Beam alignment training method and device

Abstract

The invention provides a beam alignment training method and device, and the method comprises the steps that a transmitting end transmits M pieces of first beam measurement data, and the M pieces of first beam measurement data correspond to M measurement beams; the sending end receives a merging coefficient set, the merging coefficient set is determined by the receiving end according to the M first beam measurement data, the merging coefficient set comprises 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, m is greater than or equal to 1 and less than or equal to M, and m is greater than or equal to 1 and less than or equal to M; m and M are positive integers. And the sending end determines a combined beam according to the combination coefficient set and the M measurement beams. Thus, the combined beam can be better matched with the actual air interface channel direction, the channel gain can be better utilized, then beam fine alignment can be achieved, and the coverage performance is improved.

Description

Technical Field

[0001] The present application relates to the field of communications, and more specifically, to a beam alignment training method and device. Background Art

[0002] Currently, the Institute of Electrical and Electronics Engineers (IEEE) 802.11ad / ay is one of the standards for wireless local area network (WLAN) communications applied to the millimeter wave frequency band. Among them, hybrid analog-digital beamforming (HAD-BF) is a technology used to overcome the signal attenuation in the millimeter wave frequency band. HAD-BF is a process of selecting the best beam through the beam alignment training process.

[0003] However, the beam sent by the transmitter (initiator) of the HAD-BF technology is a codebook beam with fixed directions pre-existing at the transmitter. Since the division of the angle space by the codebook beam is predetermined, when the main lobe of the codebook beam sent by the receiver (responder) and the transmitter during the simulated beam alignment training cannot be fully aligned, the receiver will not be able to obtain the maximum beam gain. Similarly, when there is a reflection path for the millimeter wave signal, a single beam cannot cover all channel angles. At this time, the receiver cannot obtain all channel gains.

[0004] Therefore, how to improve the performance of beam alignment training is an urgent problem to be solved. Summary of the invention

[0005] 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 beam precision alignment and improve coverage performance.

[0006] In a first aspect, a beam alignment training method is provided, the method comprising: a transmitting end sends M first beam measurement data, the M first beam measurement data correspond to M measurement beams. The transmitting end receives a merging coefficient set, the merging coefficient set is determined by the receiving end according to the M first beam measurement data, the merging 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, m and M are positive integers. The transmitting end determines the merging beam according to the merging coefficient set and the M measurement beams.

[0007] 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 beam precision alignment and improving coverage performance. For example, in a scenario where the receiving end 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 beam precision alignment. For another example, in the presence of NLOS scenarios in millimeter wave channels, when a single beam cannot cover all channel angles, the combined beam obtained by combining the coefficient set comprehensively considers the channel gains of all beams, achieves beam precision alignment, and improves coverage performance.

[0008] In combination with the first aspect, in certain implementations of the first aspect, before the transmitting end sends M first beam measurement data, the method further includes: the transmitting end sends N second beam measurement data, and 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 M measurement beams, 1≤n≤N, n and N are positive integers, and M<N.

[0009] In the above technical scheme, 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 amount of calculation at 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.

[0010] In combination with the first aspect, in certain implementations of the first aspect, the method further includes: the transmitting end receives M first signal-to-noise ratios and an estimated combined signal-to-noise ratio, 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 combined coefficient set. The transmitting end determines to use the combined beam for data transmission based on the M first signal-to-noise ratios and the estimated combined signal-to-noise ratio, 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.

[0011] In the above technical solution, the transmitting end comprehensively considers the M first signal-to-noise ratios and the estimated combined signal-to-noise ratio, and selects a more reasonable beam for subsequent data transmission, thereby achieving precise beam alignment and improving coverage performance.

[0012] 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.

[0013] 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.

[0014] 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 mainline Wi-Fi protocol can be used, which is compatible with the high and low frequency fusion scenario.

[0015] In a second aspect, a beam alignment training method is provided, including: a receiving end receives M first beam measurement data, the M first beam measurement data corresponding to M measurement beams. The receiving end determines a merging coefficient set based on the M first beam measurement data, the merging 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, m and M are positive integers. The receiving end sends the merging coefficient set.

[0016] It should be understood that the beneficial effects corresponding to the scheme of the second aspect are similar to those of the first aspect. For detailed description, reference may be made to the first aspect and no further details will be given here.

[0017] In combination with the second aspect, in certain implementations of the second aspect, the receiving end determines the merging coefficient set based on the M first beam measurement data, including: the receiving end determines the M first channel estimation results based on the M first beam measurement data. The receiving end determines the full-band channel covariance matrix corresponding to the M first channel estimation results, 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 receiving end performs singular value decomposition on the full-band channel covariance matrix to obtain the merging coefficient set.

[0018] In the above technical solution, for the millimeter wave high frequency beam alignment training, the combined coefficient set is obtained by using singular value decomposition of the full-band channel covariance matrix. It not only has low complexity, but also can use the channel measurement compression feedback method of the current mainline Wi-Fi protocol, and has good compatibility.

[0019] In combination with the second aspect, in some implementations of the second aspect, before receiving the M first beam measurement data, the method further includes: the receiving end receives N second beam measurement data, the N second beam measurement data correspond to N measurement beams, 1≤n≤N, n and N are positive integers. The receiving end determines N second signal-to-noise ratios based on the N second beam measurement data, the nth second signal-to-noise ratio corresponds to the nth measurement beam. The receiving end sends the N second signal-to-noise ratios.

[0020] In combination with the second aspect, in some implementations of the second aspect, the method further includes: the receiving end determines a combined estimation result based on the combined coefficient set and the M first channel estimation results. The receiving end determines an estimated combined signal-to-noise ratio based on the combined estimation result. The receiving end determines M first signal-to-noise ratios based on 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.

[0021] 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.

[0022] In a third aspect, a beam alignment training device is provided, comprising a transceiver unit and a processing unit: the transceiver unit is used to send M first beam measurement data, the M first beam measurement data correspond to M measurement beams. The transceiver unit is used to receive a merging coefficient set, the merging coefficient set is determined by the receiving end based on the M first beam measurement data, the merging 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, m and M are positive integers. The processing unit is used to determine the merging beam based on the merging coefficient set and the M measurement beams.

[0023] 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.

[0024] In combination with the third aspect, in certain implementations of the third aspect, before the transceiver unit is used to send M first beam measurement data, the transceiver unit is also used to: send N second beam measurement data, the N second beam measurement data correspond to N measurement beams; receive N second signal-to-noise ratios, the nth second signal-to-noise ratio corresponds to the nth measurement beam. The processing unit is also used 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, 1≤n≤N, n and N are positive integers, and M<N.

[0025] In combination with the third aspect, in certain implementations of the third aspect, the transceiver unit is further used to: receive M first signal-to-noise ratios and an estimated combined signal-to-noise ratio, 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 combined coefficient set. The processing unit is also used to: determine to use a combined beam for data transmission based on the M first signal-to-noise ratios and the estimated combined signal-to-noise ratio, or determine to use a measurement beam corresponding to the largest first signal-to-noise ratio among the M first signal-to-noise ratios for data transmission.

[0026] 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.

[0027] In a fourth aspect, a beam alignment training device is provided, comprising a transceiver unit and a processing unit: the transceiver unit is used to receive M first beam measurement data, the M first beam measurement data corresponding to the M measurement beams. The processing unit is used to determine a merging coefficient set based on the M first beam measurement data, the merging coefficient set including M beam weighting coefficients, the mth beam weighting coefficient corresponding to the mth first beam measurement data, the mth beam weighting coefficient representing the weight of the mth measurement beam in the M measurement beams, 1≤m≤M, m and M are positive integers. The transceiver unit is used to send the merging coefficient set.

[0028] It should be understood that the beneficial effects corresponding to the scheme of the fourth aspect are similar to those of the second aspect and will not be elaborated here.

[0029] In combination with the fourth aspect, in certain implementations of the fourth aspect, the processing unit is specifically used to: determine M first channel estimation results based on 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; perform singular value decomposition on the full-band channel covariance matrix to obtain a combined coefficient set.

[0030] In combination with the fourth aspect, in certain implementations of the fourth aspect, before the transceiver unit is used to receive the M first beam measurement data, the transceiver unit is also used to: receive N second beam measurement data, the N second beam measurement data correspond to N measurement beams, 1≤n≤N, n and N are positive integers. The processing unit is also used to determine N second signal-to-noise ratios based on the N second beam measurement data, the nth second signal-to-noise ratio corresponds to the nth measurement beam. The transceiver unit is also used to send the N second signal-to-noise ratios.

[0031] In combination with the fourth aspect, in some implementations of the fourth aspect, the processing unit is further configured to: determine a combined estimation result based on the combined 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 send the M first signal-to-noise ratios and the estimated combined signal-to-noise ratio.

[0032] 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.

[0033] 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 implementations of the first or second aspects above.

[0034] In one implementation, the device is a transmitter or a receiver in beam alignment training.

[0035] In another implementation, the device is a chip, a chip system, or a circuit in a transmitter or a receiver in beam alignment training.

[0036] 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 aspect to the second aspect. In the process of executing these methods, the process of sending the above-mentioned information and obtaining / receiving the above-mentioned information in the above-mentioned method can be understood as the process of outputting the above-mentioned information by the processor, and the process of receiving the above-mentioned information input by the processor. When outputting the above-mentioned information, the processor outputs the above-mentioned information to the interface and transmits it through the interface. After being output by the processor, the above-mentioned information may also need to be processed in other ways before it reaches the interface. Similarly, when the processor receives the above-mentioned information input, the interface obtains / receives the above-mentioned information and inputs it into the processor. Furthermore, after the interface receives the above-mentioned information, the above-mentioned information may need to be processed in other ways before it is input into the processor.

[0037] 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 operations such as output and reception, input, etc., and can also be understood as transmission, sending, and receiving operations performed by radio frequency circuits and antennas. This application does not limit this.

[0038] In the implementation process, the processor may be a processor specifically used to execute these methods, or a processor that executes computer programs or instructions in a memory to execute these 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 may be separately arranged on different chips. The embodiment of the present application does not limit the type of memory and the arrangement of the memory and the processor.

[0039] In a seventh aspect, a computer-readable storage medium is provided, which stores a program code for execution by a device, wherein the program code includes a method for executing any one of the implementations of the first to second aspects above.

[0040] In an eighth aspect, a computer program product comprising instructions is provided. When the computer program product is run on a computer, the computer is enabled to execute the method provided in any one of the implementations of the first to second aspects above.

[0041] In a ninth aspect, a chip is provided, the chip comprising 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 modes of the first to second aspects above.

[0042] 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 aspect to the second aspect above. BRIEF DESCRIPTION OF THE DRAWINGS

[0043] Figure 1 It is a schematic diagram of a wireless communication application scenario provided by the embodiment itself;

[0044] Figure 2 It is a schematic diagram of an analog-to-digital hybrid beamforming structure provided in an embodiment of the present application;

[0045] Figure 3 is a schematic diagram of a beam alignment training method provided in an embodiment of the present application;

[0046] Figure 4 is a schematic diagram of a beam alignment training scenario provided in an embodiment of the present application;

[0047] Figure 5 It is a flow chart of a beam alignment training method provided in an embodiment of the present application;

[0048] Figure 6 is an interactive schematic diagram of another beam alignment training method provided in an embodiment of the present application;

[0049] Figure 7 is an interactive schematic diagram of another beam alignment training method provided in an embodiment of the present application;

[0050] Figure 8 is an interactive schematic diagram of yet another beam alignment training method provided in an embodiment of the present application;

[0051] Fig. 9is a schematic diagram of a beam alignment training device 900 provided in an embodiment of the present application;

[0052] Fig.10 is a schematic structural diagram of a beam alignment training device 1000 provided in an embodiment of the present application;

[0053] Fig.11 It is a schematic diagram of a chip system 1100 provided in an embodiment of the present application. DETAILED DESCRIPTION

[0054] The technical solution in this application will be described below in conjunction with the accompanying drawings.

[0055] In order to facilitate understanding of the embodiments of the present application, the following points are explained:

[0056] 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 to each other, and the technical features in different embodiments can be combined to form new embodiments according to their internal logical relationships.

[0057] Second, in this application, "at least one" means one or more, and "more than one" 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 associated objects before and after 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. Where a, b and c can be single or multiple, respectively.

[0058] Third, in the present application, "first", "second" and various numerical numbers (e.g., #1, #2, etc.) indicate distinctions made for the convenience of description and are not used to limit the scope of the embodiments of the present application. For example, to distinguish different beam measurement data, etc., rather than to describe a specific order or sequence. It should be understood that the objects described in this way can be interchanged where appropriate so as to be able to describe solutions other than the embodiments of the present application.

[0059] 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 only examples, and this application does not limit them, and should not constitute any limitation on the technical solution of this application;

[0060] Fourth, in this application, descriptions such as "when...", "under the circumstances of...", and "if" all refer to the corresponding processing being carried out under certain objective circumstances, and do not limit the time, nor do they require that there must be a judgment action when implementing, nor do they mean that there are other limitations. In addition, it does not mean that the judgment action after these conditional conjunctions is the only condition for achieving the result, and other additional conditions may also be included to achieve the result.

[0061] 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 comprising a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to these processes, methods, products or apparatuses.

[0062] Sixth, in this application, "used for indication" may include being used for direct indication and being used for indirect indication. When describing that a certain indication information is used for indicating A, it may include that the indication information directly indicates A or indirectly indicates A, but it does not mean that the indication information must carry A.

[0063] The indication method involved in the embodiments of the present application should be understood to include various methods that can enable the party to be indicated to know the information to be indicated. The information to be indicated can be sent as a whole or divided into multiple sub-information and sent separately, and the sending period and / or sending time of these sub-information can be the same or different. The present application does not limit the specific sending method.

[0064] The "indication information" in the embodiments of the present application may be an explicit indication, i.e., directly indicated by signaling, or obtained by combining other rules or other parameters or by deduction according to the parameters indicated by the signaling. It may also be an implicit indication, i.e., obtained by combining other rules or other parameters or by deduction according to a rule or relationship. The present application does not make any specific limitation on this.

[0065] Seventh, in this application, "storage" may refer to storage in one or more memories. The one or more memories may be separately set or integrated in an encoder or decoder, a processor, or a communication device. The one or more memories may also be partially separately set and partially integrated in a decoder, a processor, or a communication device. The type of memory may be any form of storage medium, which is not limited in this application.

[0066] The technical solution provided in the embodiment of the present application can be applied to wireless local area network (WLAN) scenarios, for example, supporting IEEE802.11 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 waves (millimeterwave, 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). The implementation of Sub-7GHz mainly relies on 802.11ax, 802.11be and the next generation standards, while the implementation of 60GHz mainly relies on 802.11ad, 802.11ay and the next generation standards. Among them, 802.11ad can also be called directional multi-gigabit (DMG) standard, and 802.11ay can also be called enhanced directional multi-gigabit (EDMG) standard.

[0067] Although the embodiments of the present application are mainly described by deploying a WLAN network, especially a network using the IEEE 802.11 system standard, it is easy for those skilled in the art to understand that the various aspects involved in the embodiments of the present application can be extended to other networks using various standards or protocols, such as a high performance radio local area network (HIPERLAN), a wireless wide area network (WWAN), a wireless personal area network (WPAN), or other networks known now or developed later. Therefore, regardless of the coverage range and wireless access protocol used, the various aspects provided in the embodiments of the present application can be applied to any suitable wireless network.

[0068] The technical solutions of the embodiments of the present application can also be applied to various communication systems, such as: WLAN communication system, Wi-Fi system, fifth generation (5G) system or new radio (NR), future sixth generation (6G) system, Internet of Things (IoT) network or vehicle to x (V2X), etc.

[0069] The above-mentioned communication system applicable to the present application is only an example for illustration, and the communication system applicable to the present application is not limited to this. A unified description is given here and no further elaboration is given below.

[0070] Figure 1 This is a schematic diagram of a wireless communication application scenario provided by the embodiment. Figure 1 The millimeter wave communication scenario shown can support communication between a transmitter and at least one receiver. For example, the transmitter communicates with receiver #1, receiver #2 and 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, the present application only takes 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 the present application. This is explained uniformly here and will not be repeated later.

[0071] The transmitting end in the present application may be a device for communicating with the receiving end, and the network device may be a base station (base transceiver station, BTS) in a 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 may be a relay station, an access point, a vehicle-mounted device, a wearable device, a network device in a 5G network, 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 thereto.

[0072] Among them, the sender can be an access point (AP) for the receiver (such as a mobile phone) to enter the wired (or wireless) network. It is mainly deployed in homes, buildings and parks, with a typical coverage radius of tens of meters to hundreds of meters. Of course, it can also be deployed outdoors. The sender is equivalent to a bridge connecting the wired network and the wireless network. Its main function is to connect various wireless network clients together and then connect the wireless network to the Ethernet. Specifically, the sender can be a terminal device (such as a mobile phone) or a network device (such as a router) with a Wi-Fi chip. The sender can be a device that supports the 802.11be standard. The access point can also be a device that supports multiple WLAN standards of the 802.11 family, such as 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. 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.

[0073] 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 communication network (PLMN), etc., and the embodiments of this application are not limited to this.

[0074] Among them, the receiving end can be a wireless communication chip, a wireless sensor or a wireless communication terminal, etc., and can also be called a user. For example, the receiving end can be a mobile phone supporting Wi-Fi communication function, a tablet supporting Wi-Fi communication function, a set-top box supporting Wi-Fi communication function, a smart TV supporting Wi-Fi communication function, a smart wearable device supporting Wi-Fi communication function, a vehicle-mounted communication device supporting Wi-Fi communication function, and a computer supporting Wi-Fi communication function, etc. Optionally, the site can support the 802.11be standard. The site can also support WLAN standards of the 802.11 family such as 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.

[0075] For example, the transmitting end and the receiving end can be devices used in the Internet of Vehicles, IoT nodes and sensors in the IoT, smart cameras and smart remote controls in smart homes, smart water and electricity meters, and sensors in smart cities.

[0076] As described above, in order to overcome the signal attenuation in the millimeter wave band, the millimeter wave band generally adopts analog beamforming with analog-to-digital hybrid beamforming. Figure 2 Schematic diagram of a hybrid analog-digital beamforming structure provided in an embodiment of the present application. Figure 2 As shown, digital beamforming is a baseband signal. The frequency conversion and digital-to-analog conversion between the baseband signal and the RF signal are realized through the intermediate frequency unit and the digital-to-analog converter respectively. Each digital domain channel corresponds 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 name of the beam involved.

[0077] Figure 3 It is a schematic diagram of the beam alignment training method provided in an embodiment of the present application.

[0078] IEEE 802.11.ad / ay standards are used for communications in the millimeter wave band. Figure 3 There are two beam alignment training methods. Figure 3 (a) shows the packet by packet beam alignment training method. Figure 3 (b) shows the in-packet beam alignment training method.

[0079] like Figure 3As shown in (a), in the time domain, in the first step, the transmitter can continuously send multiple data packets, each of which is a complete protocol data unit (PPDU), including the preamble and data. Each data packet can be sent using a different beam, and the direction of the different beams is determined according to the pre-stored beam direction angle. Figure 3 As shown, data packet #1 is sent to the receiving end through beam #1, data packet #2 is sent to the receiving end through beam #2, and so on, data packet #N is sent to the receiving end through beam #N. Among them, the type of each data packet can be a sector sweep packet (SSW packet) or a short sector sweep packet (SSW packet). In the second step, the receiving end measures the signal-to-noise ratio (SNR) of each data packet. In the third step, the receiving end feeds back the measured SNR and the corresponding beam identifier to the transmitting end. In the fourth step, the transmitting end selects the best transmitting beam based on the feedback from the receiving end.

[0080] In order to reduce the overhead corresponding to the beam, a training (TRN) field is added to the PPDU. Figure 3 As shown in (b), the general process of the intra-packet beam alignment training method is similar to the packet-by-packet beam alignment training method. The difference is that the first step in the intra-packet beam alignment training method only sends one PPDU data packet, and multiple training fields are added to the PPDU, and each training field is sent using a different beam.

[0081] The above two beam alignment training methods both select the best beam based on the measured signal-to-noise ratio and the corresponding beam identifier fed back by the receiver. Since the measured beams are all codebook beams in the predetermined direction of the transmitter, and the number of predefined codebook beams is limited, in some scenarios, the channel direction cannot be fully matched, the receiver cannot obtain the maximum beam gain, and the transmitter cannot obtain the optimal beam based on the measurement results.

[0082] One scenario is that the main lobe of the codebook beam at the transmitter is not completely aligned with the receiver, for example, Figure 1 The position relationship between the transmitter and receiver #1 is shown. In this scenario, the codebook beam predefined by the transmitter divides the angle space, the transmitter position is fixed, and the receiver position is random. The main lobe of the codebook beam at the transmitter and the receiver are not completely aligned, and the receiver cannot obtain the maximum beam gain. At this time, the transmitter cannot obtain the best beam based on the feedback result.

[0083] Another scenario is that the millimeter wave channel has a non-line-of-sight (NLOS) scenario. Figure 4 Schematic diagram of a beam alignment training scenario provided in an embodiment of the present application. Figure 4 As shown in FIG. 1 , beam #1 reaches the receiving end after being reflected by an obstacle. A single beam cannot cover all channel angles, resulting in the receiving end being unable to obtain all channel gains, and the receiving end cannot obtain the best beam based on the feedback results.

[0084] In order to solve the above problems, the present application embodiment proposes a beam alignment training method and device. Figures 5 to 11 Detailed description.

[0085] Figure 5 It is a flow diagram 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 is to illustrate the corresponding method by taking the transmitting end and the receiving end as the execution subject of the interaction diagram as an example, but the present application does not limit the execution subject of the interaction diagram. For example, Figure 5 The sending end in the method may also be a chip, a chip system or a processor that supports the sending end to implement the corresponding method, or may be a logic module or software that can implement all or part of the functions of the sending end. Figure 5 The receiving end in the method may also be a chip, a chip system or a processor that supports the receiving end to implement the corresponding method, or may be a logic module or software that can implement all or part of the functions of the receiving end.

[0086] 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.

[0087] It should be understood that the M measurement beams are a subset of the N measurement beams, N=M, or 1≤M<N. The N measurement beams are all measurement beams corresponding to a digital domain transmission channel of the transmitting end.

[0088] 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. In the case of 1≤M<N, the specific implementation method will be combined with Figure 6 Detailed description.

[0089] 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.

[0090] For example, when M first beam measurement data are carried in M ​​PPDU data packets, the transmitter uses M measurement beams to send M PPDU data packets at equal time intervals. This can also be understood as a packet-by-packet beam alignment training method. The detailed process will be combined with Figure 7 (a) Detailed description.

[0091] 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, and the transmitter uses M measurement beams to send M training fields in one data packet. Specifically, it can also be understood as a beam alignment training method in a packet, or combined with a low-frequency NDP measurement method. The detailed process will be combined with Figure 7 (b) and Figure 8 Detailed description.

[0092] 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, the mth beam weighting coefficient represents the weight of the mth measurement beam among the M measurement beams, 1≤m≤M, and m and M are positive integers.

[0093] As a possible implementation method, based on M first beam measurement data, M first channel estimation results are determined; 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; singular value delimitation is performed on the full-band channel covariance matrix to obtain a merging coefficient set.

[0094] 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.

[0095] As a possible implementation manner, 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.

[0096] 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.

[0097] As a possible implementation method, when the receiving end has a multi-beam measurement capability, the receiving end calculates a combination coefficient set corresponding to the multi-beam by a joint iteration method of the receiving end and the transmitting end.

[0098] S503: The receiving end sends a combining coefficient set to the transmitting end.

[0099] S504: The transmitting end determines a combined beam according to the combining coefficient set and the M measurement beams.

[0100] Specifically, the M measurement beams are weightedly combined by using M beam weighting coefficients in a combining coefficient set, and a combined beam is obtained after processing based on hardware limitation constraints.

[0101] 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 beam precision alignment and improving coverage performance. For example, in a scenario where the receiving end 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 beam precision alignment. For another example, in the presence of NLOS scenarios in millimeter wave channels, when a single beam cannot cover all channel angles, the combined beam obtained by combining the coefficient set comprehensively considers the channel gains of all beams, achieves beam precision alignment, and improves coverage performance.

[0102] Figure 6 is an interactive schematic diagram of another beam alignment training method provided in an embodiment of the present application. It should be understood that Figure 6 For instructions on the execution entity shown, please refer to Figure 5 , I will not go into details here.

[0103] 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.

[0104] It should be understood that the N second beam measurement data may be carried in Figure 3 The PPDU data packet in the packet-by-packet beam alignment training method shown in (a) of FIG. 1 , or the N second beam measurement data may also be carried on Figure 3 The intra-packet beam alignment training method shown in (b) is directed to N training fields in a PPDU data packet. Different measurement beams correspond to different fixed directions.

[0105] Specifically, the transmitting end traverses and uses N measurement beams to send N second beam measurement data to the receiving end.

[0106] S602: The receiving end determines N second signal-to-noise ratios according to N second beam measurement data.

[0107] S603: The receiving end sends N second signal-to-noise ratios to the transmitting end.

[0108] S604: The transmitting end determines M measurement beams according to the N second signal-to-noise ratios.

[0109] 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.

[0110] It should be understood that S601 to S604 are the process of determining M measurement beams when the M measurement beams are subsets 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.

[0111] S605: The transmitting end sends M first beam measurement data to the receiving end, wherein 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.

[0112] It should be understood that the detailed process of S605 can be referred to S501 and will not be described in detail here.

[0113] 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, the mth beam weighting coefficient represents the weight coefficient of the mth measurement beam in the M measurement beams, 1≤m≤M, m and M are positive integers.

[0114] As a possible implementation method, M first channel estimation results are determined based on M first beam measurement data; a full-band channel covariance matrix is ​​determined based on the M first channel estimation results, and singular value demarcation is performed on the full-band channel covariance matrix to obtain a merging coefficient set.

[0115] 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)].

[0116] Specifically, for a scenario where the transmitter has only a single digital domain transmission channel, the full-band channel covariance matrix can be obtained through formula (1), and its dimension is M×M.

[0117]

[0118] 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.

[0119] As a possible implementation, according to the M first channel estimation results, M first signal-to-noise ratios are determined:

[0120] 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.

[0121] Specifically, the M first channel estimation results are multiplied by the combination coefficient set to obtain a combined estimation result, which can be specifically recorded as

[0122] 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.

[0123] 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 . Each V i The first column vector v of the matrix i A corresponding set of combining coefficients is sent for each digital domain channel.

[0124] S607: The receiving end sends a combining coefficient set, M first signal-to-noise ratios, and an estimated combined signal-to-noise ratio to the transmitting end.

[0125] 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.

[0126] S608: The transmitting end obtains a combined beam according to the combining coefficient set and the M measurement beams.

[0127] Specifically, the M measurement beams are weightedly combined by using M beam weighting coefficients in a combining coefficient set, and a combined beam is obtained after processing based on hardware limitation constraints.

[0128] S609: The transmitting end determines to use a combined beam or a target beam for data transmission according to 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.

[0129] 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.

[0130] 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 adopt the target beam for data transmission.

[0131] Figure 6 The beam alignment training method shown and Figure 5 The difference between the beam alignment training methods shown is that Figure 6 The M measurement beams used in sending the M first beam measurement data in S605 are obtained by screening through S601 to S604.

[0132] In the above technical scheme, 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 amount of calculation at 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.

[0133] The following will be combined Figure 7 and Figure 8 A beam alignment training method for different types of first beam measurement data is described in detail.

[0134] Figure 7 This is an interactive schematic diagram of another beam alignment training method provided in an embodiment of the present application. Figure 7 (a) is a packet-by-packet beam alignment training method in which M first beam measurement data are carried in M ​​data packets (eg, M PPDU data packets).

[0135] S1, the transmitting end uses M measurement beams to continuously send M data packets to the receiving end, each data packet is a complete PPDU data packet, wherein the type of the M data packets can be SSW data packets or short-SSW data packets.

[0136] S2, the receiving end determines a combination coefficient set according to the M data packets. It should be understood that specific possible implementation methods have been Figure 5 and Figure 6 The detailed description is given in the document and will not be repeated here.

[0137] S3, the receiving end feeds back the combining coefficient set to the transmitting end. It should be understood that the detailed explanation of the combining coefficient set can refer to S502 and S606.

[0138] 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 can be compressed and fed back to the transmitting end together.

[0139] S4: The transmitting end determines a combined beam according to the combining coefficient set and the M measurement beams.

[0140] 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, which will not be described in detail.

[0141] Figure 7 (b) is an intra-packet beam alignment training method in which M first beam measurement data are carried in a data packet (for example, a PPDU data packet) and correspond to M training fields. Figure 7 (b) and Figure 7 The difference from (a) is that in S1, M measurement beams are used to send M training fields in one data packet. The M training fields are in the same data packet. The remaining steps are similar and will not be repeated here.

[0142] Thus, if M measurement beams are passed through Figure 6 The measurement beams with smaller signal-to-noise ratio differences after the first round of screening can be trained through intra-packet beam alignment, which can limit the signal-to-noise ratio fluctuation of the measurement beam during the next round of intra-packet beam alignment training. The resulting merging coefficient set is more accurate and can reduce bandwidth resources and signaling overhead.

[0143] The current WLAN high-frequency and low-frequency protocols are independent, and the next generation of WLAN technology will develop in the direction of high-frequency and low-frequency integration. The current mainstream Wi-Fi protocols (for example, 802.11ac / ax / be) are mainly used in Sub7GHz low-frequency scenarios, and the next generation of mainstream Wi-Fi protocols will consider integrating millimeter-wave high-frequency.

[0144] Figure 8 It is an interactive schematic diagram of yet another beam alignment training method provided in an embodiment of the present application. Figure 8 The beam alignment method shown is compatible with the low-frequency scenario of the current mainstream Wi-Fi protocol application, and is also compatible with the high- and low-frequency fusion scenario of the next-generation mainstream Wi-Fi protocol application.

[0145] like Figure 8As shown, 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 feedback.

[0146] S1: The transmitter uses M measurement beams to send M training fields in one NDP.

[0147] Among them, M training (TRN) fields are added to the data structure of the current NDP. NDP is a PPDU that does not carry a data field and is used for channel measurement.

[0148] For high-frequency signals, channel estimation can be achieved through S2.

[0149] S2, determining a combination coefficient set according to the M training fields. It should be understood that a specific possible implementation method has been Figure 5 and Figure 6 The detailed description is given in the document and will not be repeated here.

[0150] For low-frequency signals, channel estimation can be achieved through S3.

[0151] S3, performing singular value decomposition on each effective subcarrier channel to obtain digital domain weight and signal-to-noise ratio.

[0152] In this way, for the high-frequency signal S2, singular value decomposition is used for the full-band channel covariance matrix to obtain a combined coefficient set. This not only has low complexity, but also can follow the channel measurement compression feedback method of the current mainline Wi-Fi protocol, and has good compatibility.

[0153] For high frequency signals, the results can be fed back through S4.

[0154] S4, the receiving end feeds back the combining coefficient set to the transmitting end. It should be understood that the detailed explanation of the combining coefficient set can refer to S502 and S606.

[0155] 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 can be compressed and fed back to the transmitting end together.

[0156] For low-frequency signals, the results can be fed back through the following steps.

[0157] Optionally, the receiving end performs compressed feedback on the digital domain weight and signal-to-noise ratio of S3.

[0158] For high frequency signals, subsequent data transmission can be achieved through S5 and S6. The detailed process of S5 and S6 can be referred to Figure 5 S508 and S509 in the description will not be described in detail here.

[0159] 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.

[0160] Above, combined Figures 5 to 8 The beam alignment training method provided by the embodiment of the present application is described in detail. It can be understood that in order to realize the above functions, it includes hardware structures and / or software modules corresponding to executing various functions.

[0161] 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 executed 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.

[0162] The following, combined Figures 9 to 11 The beam alignment training device provided in the embodiment of the present application is described in detail. It should be understood that the description of the device embodiment corresponds to the description of the method embodiment, so the contents not described in detail can be referred to the method embodiment above, and some contents will not be repeated for the sake of brevity.

[0163] Fig. 9 It 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, and 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 the antenna.

[0164] Optionally, the device 900 may further include a storage unit, which may be used to store instructions and / or data, and the processing unit 920 may read the instructions and / or data in the storage unit so that the device implements the aforementioned method embodiment.

[0165] 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 in 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.

[0166] As a design, the device 900 is used to perform the above Figures 5 to 8 The actions performed by the transmitter in the beam alignment training in the method embodiment shown. The execution subject may 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.

[0167] Specifically, the transceiver unit 910 is used to receive M first beam measurement data, where the M first beam measurement data correspond to M measurement beams.

[0168] The processing unit 920 is used to determine a merging coefficient set based on 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, the mth beam weighting coefficient represents the weight of the mth measurement beam among the M measurement beams, 1≤m≤M, and m and M are positive integers.

[0169] The transceiver unit 910 is used to send a combining coefficient set.

[0170] For matters not described in detail, reference may be made to the above method embodiments.

[0171] As a design, the beam alignment training device 900 is used to perform the above Figures 5 to 8 The actions performed by the receiving end in the beam alignment training in the method embodiment shown. The execution subject may be a chip, chip system or processor that supports the receiving end to implement the corresponding method, or a logic module or software that can implement all or part of the functions of the receiving end.

[0172] Specifically, the transceiver unit 910 is used to receive M first beam measurement data, where the M first beam measurement data correspond to M measurement beams. 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, 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 in the M measurement beams, where 1≤m≤M, and m and M are positive integers. The transceiver unit 910 is used to send the merging coefficient set.

[0173] For matters not described in detail, reference may be made to the above method embodiments.

[0174] 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.

[0175] The processing unit 920 in the above embodiment may be implemented by at least one processor or processor-related circuits. The transceiver unit 910 may be implemented by a transceiver or a transceiver-related circuit. The storage unit may be implemented by at least one memory.

[0176] Fig.10 It is a schematic structural diagram of a beam alignment training device 1000 provided in an embodiment of the present application.

[0177] like Fig.10 As shown, the embodiment of the present application also provides a beam alignment training device 1000. The device 1000 includes a processor 1010, the processor 1010 is coupled to a memory 1020, the memory 1020 is used to store computer programs or instructions and / or data, and the processor 1010 is used to execute the computer programs or instructions and / or data stored in the memory 1020, so that the method in the above method embodiment is executed.

[0178] Optionally, the device 1000 includes one or more processors 1010.

[0179] Optional, such as Fig.10 As shown, the device 1000 may further include a memory 1020 .

[0180] Optionally, the memory 1020 included in the device 1000 may be one or more.

[0181] Optionally, the memory 1020 may be integrated with the processor 1010 or provided separately.

[0182] Optional, such as Fig.10 As shown, the device 1000 may further include a transceiver 1030, and the transceiver 1030 is used for receiving and / or sending signals. For example, the processor 1010 is used to control the transceiver 1030 to receive and / or send signals.

[0183] As a solution, the device 1000 is used to implement the operations performed by the sending end or the receiving end in the above method embodiment.

[0184] For example, the processor 1010 is used to implement the processing-related operations performed by the transmitter or the 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 the receiver in the above method embodiment.

[0185] Fig.11 is a schematic diagram of a chip system 1100 provided in an embodiment of the present application, such as Fig.11 As shown. 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 (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 installed with the chip system 1100 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 realizes the control of the device installed with the chip system 1100, and can also be coupled to a storage unit to call the 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 the information processed by the chip system 1100, or inputs the data or signaling information to be processed into the chip system 1100 for processing.

[0186] 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 embodiment.

[0187] 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.

[0188] An embodiment of the present application also 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.

[0189] An embodiment of the present application also provides a computer-readable storage medium on which are stored 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.

[0190] 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.

[0191] 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 a beam alignment training device (such as a transmitting end or a receiving end) in the above method embodiment.

[0192] 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.

[0193] It should be understood that the processor mentioned in the embodiments of the present application may be a central processing unit (CPU), or 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. A general-purpose processor may be a microprocessor or the processor may also be any conventional processor, etc.

[0194] 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).

[0195] 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.

[0196] 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.

[0197] Those of ordinary skill 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 to be beyond the scope of this application.

[0198] Those skilled in the art can 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.

[0199] In the several embodiments provided in the present 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 only schematic. For example, the division of the units is only a logical function division. There may be other division methods in actual implementation, 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.

[0200] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0201] 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.

[0202] 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 can be essentially or partly embodied in the form of a software product that contributes to the prior art. The computer software product is stored in a storage medium and includes several instructions for a computer device (which can be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the methods described in the various embodiments of the present application. The aforementioned storage media include: various media that can store program codes, such as USB flash drives, mobile hard disks, read-only memories ROM, random access memories RAM, magnetic disks or optical disks.

[0203] The above is only a specific implementation of the present application, but the protection scope of the present application is not limited thereto. Any person skilled in the art who is familiar with the present technical field can easily think of changes or substitutions within the technical scope disclosed in the present application, which should be included in the protection scope of the present application. Therefore, the protection scope of the present application should be based on the protection scope 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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