is a complete PPDU data packet. The M data packets can be SSW data packets or short-SSW data packets.

[0137] S2: The receiving end determines a set of combining coefficients based on the M data packets. It should be understood that specific possible implementations have been described in detail in FIG5 and FIG6 and will not be repeated here.

[0138] S3: The receiving end feeds back the combining coefficient set to the transmitting end. It should be understood that a detailed explanation of the combining coefficient set can be found in S502 and S606.

[0139] Optionally, the receiving end further feeds back the M first signal-to-noise ratios and the estimated combined signal-to-noise ratio to the transmitting end. The combining coefficient set, the M first signal-to-noise ratios, and the estimated combined signal-to-noise ratio may be compressed and fed back to the transmitting end together.

[0140] S4: The transmitter determines a combined beam based on the combining coefficient set and the M measurement beams.

[0141] S5: The transmitting end uses the target beam or the combined beam for data transmission. It should be understood that the specific process of determining whether to use the target beam or the combined beam can be referred to S609 and will not be described in detail here.

[0142] Figure 7(b) illustrates an intra-packet beam alignment training method in which M pieces of first beam measurement data are carried in M ​​training fields within a data packet (e.g., a PPDU). The difference between Figure 7(b) and Figure 7(a) is that in S1, M measurement beams are used to transmit M training fields within a single data packet. These M training fields are contained within the same data packet. The remaining steps are similar and are not detailed here.

[0143] In this way, if the M measurement beams are the measurement beams with smaller signal-to-noise ratio differences after the first round of screening in Figure 6 and undergo intra-packet beam alignment training, the signal-to-noise ratio fluctuations of the measurement beams during the next round of intra-packet beam alignment training can be limited, the resulting merging coefficient set is more accurate, and bandwidth resources and signaling overhead can be reduced.

[0144] Currently, WLAN high- and low-frequency protocols are independent. The next generation of WLAN technology will develop towards the integration of high and low frequency. Current mainstream Wi-Fi protocols (such as 802.11ac / ax / be) are primarily used in sub-7GHz low-frequency scenarios, and the next generation of mainstream Wi-Fi protocols is considering integrating millimeter wave high-frequency.

[0145] Figure 8 is an interactive diagram of another beam alignment training method provided by an embodiment of the present application. The beam alignment method shown in Figure 8 is compatible with low-frequency scenarios of current mainstream Wi-Fi protocol applications and high- and low-frequency fusion scenarios of next-generation mainstream Wi-Fi protocol applications.

[0146] As shown in Figure 8, in the time domain, the transmitter sends a null data packet announcement (NDPA) to the receiver. The NDPA is used to notify the receiver of the existence of a subsequent NDP and instruct the receiver to perform channel measurement and provide feedback.

[0147] S1: The transmitter uses M measurement beams to send M training fields in one NDP.

[0148] Among them, M training (TRN) fields are added to the current NDP data structure. NDP is a PPDU that does not carry a data field and is used for channel measurement.

[0149] For high-frequency signals, channel estimation can be achieved through S2.

[0150] S2: Determine a combination coefficient set based on the M training fields. It should be understood that specific possible implementations have been described in detail in FIG5 and FIG6 and will not be repeated here.

[0151] For low-frequency signals, channel estimation can be achieved through S3.

[0152] S3, perform singular value decomposition on each effective subcarrier channel to obtain the digital domain weight and signal-to-noise ratio.

[0153] In this way, when singular value decomposition is applied to the full-band channel covariance matrix in the high-frequency signal S2 to obtain a combined coefficient set, not only is the complexity low, but the channel measurement compression feedback method of the current mainstream Wi-Fi protocol can also be used, which has good compatibility.

[0154] For high frequency signals, the results can be fed back through S4.

[0155] S4: The receiving end feeds back the combining coefficient set to the transmitting end. It should be understood that a detailed explanation of the combining coefficient set can be found in S502 and S606.

[0156] Optionally, the receiving end further feeds back the M first signal-to-noise ratios and the estimated combined signal-to-noise ratio to the transmitting end. The combining coefficient set, the M first signal-to-noise ratios, and the estimated combined signal-to-noise ratio may be compressed and fed back to the transmitting end together.

[0157] For low-frequency signals, the results can be fed back through the following steps.

[0158] Optionally, the receiving end performs compressed feedback on the digital domain weight and signal-to-noise ratio of S3.

[0159] For high frequency signals, subsequent data transmission can be achieved through S5 and S6. The detailed processes of S5 and S6 can be referred to S508 and S509 in FIG5 , which will not be described in detail here.

[0160] For low-frequency signals, subsequent data transmission can be achieved based on the digital domain weight and signal-to-noise ratio fed back by the transmitter.

[0161] The beam alignment training method provided by the embodiment of the present application is described in detail above with reference to Figures 5 to 8. It is understood that in order to implement the above functions, it includes hardware structures and / or software modules corresponding to executing each function.

[0162] Those skilled in the art should be aware that, in combination with the units and algorithm steps of each example described in the embodiments disclosed herein, the present application can be implemented in the form of hardware or a combination of hardware and computer software. Whether a function is performed in the form of hardware or computer software driving hardware depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for specific applications, but such implementation should not be considered to be beyond the scope of this application.

[0163] The beam alignment training device provided in the embodiments of the present application is described in detail below with reference to Figures 9 to 11. It should be understood that the description of the device embodiment corresponds to the description of the method embodiment. Therefore, for matters not described in detail, reference can be made to the method embodiment above. For the sake of brevity, some contents are not repeated here.

[0164] Figure 9 is a schematic diagram of a beam alignment training device 900 provided in an embodiment of the present application. The device 900 may include a processing unit 920, which is used to perform data processing. The device 900 may also include a transceiver unit 910, which may implement corresponding communication functions. The transceiver unit 910 may also be referred to as a communication interface or a communication unit or an interface unit. It should be understood that for the operations such as sending and receiving involved in this application, if there is no special explanation, or if it does not conflict with its actual function or internal logic in the relevant description, it can be more generally understood as operations such as output and input, rather than sending and receiving operations directly performed by the radio frequency circuit and antenna.

[0165] Optionally, the device 900 may further include a storage unit, which may be used to store instructions and / or data. The processing unit 920 may read the instructions and / or data in the storage unit so that the device implements the aforementioned method embodiment.

[0166] The device 900 can be used to execute the actions performed by the sending end in the above method embodiment. In this case, the device 900 can be a communication device or a component that can be configured on a communication device. The transceiver unit 910 is used to execute the transceiver-related operations on the communication device side in the above method embodiment, and the processing unit 920 is used to execute the processing-related operations of the sending end in the above method embodiment.

[0167] As a design, apparatus 900 is configured to execute the actions performed by the transmitter during beam alignment training in the method embodiments shown in Figures 5 through 8 above. The execution entity may be a chip, chip system, or processor that supports the transmitter in implementing the corresponding method, or a logic module or software that implements all or part of the transmitter's functions.

[0168] Specifically, the transceiver unit 910 is configured to receive M first beam measurement data, where the M first beam measurement data correspond to M measurement beams.

[0169] The processing unit 920 is used to determine a merging coefficient set based on the M first beam measurement data, where the merging coefficient set includes M beam weighting coefficients, the mth beam weighting coefficient corresponds to the mth first beam measurement data, and the mth beam weighting coefficient represents the weight of the mth measurement beam in the M measurement beams, 1≤m≤M, and m and M are positive integers.

[0170] The transceiver unit 910 is configured to send a combining coefficient set.

[0171] For details not described in detail, please refer to the above method embodiment.

[0172] As a design, the beam alignment training device 900 is used to execute the actions performed by the receiving end during beam alignment training in the method embodiments shown in Figures 5 to 8 above. The execution entity can be a chip, chip system, or processor that supports the receiving end in implementing the corresponding method, or a logic module or software that can implement all or part of the receiving end's functions.

[0173] Specifically, the transceiver unit 910 is configured to receive M first beam measurement data, where the M first beam measurement data correspond to M measurement beams. The processing unit 920 is configured to determine a combining coefficient set based on the M first beam measurement data, where the combining coefficient set includes M beam weighting coefficients, where the mth beam weighting coefficient corresponds to the mth first beam measurement data, and the mth beam weighting coefficient represents the weight of the mth measurement beam among the M measurement beams, where 1≤m≤M, and m and M are positive integers. The transceiver unit 910 is configured to transmit the combining coefficient set.

[0174] For details not described in detail, please refer to the above method embodiment.

[0175] It should be understood that the specific process of each unit executing the above corresponding steps has been described in detail in the above method embodiment, and for the sake of brevity, it will not be repeated here.

[0176] The processing unit 920 in the above embodiment can be implemented by at least one processor or processor-related circuit. The transceiver unit 910 can be implemented by a transceiver or transceiver-related circuit. The storage unit can be implemented by at least one memory.

[0177] FIG10 is a schematic structural diagram of a beam alignment training device 1000 provided in an embodiment of the present application.

[0178] As shown in Figure 10, an embodiment of the present application further provides a beam alignment training device 1000. The device 1000 includes a processor 1010, which is coupled to a memory 1020. The memory 1020 is configured to store computer programs, instructions, and / or data. The processor 1010 is configured to execute the computer programs, instructions, and / or data stored in the memory 1020, thereby executing the method in the above method embodiment.

[0179] Optionally, the device 1000 includes one or more processors 1010.

[0180] Optionally, as shown in FIG10 , the apparatus 1000 may further include a memory 1020 .

[0181] Optionally, the memory 1020 included in the device 1000 may be one or more.

[0182] Optionally, the memory 1020 may be integrated with the processor 1010 or provided separately.

[0183] Optionally, as shown in Figure 10, the apparatus 1000 may further include a transceiver 1030, which is configured to receive and / or transmit signals. For example, the processor 1010 is configured to control the transceiver 1030 to receive and / or transmit signals.

[0184] As a solution, the device 1000 is used to implement the operations performed by the transmitting end or the receiving end in the above method embodiment.

[0185] For example, the processor 1010 is used to implement the processing-related operations performed by the transmitter or receiver in the above method embodiment, and the transceiver 1030 is used to implement the sending and receiving-related operations performed by the transmitter or receiver in the above method embodiment.

[0186] FIG11 is a schematic diagram of a chip system 1100 provided in an embodiment of the present application, as shown in FIG11 . The chip system 1100 (or it may also be referred to as a processing system) includes a logic circuit 1110 and an input / output interface 1120. The logic circuit is used to couple with the input interface and transmit data parameters through the input / output interface to execute the method in the above method embodiment. The device in which the chip system 1100 is installed can implement the method and function of the embodiment of the present application. For example, the logic circuit 1110 can be a processing circuit in the chip system 1100, which controls the device in which the chip system 1100 is installed, and can also be coupled to a storage unit to call instructions in the storage unit so that the device can implement the method and function of the embodiment of the present application. The input / output interface 1120 can be an input / output circuit in the chip system 1100, which outputs information processed by the chip system 1100, or inputs data or signaling information to be processed into the chip system 1100 for processing.

[0187] As a solution, the chip system 1100 is used to implement the operations performed by the beam alignment training device (such as the transmitting end or the receiving end) in the above method embodiments.

[0188] For example, the logic circuit 1110 is used to implement the processing-related operations performed by the transmitter or receiver in the above method embodiments, and the input / output interface 1120 is used to implement the sending and receiving-related operations performed by the transmitter or receiver in the above method embodiments.

[0189] An embodiment of the present application further provides a communication system, which includes one or more transmitting ends and one or more receiving ends that implement the beam alignment training method in the above method embodiment.

[0190] An embodiment of the present application also provides a computer-readable storage medium storing computer instructions for implementing the method executed by a beam alignment training device (such as a transmitting end or a receiving end) in the above method embodiment.

[0191] For example, when the computer program is executed by a computer, the computer can implement the method performed by the beam alignment training device (such as a transmitting end or a receiving end) in the above method embodiment.

[0192] An embodiment of the present application also provides a computer program product comprising instructions, which, when executed by a computer, enables the computer to implement the method performed by the beam alignment training device (such as a transmitter or a receiver) in the above method embodiment.

[0193] The explanation of the relevant contents and beneficial effects of any of the above-mentioned devices can be referred to the corresponding method embodiments provided above, which will not be repeated here.

[0194] It should be understood that the processor mentioned in the embodiments of the present application may be a central processing unit (CPU), or may be other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), field programmable gate arrays (FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. The general-purpose processor may be a microprocessor or any conventional processor, etc.

[0195] It should also be understood that the memory mentioned in the embodiments of the present application may be a volatile memory and / or a non-volatile memory. Among them, the non-volatile memory may be a read-only memory (ROM), a programmable read-only memory (PROM), an erasable programmable read-only memory (EPROM), an electrically erasable programmable read-only memory (EEPROM), or a flash memory. The volatile memory may be a random access memory (RAM). For example, RAM can be used as an external cache. By way of example and not limitation, RAM may include the following forms: static random access memory (SRAM), dynamic random access memory (DRAM), synchronous dynamic random access memory (SDRAM), double data rate synchronous dynamic random access memory (DDR SDRAM), enhanced synchronous dynamic random access memory (ESDRAM), synchronous link dynamic random access memory (SLDRAM), and direct rambus RAM (DR RAM).

[0196] It should be noted that when the processor is a general-purpose processor, DSP, ASIC, FPGA or other programmable logic device, discrete gate or transistor logic device, discrete hardware component, the memory (storage module) can be integrated into the processor.

[0197] It should also be noted that the memory described herein is intended to include, but is not limited to, these and any other suitable types of memory.

[0198] Those skilled in the art will appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of this application.

[0199] Those skilled in the art will clearly understand that, for the convenience and brevity of description, the specific working processes of the systems, devices and units described above can refer to the corresponding processes in the aforementioned method embodiments and will not be repeated here.

[0200] In the several embodiments provided in this application, it should be understood that the disclosed systems, devices and methods can be implemented in other ways. For example, the device embodiments described above are merely schematic. For example, the division of the units is merely a logical function division. In actual implementation, there may be other division methods, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of devices or units, which can be electrical, mechanical or other forms.

[0201] The units described as separate components may or may not be physically separate, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed across multiple network units. Some or all of these units may be selected to achieve the purpose of this embodiment according to actual needs.

[0202] In addition, each functional unit in each embodiment of the present application may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit.

[0203] If the functions are implemented in the form of software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present application, or the part that contributes to the prior art, or the part of the technical solution, can be embodied in the form of a software product. The computer software product is stored in a storage medium and includes several instructions for enabling a computer device (which can be a personal computer, server, or network device, etc.) to execute all or part of the steps of the method described in each embodiment of the present application. The aforementioned storage medium includes various media that can store program codes, such as a USB flash drive, a mobile hard disk, a read-only memory ROM, a random access memory RAM, a magnetic disk, or an optical disk.

[0204] The above description is merely a specific embodiment of the present application, but the scope of protection of the present application is not limited thereto. Any changes or substitutions that can be easily conceived by a person skilled in the art within the technical scope disclosed in this application should be included in the scope of protection of this application. Therefore, the scope of protection of this application should be based on the scope of protection of the claims.

Claims

1. A beam alignment training method, characterized in that: include: The transmitting end sends M first beam measurement data, where the M first beam measurement data correspond to M measurement beams; The transmitting end receives a combining coefficient set, where the combining coefficient set is determined by the receiving end according to the M first beam measurement data, the combining coefficient set includes M beam weighting coefficients, the mth beam weighting coefficient corresponds to the mth first beam measurement data, the mth beam weighting coefficient represents the weight of the mth measurement beam in the M measurement beams, 1≤m≤M, and m and M are positive integers; The transmitting end determines a combined beam according to the combining coefficient set and the M measurement beams.

2. The method according to claim 1, characterized in that Before the transmitting end sends the M first beam measurement data, the method further includes: The transmitting end sends N second beam measurement data, where the N second beam measurement data correspond to N measurement beams; The transmitting end receives N second signal-to-noise ratios, and the nth second signal-to-noise ratio corresponds to the nth measurement beam; The measurement beams corresponding to the second signal-to-noise ratios greater than a preset threshold among the N second signal-to-noise ratios are determined as the M measurement beams, where 1≤n≤N, n and N are positive integers, and M<N.

3. The method according to claim 1 or 2, characterized in that: The method further comprises: The transmitting end receives M first signal-to-noise ratios and an estimated combined signal-to-noise ratio, where the M first signal-to-noise ratios are obtained by the receiving end according to the M first beam measurement data, and the estimated combined signal-to-noise ratio is determined by the receiving end according to the M first beam measurement data and the combining coefficient set; The transmitting end determines to use the combined beam for data transmission according to the M first signal-to-noise ratios and the estimated combined signal-to-noise ratio, or determines to use a measurement beam corresponding to a largest first signal-to-noise ratio among the M first signal-to-noise ratios for data transmission.

4. The method according to any one of claims 1 to 3, characterized in that: The M first beam measurement data are carried in a non-data packet NDP, or the M first beam measurement data are carried in one or M protocol data unit PPDU data packets.

5. A beam alignment training method, characterized in that: include: The receiving end receives M first beam measurement data, where the M first beam measurement data correspond to M measurement beams; The receiving end determines a merging coefficient set according to the M first beam measurement data, where the merging coefficient set includes M beam weighting coefficients, the mth beam weighting coefficient corresponds to the mth first beam measurement data, and the mth beam weighting coefficient represents a weight of the mth measurement beam in the M measurement beams, 1≤m≤M, and m and M are positive integers; The receiving end sends the combining coefficient set.

6. The method according to claim 5, characterized in that The receiving end determines the combination coefficient set according to the M first beam measurement data, including: The receiving end determines M first channel estimation results according to the M first beam measurement data; The receiving end determines a full-band channel covariance matrix corresponding to the M first channel estimation results, where the full-band channel covariance matrix is ​​obtained by summing and averaging K M×M-dimensional channel covariance matrices corresponding to K subcarriers, where K is a positive integer; The receiving end performs singular value decomposition on the full-band channel covariance matrix to obtain the combined coefficient set.

7. The method according to claim 6, characterized in that Before receiving the M first beam measurement data, the method further includes: The receiving end receives N second beam measurement data, where the N second beam measurement data correspond to N measurement beams, 1≤n≤N, and n and N are positive integers; The receiving end determines N second signal-to-noise ratios according to the N second beam measurement data, and the nth second signal-to-noise ratio corresponds to the nth measurement beam; The receiving end sends the N second signal-to-noise ratios.

8. The method according to claim 6 or 7, characterized in that: The method further comprises: The receiving end determines a combined estimation result according to the combined coefficient set and the M first channel estimation results; The receiving end determines an estimated combined signal-to-noise ratio according to the combined estimation result; The receiving end determines M first signal-to-noise ratios according to the M first channel estimation results; The receiving end sends the M first signal-to-noise ratios and the estimated combined signal-to-noise ratio.

9. The method according to any one of claims 5 to 8, characterized in that: The M first beam measurement data are carried in a non-data packet NDP, or the M first beam measurement data are carried in one or M protocol data unit PPDU data packets.

10. A beam alignment training device, characterized in that: Including transceiver unit and processing unit: The transceiver unit is used to send M first beam measurement data, where the M first beam measurement data correspond to M measurement beams; The transceiver unit is used to receive a combining coefficient set, where the combining coefficient set is determined by the receiving end according to the M first beam measurement data, the combining coefficient set includes M beam weighting coefficients, the mth beam weighting coefficient corresponds to the mth first beam measurement data, the mth beam weighting coefficient represents the weight of the mth measurement beam in the M measurement beams, 1≤m≤M, and m and M are positive integers; The processing unit is configured to determine a combined beam according to the combining coefficient set and the M measurement beams.

11. The device according to claim 10, characterized in that Before the transceiver unit is used to send the M first beam measurement data, the transceiver unit is further used to: Sending N second beam measurement data, where the N second beam measurement data correspond to N measurement beams; receiving N second signal-to-noise ratios, wherein the nth second signal-to-noise ratio corresponds to the nth measurement beam; The processing unit is also used for: The measurement beams corresponding to the second signal-to-noise ratios greater than a preset threshold among the N second signal-to-noise ratios are determined as the M measurement beams, where 1≤n≤N, n and N are positive integers, and M<N.

12. The device according to claim 10 or 11, characterized in that The transceiver unit is also used for: Receiving M first signal-to-noise ratios and an estimated combined signal-to-noise ratio, where the M first signal-to-noise ratios are obtained by the receiving end according to the M first beam measurement data, and the estimated combined signal-to-noise ratio is determined by the receiving end according to the M first beam measurement data and the combining coefficient set; The processing unit is further used to: determine, based on the M first signal-to-noise ratios and the estimated combined signal-to-noise ratio, to use the combined beam for data transmission, or determine to use a measurement beam corresponding to a largest first signal-to-noise ratio among the M first signal-to-noise ratios for data transmission.

13. The device according to any one of claims 10 to 12, characterized in that The M first beam measurement data are carried in a non-data packet NDP, or the M first beam measurement data are carried in one or M protocol data unit PPDU data packets.

14. A beam alignment training device, characterized in that: Including transceiver unit and processing unit: The transceiver unit is used to receive M first beam measurement data, where the M first beam measurement data correspond to M measurement beams; The processing unit is used to determine a merging coefficient set according to the M first beam measurement data, where the merging coefficient set includes M beam weighting coefficients, the mth beam weighting coefficient corresponds to the mth first beam measurement data, and the mth beam weighting coefficient represents the weight of the mth measurement beam in the M measurement beams, 1≤m≤M, and m and M are positive integers; The transceiver unit is used to send the combining coefficient set.

15. The device according to claim 14, characterized in that The processing unit is specifically used for: Determine M first channel estimation results according to the M first beam measurement data; Determine a full-band channel covariance matrix corresponding to the M first channel estimation results, where the full-band channel covariance matrix is ​​obtained by summing and averaging K channel covariance matrices of M×M dimensions corresponding to the K subcarriers, where K is a positive integer; Performing singular value decomposition on the full-band channel covariance matrix to obtain the combined coefficient set.

16. The device according to claim 15, characterized in that Before the transceiver unit is used to receive the M first beam measurement data, the transceiver unit is further used to: Receiving N second beam measurement data, where the N second beam measurement data correspond to N measurement beams, 1≤n≤N, and n and N are positive integers; The processing unit is further used to determine N second signal-to-noise ratios according to the N second beam measurement data, and the nth second signal-to-noise ratio corresponds to the nth measurement beam; The transceiver unit is further configured to send the N second signal-to-noise ratios.

17. The device according to claim 15 or 16, characterized in that The processing unit is also used for: Determining a combined estimation result according to the combined coefficient set and the M first channel estimation results; Determining an estimated combined signal-to-noise ratio according to the combined estimation result; Determining M first signal-to-noise ratios according to the M first channel estimation results; The transceiver unit is further configured to send the M first signal-to-noise ratios and the estimated combined signal-to-noise ratio.

18. The device according to any one of claims 14 to 17, characterized in that The M first beam measurement data are carried in a non-data packet NDP, or the M first beam measurement data are carried in one or M protocol data unit PPDU data packets.

19. A beam alignment training device, characterized in that: The device comprises a processor, the processor is coupled to a memory, the memory is used to store a computer program or instruction, and the processor is used to execute the computer program or instruction in the memory, so that the device performs the method according to any one of claims 1 to 9.

20. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores a computer program or instruction, and when the computer program or instruction is executed on a computer, the computer is caused to execute the method according to any one of claims 1 to 9.

21. A chip, characterized in that: The chip is coupled to a memory and is used to read and execute program instructions stored in the memory to implement the method according to any one of claims 1 to 9.

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