Data processing method and apparatus

Abstract

The present application discloses a data processing method and apparatus. The method comprises: acquiring spatial-domain beamforming weight data corresponding to a first stream transmitted on a first resource block group; rearranging the spatial-domain beamforming weight data and performing first processing in at least one direction dimension of an antenna array plane, to obtain angle-domain beamforming weight data corresponding to the first stream; dividing the angle-domain beamforming weight data into one or more subsets, and compressing each subset on the basis of a target compression bit width corresponding to each subset; sending beamforming weight data after each subset is compressed, and bit width information corresponding to each subset. The present solution performs beam transformation on spatial-domain beamforming weight data based on a single-flow granularity, and can obtain good sparsity in the angle domain. Adaptive bit width compression is performed on angle-domain beamforming weight data, so that a high compression rate can be obtained, thereby reducing forward transmission flow. The solution can also reduce or avoid forcibly discarding some directions in the angle domain, and MU demodulation performance is considered.

Description

Data processing method and device

[0001] CROSS-REFERENCE TO RELATED APPLICATIONS

[0002] This application claims priority to the Chinese patent application filed with the State Intellectual Property Office of the People's Republic of China on February 29, 2024, with application number 202410232251.6 and application name "A Data Processing Method and Device", the entire contents of which are incorporated by reference into this application. Technical Field

[0003] The present application relates to the field of communication technology, and in particular to a data processing method and device. Background Art

[0004] In a communication system using an Ethernet structure (such as a fronthaul communication system using an enhanced common public radio interface (eCPRI)), when the beamforming weights are calculated in the baseband unit (BBU), the downlink bit data and the beamforming weight data are the bottlenecks of the fronthaul traffic peak. The downlink bit data and the beamforming weight data increase with the number of antennas, especially the beamforming weight data, which increases nonlinearly with the number of antennas. The existing technology generally adopts a method of transforming the beamforming weight data from the antenna domain to the beam domain. Based on the fact that the beamforming weight data exhibits a certain sparsity in the beam domain, certain beam directions are set to zero, thereby achieving the effect of reducing the data volume of the beamforming weight data.

[0005] However, in massive multiple-input multiple-output (MIMO) scenarios, scheduling more users through spatial division multiplexing is a key way to increase capacity. The bottleneck in fronthaul traffic occurs precisely when a large number of users are being scheduled. Multi-user (MU) pairing consumes a large number of spatial degrees of freedom. Therefore, after the multi-user beamforming weight data is transformed from the antenna domain to the beam domain, the spatial sparsity is often less than ideal. Discarding too many directions in the beam domain reduces the compression accuracy of the beamforming weight data, leading to a loss in MU demodulation performance.

[0006] How to reduce fronthaul traffic while taking into account MU demodulation performance is a technical problem that needs to be solved urgently. Summary of the Invention

[0007] The present application provides a data processing method and apparatus for reducing forward transmission traffic while taking into account MU demodulation performance.

[0008] In a first aspect, a data processing method is provided. The method can be performed by a first device, which can be a device in an access network device, for example, a BBU. Unless otherwise specified, the "first device" in this application can refer to the first device itself (e.g., a BBU), a component in the first device (e.g., a processor, chip, or chip system), or a logical module or software that can implement all or part of the functions of the first device. The method includes: obtaining spatial beamforming weight data corresponding to a first stream transmitted on a first resource block group; rearranging the spatial beamforming weight data to obtain rearranged spatial beamforming weight data; performing a first processing on the rearranged spatial beamforming weight data in at least one directional dimension of an antenna array surface to convert the rearranged spatial beamforming weight data into an angular domain to obtain angular domain beamforming weight data corresponding to the first stream; dividing the angular domain beamforming weight data into one or more subsets; compressing each subset according to a target compression bit width corresponding to each subset in the one or more subsets to obtain compressed beamforming weight data for each subset; and sending the compressed beamforming weight data for each subset and bit width information corresponding to each subset, wherein the bit width information corresponding to each subset is used to determine a target compression bit width corresponding to each subset.

[0009] In the embodiment of the present application, the spatial domain beamforming weight data is rearranged and the beam transformation from the spatial domain to the angular domain is performed at the granularity of a single stream (such as the spatial domain beamforming weight data corresponding to the first stream is rearranged and the first processing is performed), so that the angular domain beamforming weight data has good sparsity, which helps to compress the weight data in the angular domain. In addition, when compressing the weight data in the angular domain, the weight data in the angular domain is adaptively compressed (that is, the angular domain beamforming weight data is divided into one or more subsets; and the subsets are compressed according to the target compression bit width corresponding to each subset). The sparsity of the weight data in the angular domain is fully utilized to obtain a high compression rate, which can effectively reduce the fronthaul traffic. At the same time, compression at the granularity of a single stream can avoid the limitations of MU pairing, thereby reducing or even avoiding the forced abandonment of certain directions in the angular domain, thereby reducing or even avoiding the loss of MU demodulation performance at the same time.

[0010] In one possible design, obtaining spatial beamforming weight data corresponding to a first stream transmitted on a first resource block group may include: obtaining spatial beamforming weight data corresponding to multiple streams transmitted on the first resource block group, wherein the dimension of the spatial beamforming weight data corresponding to the multiple streams is a spatial beamforming weight matrix of P*Q, where P is the number of antennas on the antenna array, Q is the number of streams transmitted on the first resource block group, and P and Q are positive integers; and determining a column from the spatial beamforming weight matrix, where the determined column is the spatial beamforming weight data corresponding to the first stream.

[0011] In one possible design, rearranging the spatial beamforming weight data may include: rearranging the spatial beamforming weight data according to the structure of the antenna array, wherein the rearranged spatial beamforming weight data is a spatial beamforming weight matrix having a weight dimension of the number of horizontal antennas × the number of vertical antennas.

[0012] This design method combines the structure of the antenna array to convert the single-stream spatial beamforming weight data from the spatial domain to the angular domain, so that the converted angular domain beamforming weight data can better show sparsity.

[0013] In one possible design, if the structure of the antenna array surface is a regularly arranged antenna array, the rearranged spatial beamforming weight data is first processed in at least one directional dimension of the antenna array surface, including: performing a point-wise Fourier transform processing on the rearranged spatial beamforming weight data in at least one directional dimension of the antenna array surface to obtain an angular beamforming weight matrix, and the angular beamforming weight data corresponding to the first stream includes an angular beamforming weight matrix.

[0014] This design is simple to implement and easy to implement.

[0015] In one possible design, if the structure of the antenna array surface is an irregularly arranged antenna array, the rearranged spatial beamforming weight data is first processed in at least one directional dimension of the antenna array surface, including: performing a Fourier transform process of multiple points on the rearranged spatial beamforming weight data in at least one directional dimension of the antenna array surface to obtain multiple angular beamforming weight matrices, and the angular beamforming weight data corresponding to the first stream includes multiple angular beamforming weight matrices, and each of the multiple angular beamforming weight matrices corresponds to a regularly arranged antenna array.

[0016] This design approach can convert the spatial beamforming weight data of irregularly arranged antenna arrays into the spatial beamforming weight data of multiple regularly arranged antenna arrays through multi-point Fourier transform processing, which facilitates subsequent adaptive bit width compression and improves the applicability of the solution.

[0017] In one possible design, the target compression bit width corresponding to each subset in one or more subsets may be determined based on the target compression bit width of the angular domain beamforming weight data corresponding to the first stream and the effective bit width of each subset in the one or more subsets.

[0018] In this way, it can be ensured that after each subset is compressed according to the target compression bit width corresponding to each subset, the average bit width of the compressed beamforming weight data of all subsets can be consistent with the target compression bit width of the angular domain beamforming weight data corresponding to the first stream, thereby improving the reliability of the solution.

[0019] In one possible design, a target compressed bit width of the angular domain beamforming weight data corresponding to the first stream may be calculated according to a transmission time interval (TTI) scheduling information.

[0020] In one possible design, performing a first processing on the rearranged spatial beamforming weight data in at least one directional dimension of the antenna array surface may include: performing a first processing on the rearranged spatial beamforming weight data in a first directional dimension of the antenna array surface to obtain angular beamforming weight data, wherein the first directional dimension is a dimension corresponding to the first direction; the angular beamforming weight data includes one or more angular beamforming weight matrices. Accordingly, dividing the angular beamforming weight data into one or more subsets includes: dividing the elements in the one or more angular beamforming weight matrices into at least one subset according to the rows of the matrix, wherein one subset corresponds to a row of the matrix.

[0021] This design method, by performing a one-dimensional beam transformation from the spatial domain to the angular domain on the spatial beamforming weight data, can make the beamforming weight data have good sparsity in the angular domain. In addition, by adaptively compressing the beamforming weight data according to the rows of the matrix in the angular domain, a good compression effect can be achieved, thereby reducing the fronthaul traffic.

[0022] In one possible design, the number of antennas on the antenna array surface in the first direction is greater than or equal to the number of antennas on the antenna array surface in the second direction.

[0023] In other words, the beamforming weight data in the spatial domain is transformed from the spatial domain to the angular domain in the directional dimension where the number of antennas is large, so that the beamforming weight data can obtain better sparsity in the angular domain.

[0024] In one possible design, performing a first processing on the rearranged spatial beamforming weight data in at least one directional dimension of the antenna array surface may include: performing a first processing on the rearranged spatial beamforming weight data in a first directional dimension and a second directional dimension of the antenna array surface, respectively, to obtain angular beamforming weight data, wherein the first directional dimension is a dimension corresponding to the first direction, and the second directional dimension is a dimension corresponding to the second direction. Accordingly, dividing the angular beamforming weight data into one or more subsets includes: determining peak data in the angular beamforming weight data; reconstructing the peak data according to the structure of the antenna array surface to obtain a main signal; and subtracting the main signal from the angular beamforming weight data to obtain a residual signal; wherein the peak data and the residual signal are two different subsets.

[0025] This design method, by performing a two-dimensional beam transformation from the spatial domain to the angular domain on the spatial beamforming weight data, can make the beamforming weight data have good sparsity in the angular domain. In addition, by adaptively compressing the beamforming weight data in the angular domain according to the main signal and the residual signal, a good compression effect can be achieved, thereby reducing the fronthaul traffic.

[0026] In one possible design, the position information of the main signal on the antenna array can also be sent, which helps the decompression end recover the peak data.

[0027] In one possible design, beamforming weight data corresponding to multiple resource block groups can also be obtained, where the multiple resource block groups include a first resource block group; the beamforming weight data corresponding to the multiple resource block groups are arranged according to a third direction dimension, where the third dimension is the dimension corresponding to the third direction, and the third direction is different from the first direction and the second direction; the beamforming weight data corresponding to the multiple resource block groups are subjected to a second processing on the third direction dimension to convert the beamforming weight data corresponding to the multiple resource block groups into the delay domain, thereby obtaining delay domain beamforming weight data corresponding to the multiple resource block groups; and the delay domain beamforming weight data are compressed.

[0028] In this way, the beamforming weight data can also be compressed in the third dimension, further improving the compression rate of the beamforming weight data and reducing the fronthaul traffic.

[0029] In a possible design, the first processing is any one of inverse fast Fourier transform (IFFT), inverse discrete Fourier transform (IDFT), and inverse discrete cosine transform (IDCT).

[0030] In a second aspect, a data processing method is provided. The method can be performed by a second device, which can be a device in an access network device, such as an AAU. Unless otherwise specified, the "second device" in this application can refer to the second device itself (such as an AAU), a component in the second device (such as a processor, chip, or chip system), or a logical module or software that can implement all or part of the functions of the second device. The method includes: receiving compressed beamforming weight data of each subset in one or more subsets and bit width information corresponding to each subset, wherein the bit width information corresponding to each subset is used to determine a target compressed bit width corresponding to each subset; decompressing each subset according to the bit width information corresponding to each subset to obtain angular domain beamforming weight data corresponding to a first stream transmitted on a first resource block group; performing a third processing on the angular domain beamforming weight data in at least one directional dimension of an antenna array surface to convert the angular domain beamforming weight data into a spatial domain to obtain rearranged spatial domain beamforming weight data; and restoring the rearranged spatial domain beamforming weight data to obtain spatial domain beamforming weight data corresponding to the first stream transmitted on the first resource block group.

[0031] In a possible design, the third processing is any one of fast Fourier transform (FFT), discrete Fourier transform (DFT), and discrete cosine transform (DCT).

[0032] According to a third aspect, a communication device is provided, which includes a module, a unit, or a technical means for implementing the method described in the first aspect or any possible design of the first aspect.

[0033] Exemplarily, the apparatus may include:

[0034] a processing module, configured to obtain spatial beamforming weight data corresponding to a first stream transmitted on a first resource block group; rearrange the spatial beamforming weight data to obtain rearranged spatial beamforming weight data; perform a first processing on the rearranged spatial beamforming weight data in at least one directional dimension of an antenna array plane to convert the rearranged spatial beamforming weight data into an angular domain to obtain angular domain beamforming weight data corresponding to the first stream; divide the angular domain beamforming weight data into one or more subsets; and compress each subset according to a target compression bit width corresponding to each subset in the one or more subsets to obtain compressed beamforming weight data for each subset;

[0035] The transceiver module is used to send the compressed beamforming weight data of each subset and the bit width information corresponding to each subset. The bit width information corresponding to each subset is used to determine the target compression bit width corresponding to each subset.

[0036] In a fourth aspect, a communication device is provided, which includes modules, units or technical means for implementing the method described in the second aspect or any possible design of the second aspect.

[0037] Exemplarily, the apparatus may include:

[0038] a transceiver module, configured to receive compressed beamforming weight data of each subset in one or more subsets and bit width information corresponding to each subset, wherein the bit width information corresponding to each subset is used to determine a target compressed bit width corresponding to each subset;

[0039] A processing module is configured to decompress each subset based on the bit width information corresponding to each subset to obtain angular domain beamforming weight data corresponding to the first stream transmitted on the first resource block group; perform a third processing on the angular domain beamforming weight data in at least one directional dimension of the antenna array surface to convert the angular domain beamforming weight data into the spatial domain to obtain rearranged spatial domain beamforming weight data; and restore the rearranged spatial domain beamforming weight data to obtain spatial domain beamforming weight data corresponding to the first stream transmitted on the first resource block group.

[0040] In a fifth aspect, a system is provided, comprising an apparatus as described in the third aspect or any possible design of the third aspect, and an apparatus as described in the fourth aspect or any possible design of the fourth aspect.

[0041] In a sixth aspect, a communication device is provided, comprising a processor and an interface circuit, wherein the interface circuit is electrically coupled to the processor, and the processor causes the method described in the first aspect or any possible design of the first aspect to be executed through a logic circuit or execution code instructions, or causes the method described in the second aspect or any possible design of the second aspect to be executed.

[0042] In the seventh aspect, a communication device is provided, comprising: at least one processor; and a communication interface communicatively connected to the at least one processor; the at least one processor executes instructions stored in a memory, so that the communication device executes the method described in the first aspect or any possible design of the first aspect through the communication interface, or executes the method described in the second aspect or any possible design of the second aspect.

[0043] In an eighth aspect, a computer-readable storage medium is provided, in which a computer program or instruction is stored. When the computer program or instruction is executed, the method described in the first aspect or any possible design of the first aspect is executed, or the method described in the second aspect or any possible design of the second aspect is executed.

[0044] In the ninth aspect, a computer program product is provided, comprising instructions which, when run on a computer, cause the method described in the first aspect or any possible design of the first aspect to be executed, or cause the method described in the second aspect or any possible design of the second aspect to be executed.

[0045] The specific designs and beneficial effects of the second to ninth aspects mentioned above can refer to the corresponding designs and beneficial effects in the first aspect. BRIEF DESCRIPTION OF THE DRAWINGS

[0046] FIG1 is a schematic diagram of the architecture of a communication system that can be applied in embodiments of the present application;

[0047] Figure 2 is a schematic diagram of the architecture of the access network equipment;

[0048] Figure 3 is a schematic diagram of base station fronthaul;

[0049] FIG4 is a schematic diagram of a possible eCPRI fronthaul splitting method;

[0050] FIG5 is a schematic diagram showing the ratio of downlink bit data and weight data in forward traffic;

[0051] FIG6 is a schematic diagram of a weight compression method;

[0052] FIG7 is a schematic diagram of bit compression;

[0053] FIG8 is a schematic diagram of a possible eCPRI re-splitting method;

[0054] FIG9 is a schematic diagram of the connection relationship between the AAU and the BBU;

[0055] FIG10 is a schematic diagram of an access network device provided in an embodiment of the present application;

[0056] FIG11 is a flow chart of a data processing method provided in an embodiment of the present application;

[0057] FIG12 is a schematic diagram of spatial beamforming weight data;

[0058] FIG13 is a schematic diagram of rearranged spatial beamforming weight data corresponding to a single stream;

[0059] FIG14 is a schematic diagram of a multi-point IFFT transformation method;

[0060] FIG15 is a schematic diagram of the effect of multi-point IFFT transformation;

[0061] FIG16 is a schematic diagram of angular domain beamforming weight data obtained by one-dimensional IFFT;

[0062] FIG17 is a schematic diagram of angular domain beamforming weight data obtained by two-dimensional IFFT;

[0063] FIG18 is a schematic diagram of a three-dimensional IFFT;

[0064] FIG19 is a flowchart of another data processing method provided in an embodiment of the present application;

[0065] FIG20 is a schematic structural diagram of a communication device provided in an embodiment of the present application;

[0066] FIG21 is a schematic structural diagram of another communication device provided in an embodiment of the present application;

[0067] Figure 22 is a structural diagram of another communication device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0068] To facilitate understanding of the technical solutions provided in the embodiments of the present application, some of the terms mentioned in the embodiments of the present application are explained and illustrated below.

[0069] (1) The "plurality" involved in the embodiments of the present application refers to 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 represent three situations: A exists alone, A and B exist at the same time, and B exists alone. The character " / " generally indicates that the previous and next associated objects are in an "or" relationship. In addition, it should be understood that although the terms first, second, etc. may be used to describe each object in the embodiments of the present invention, these objects should not be limited to these terms. These terms are only used to distinguish each object from each other.

[0070] The terms "including" and "having" and any variations thereof mentioned in the description of the embodiments of the present application are intended to cover non-exclusive inclusions. For example, a process, method, system, product or device that includes a series of steps or units is not limited to the listed steps or units, but may optionally include other steps or units that are not listed, or may optionally include other steps or units that are inherent to these processes, methods, products or devices. It should be noted that in the embodiments of the present application, words such as "exemplary" or "for example" are used to indicate examples, illustrations or descriptions. Any embodiment or design described as "exemplary" or "for example" in the embodiments of the present application should not be interpreted as being more preferred or more advantageous than other embodiments or design schemes. Specifically, the use of words such as "exemplary" or "for example" is intended to present related concepts in a concrete way.

[0071] (2) Beam forming (BF): is a technology that uses an antenna array to transmit or receive signals in a directional manner. Beam forming forms a directional beam by changing the amplitude and phase of the signals of each antenna in the antenna array, so that the signals in certain directions experience constructive interference, while the signals in other directions experience destructive interference, thereby improving communication performance. For example, beam forming can increase the received signal-to-noise ratio, thereby effectively combating path loss. In specific implementation, beam forming can generate a directional beam by adjusting the weighting coefficient of each array element (or antenna unit) in the antenna array, thereby achieving significant array gain.

[0072] (3) Beamforming weight data, also known as beamforming weights, weight data, beam weights, weights, etc., refers to weighting coefficients of array elements (or antenna units) in an antenna array. When the beamforming weight data is represented by a vector (or matrix), the weight data may also be referred to as a weight vector (or matrix), etc.

[0073] The technical solutions provided in the embodiments of the present application can be applied to various communication systems, such as: fifth-generation (5G) communication systems, sixth-generation (6G) communication systems or other future evolution systems, or other various wireless communication systems using radio access technologies. The technical solutions provided in the present application can also be applied to device-to-device (D2D) communication, vehicle-to-everything (V2X) communication, machine-to-machine (M2M) communication, machine type communication (MTC), and Internet of Things (IoT) communication systems or other communication systems.

[0074] For example, FIG1 is a schematic diagram of the architecture of a communication system that can be applied in an embodiment of the present application. The communication system 1000 includes a wireless access network 100 and a core network 200. Optionally, the communication system 1000 may also include the Internet 300. The wireless access network 100 includes at least one access network device, such as 110a and 110b in FIG1 , and also includes at least one terminal device, such as 120a-120j in FIG1 . 110a is a base station, 110b is a micro station, 120a, 120e, 120f, and 120j are mobile phones, 120b is a car, 120c is a gas pump, 120d is a home access point (HAP) arranged indoors or outdoors, 120g is a laptop computer, 120h is a printer, and 120i is a drone. The same terminal device or access network device can provide different functions in different application scenarios. For example, in FIG1 , there are mobile phones 120 a , 120 e , 120 f , and 120 j . Mobile phone 120 a can access base station 110 a , connect to car 120 b , communicate directly with mobile phone 120 e , and access HAP. Mobile phone 120 b can access HAP and communicate directly with mobile phone 120 a . Mobile phone 120 f can be connected as micro station 110 b , connect to laptop computer 120 g , and connect to printer 120 h . Mobile phone 120 j can control drone 120 i .

[0075] The terminal device is connected to the access network device, which is in turn connected to the core network. The core network device and the access network device can be independent and distinct physical devices, or they can integrate the functions of the core network device and the logical functions of the access network device into the same physical device, or they can integrate some of the functions of the core network device and some of the functions of the access network device into one physical device. Terminal devices and access network devices can be connected to each other via wired or wireless means. Figure 1 is only a schematic diagram, and the communication system can also include other network devices, such as wireless relay devices and wireless backhaul devices, which are not shown in Figure 1.

[0076] Among them, the terminal device can also be called a terminal, user equipment (UE), mobile station, mobile terminal, etc. The terminal device can be widely used in various scenarios, for example, device-to-device (D2D), vehicle to everything (V2X) communication, machine-type communication (MTC), Internet of Things (IOT), virtual reality, augmented reality, industrial control, autonomous driving, telemedicine, smart grid, smart furniture, smart office, smart wearable, smart transportation, smart city, etc. The terminal device can be a mobile phone, a tablet computer, a computer with wireless transceiver function, a wearable device, a vehicle, a drone, a helicopter, an airplane, a ship, a robot, a robotic arm, a smart home device, etc. The embodiments of the present application do not limit the specific technology and specific device form adopted by the terminal device.

[0077] The access network 100 may be configured as a 3GPP-related cellular system. For example, the access network 100 may be configured as a 4G mobile communication system, a 5G mobile communication system, a WiFi system, a future-oriented evolution system (e.g., a 6G mobile communication system), or a communication system that integrates at least two of the above systems. 5G may also be referred to as NR (New Radio). Alternatively, the access network 100 may be configured as ORAN or O-RAN.

[0078] The access network device can be a base station, an evolved NodeB (eNodeB), a transmission reception point (TRP), a next generation NodeB (gNB) in a fifth generation (5G) mobile communication system, a base station in a sixth generation (6G) mobile communication system, a base station in a future mobile communication system, or an access node in a wireless fidelity (WiFi) system, etc.; it can also be a module or unit that performs some of the functions of a base station, for example, a centralized unit (CU) or a distributed unit (DU). The access network device can be a macro base station (such as 110a in Figure 1), a micro base station or an indoor station (such as 110b in Figure 1), a relay node or a donor node, etc. The embodiments of the present application do not limit the specific technology and specific device form adopted by the access network device. In the embodiments of the present application, a base station is used as an example of an access network device for description.

[0079] Base stations and UEs can be fixed or mobile. They can be deployed on land, indoors or outdoors, handheld or vehicle-mounted; on water; or in the air on aircraft, balloons, and satellites. The embodiments of this application do not limit the application scenarios of base stations and UEs.

[0080] The roles of base stations and UEs can be relative. For example, the helicopter or drone 120i in Figure 1 can be configured as a mobile base station. To devices 120j accessing the wireless access network 100 via 120i, 120i is a base station. However, to base station 110a, 120i is a UE, meaning that communication between 110a and 120i occurs via a wireless air interface protocol. Of course, communication between 110a and 120i can also occur via a base station-to-base station interface protocol. In this case, 120i is also a base station relative to 110a. Therefore, base stations and UEs can be collectively referred to as communication devices. 110a and 110b in Figure 1 can be referred to as communication devices with base station functionality, while 120a-120j in Figure 1 can be referred to as communication devices with UE functionality.

[0081] Communication between base stations and UEs, between base stations, and between UEs can be carried out through authorized spectrum, unauthorized spectrum, or both; communication can be carried out through spectrum below 6 gigahertz (GHz), spectrum above 6 GHz, or spectrum below 6 GHz and spectrum above 6 GHz. The embodiments of the present application do not limit the spectrum resources used for wireless communication.

[0082] In one possible scenario, multiple RAN nodes collaborate to assist the terminal in achieving wireless access, and different RAN nodes respectively implement part of the functions of the base station. For example, the RAN node can be a centralized unit (CU), a distributed unit (DU), a CU-control plane (CP), a CU-user plane (UP), or a radio unit (RU). The CU and DU can be set separately, or they can be included in the same network element, such as a baseband unit (BBU). The RU can be included in a radio frequency device or radio frequency unit, such as a remote radio unit (RRU), an active antenna unit (AAU), or a remote radio head (RRH).

[0083] In different systems, CU (or CU-CP and CU-UP), DU or RU may also have different names, but those skilled in the art can understand their meanings. For example, in an open radio access network (O-RAN or open RAN or ORAN) system, CU may also be called O-CU (open CU), DU may also be called O-DU, CU-CP may also be called O-CU-CP, CU-UP may also be called O-CU-UP, and RU may also be called O-RU. CU (or CU-CP and CU-UP), DU and RU can implement different protocol layer functions. For the convenience of description, this application takes CU, CU-CP, CU-UP, DU and RU as examples for description. Any unit of CU (or CU-CP, CU-UP), DU and RU in this application can be implemented by a software module, a hardware module, or a combination of a software module and a hardware module.

[0084] The communication between the access network device and the terminal device may follow a certain protocol layer structure. The protocol layer may include a control plane protocol layer and a user plane protocol layer. The control plane protocol layer may include at least one of the following: a radio resource control (RRC) layer, a packet data convergence protocol (PDCP) layer, a radio link control (RLC) layer, a media access control (MAC) layer, or a physical (PHY) layer. The user plane protocol layer may include at least one of the following: a service data adaptation protocol (SDAP) layer, a PDCP layer, an RLC layer, a MAC layer, or a physical layer.

[0085] As shown in Figure 2, the access network device may include at least one CU and at least one DU. This design can be called CU and DU separation. A CU can be connected to one or more DUs. CU and DU can be divided according to the protocol layers of the wireless network: for example, the functions of the PDCP layer and the protocol layers above it (such as the RRC layer and the SDAP layer, etc.) are set in the CU, and the functions of the protocol layers below the PDCP layer (such as the RLC layer, the MAC layer and the PHY layer, etc.) are set in the DU; for another example, the functions of the protocol layers above the PDCP layer are set in the CU, and the functions of the protocol layers at and below the PDCP layer are set in the DU, without limitation. The present disclosure does not limit the names of CU and DU. For example, CU can be called the first access network network element, DU can be called the second access network network element, etc.

[0086] The above division of the processing functions of CU and DU according to the protocol layer is only an example, and they can also be divided in other ways. For example, the CU or DU can be divided into functions with more protocol layers, or the CU or DU can be divided into partial processing functions with protocol layers. For example, some functions of the RLC layer and the functions of the protocol layers above the RLC layer are set in the CU, and the remaining functions of the RLC layer and the functions of the protocol layers below the RLC layer are set in the DU. For another example, the functions of the CU or DU can be divided according to the service type or other system requirements, such as by delay, and the functions whose processing time needs to meet the smaller delay requirement are set in the DU, and the functions that do not need to meet the delay requirement are set in the CU.

[0087] The CU can be connected to the core network. Optionally, the CU can have some of the functions of the core network.

[0088] Furthermore, some functions of the DU can be set separately. As shown in Figure 2, these functions can be implemented by a radio unit (RU). The RU can have a radio frequency function. The present disclosure does not limit the name of the RU. For example, the RU can be called a third access network element, etc. The DU and the RU can be split or separated at the PHY layer. For example, the DU can implement high-level functions in the PHY layer, and the RU can implement low-level functions in the PHY layer or implement the low-level functions and radio frequency functions. The high-level functions in the PHY layer include functions that are closer to the MAC layer, and the low-level functions in the PHY layer include functions that are closer to the radio frequency. The splitting method between the DU and the RU can be various possible methods and is not limited. There is an interface between the DU and the RU. For example, depending on the splitting method, the interface between the DU and the RU can be a common public radio interface (CPRI) interface, an enhanced common public radio interface (eCPRI) interface, or a fronthaul interface in the ORAN.

[0089] A 5G wireless base station consists of two parts: the active antenna unit (AAU) and the baseband unit (BBU). The AAU and BBU correspond to the RU and DU of the ORAN, respectively. The AAU includes the low-specification baseband unit (BBL), while the BBU includes the high-specification baseband unit (BBH) and the control module.

[0090] Figure 3 shows a schematic diagram of base station fronthaul. The AAU and BBU are connected to optical fiber via optical modules. The portion between the AAU and BBU is called fronthaul. As the 5G AAU evolves towards massive multiple-input multiple-output (Massive MIMO), the baseband processing portion has evolved from CPRI splitting to eCPRI splitting to reduce fronthaul traffic demand. However, the development of optical modules has not kept pace with the growth of fronthaul traffic under wireless Massive MIMO, making them a bottleneck limiting wireless fronthaul.

[0091] Figure 4 illustrates a possible eCPRI fronthaul splitting scheme. 5G eCPRI fronthaul splitting consists of uplink transmission of equalized data and downlink transmission of downlink bit data and weight data before constellation modulation. With the evolution of 5G to 5.5G and 6G, bandwidth has increased from 100MHz to 200MHz and 400MHz, and the number of antennas has increased from 64T to 128T and even 256T, leading to a nonlinear growth in fronthaul traffic. Therefore, downlink bit data and weight data are bottlenecks for peak fronthaul traffic, with the proportion of weight data increasing as the number of antennas increases. Figure 5 illustrates the ratio of downlink bit data to weight data in fronthaul traffic. The increase in fronthaul traffic directly leads to an increase in optical module performance, so weight data compression is key to reducing the cost of fronthaul optical modules. It should be understood that Figure 4 is only an example of a possible fronthaul splitting scheme. In actual applications, other uplink and downlink fronthaul splitting schemes are possible. As long as the fronthaul splitting involves the transmission of downlink weight data, the peak fronthaul traffic bottleneck will exist.

[0092] To alleviate the bottleneck of fronthaul traffic peaks, weight data can be compressed. Figure 6 shows a schematic diagram of the weight compression method. The BBU uses sounding reference signal (SRS) measurements and downlink weight calculations to obtain multi-user (MU) / single-user (SU) weights. The BBU then reduces the dimensionality of the weights and transmits them to the AAU via the eCPRI interface. The AAU then performs precoding on the received weights after upscaling.

[0093] In one implementation, a transform domain solution can be used to reduce fronthaul traffic. For example, transform domain methods such as the inverse fast Fourier transform (IFFT), inverse discrete Fourier transform (IDFT), and inverse discrete cosine transform (IDCT) can be used to transform weight data from the antenna domain (or spatial domain) to the beam domain (or angular domain). Weight data exhibits a certain degree of sparsity in the beam domain, so certain beam directions can be set to zero to reduce the amount of weight data. After transform domain processing and dimensionality reduction by setting some beam directions to zero, each element in the beam domain is uniformly bit compressed to obtain compressed weight data. Figure 7 shows a schematic diagram of bit compression, where compression is based on 16-bit to 8-bit compression, but is not limited to this.

[0094] However, in Massive MIMO scenarios, scheduling more users through spatial division multiplexing is a key approach to increasing capacity. The bottleneck in eCPRI fronthaul traffic occurs precisely when a large number of users are being scheduled. MU pairing consumes a significant number of spatial degrees of freedom, and after MU weights are transformed into the beam domain, spatial sparsity is often less than ideal. If MU weights discard too many directions in the angular domain, compression accuracy decreases, leading to a loss in MU demodulation performance.

[0095] Another implementation method is to use an eCPRI resplitting solution to reduce fronthaul traffic. Figure 8 shows a possible eCPRI resplitting scheme. SRS measurement and MU weight calculation are moved from the BBU to the AAU, eliminating the need to transmit MU weight data from the BBU to the AAU, thereby reducing fronthaul traffic.

[0096] However, different AAUs correspond to different sectors, and the loads of different sectors often vary significantly. When a BBU is connected to multiple AAUs simultaneously, as shown in Figure 9, which illustrates a single BBU connected to three AAUs, this is not the only example. MU weight calculation on the BBU can form an efficient resource pool, eliminating the need to reserve computing resources based on all AAUs reaching their maximum capacity simultaneously. If MU weight calculation were moved up to the AAU, the resource pooling effect would be lost, and each AAU would need to reserve resources for MU weight calculation at its maximum capacity, increasing overall base station costs.

[0097] In order to solve one or more of the above-mentioned technical problems, a technical solution of an embodiment of the present application is provided, which can utilize the structural characteristics of weight data to compress the weight data, thereby reducing the fronthaul traffic, and at the same time avoid moving the weight calculation function to AAU, so that the benefits of the resource pool can still be obtained on the BBU, avoiding the increase of base station costs.

[0098] Referring to Figure 10, a schematic diagram of an access network device provided in an embodiment of the present application includes a BBU and an AAU. It is understood that as the access network architecture changes, the BBU and AAU described above may be replaced with other names, for example, BBU may be replaced with DU, and AAU may be replaced with RU, etc.

[0099] The BBU is used to dynamically determine the weight compression switch or depth based on the current load. For example, if the current fronthaul load is high and the traffic is about to exceed the optical module capacity, the weight compression switch is turned on (i.e., the compression method provided in the embodiment of the present application is started to compress the weight data), reducing the fronthaul load rate to provide more service traffic. For the calculated weight data, the compression method provided in the embodiment of the present application is used to compress the weight data to achieve the purpose of data compression. The compressed data is sent to the AAU, for example, the compressed data is encapsulated into an eCPRI frame, and the eCPRI frame is sent to the AAU.

[0100] The AAU is used to decompress received weight data using a decompression method symmetric to the BBU compression method. For example, it extracts weight data from eCPRI frames and decompresses the weight data using a decompression method symmetric to the BBU compression method, restoring the weight data to its original dimensions.

[0101] In some embodiments, the BBU can flexibly switch the compression module or adjust the degree of compression according to current performance requirements, bandwidth requirements, etc.

[0102] It can be understood that there can be multiple fronthaul splitting methods for the access network device, including but not limited to the eCPRI fronthaul splitting method shown in Figure 4, which is applicable as long as the fronthaul splitting involves the transmission of downlink weight data.

[0103] Referring to Figure 11, which is a flow chart of a data processing method provided in an embodiment of the present application, the method can be applied to a first device, which can be a device in an access network device, such as a BBU. Unless otherwise specified, the "first device" in this application can refer to the first device itself (such as a BBU), or a component in the first device (such as a processor, a chip, or a chip system, etc.), or a logical module or software that can implement all or part of the functions of the first device. The method includes:

[0104] S101. Acquire spatial beamforming weight data corresponding to a first stream transmitted on a first resource block group;

[0105] Among them, the resource block group (RBG) may include one or more resource blocks (RBs). For example, 1 RB, 2 RBs, or 4 RBs, or even a larger granularity, is not limited in the embodiments of the present application. The first resource block group may be any resource block group. It is understood that the embodiments of the present application may adopt the same processing method for each resource group in multiple resource block groups. Therefore, the processing method for the first resource block group described below may also be applied to other resource block groups.

[0106] The first resource block group can transmit spatial beamforming weight data corresponding to multiple streams, and the multiple streams can be streams of multiple users. In other words, the spatial beamforming weight data transmitted on the first resource block group can be MU weight data, and one user can have one or more streams transmitted on the first resource block group.

[0107] In a specific implementation, obtaining spatial beamforming weight data corresponding to a first stream transmitted on a first resource block group may include:

[0108] First, obtain spatial beamforming weight data corresponding to multiple streams transmitted on the first resource block group. The spatial beamforming weight data corresponding to the multiple streams is a spatial beamforming weight matrix with a weight dimension of the number of streams × the number of antennas. For example, it is a spatial beamforming weight matrix with a dimension of P*Q, where P is the number of antennas on the antenna array, and Q is the number of streams transmitted on the first resource block group. P and Q are positive integers, as shown in Figure 12, which is a schematic diagram of the spatial beamforming weight data.

[0109] Then, a column is determined from the spatial beamforming weight matrix. The determined column is the spatial beamforming weight data corresponding to the first stream. The determined column can be any column in the spatial beamforming weight matrix. In other words, the first stream can be any stream among the multiple streams (i.e., the first stream can be any stream transmitted on the first resource block group). It will be understood that the embodiments of the present application can use the same processing method for each stream on the first resource block group. Therefore, the processing method for the first stream described below can also be applied to other streams.

[0110] S102. Rearrange the spatial beamforming weight data to obtain rearranged spatial beamforming weight data;

[0111] In one possible design, the spatial beamforming weight data can be rearranged according to the antenna array structure. Specifically, the spatial beamforming weight data corresponding to the first stream is rearranged according to the antenna array configuration, such as rearranging the spatial beamforming weight data according to the horizontal and vertical antenna arrangements. The rearranged spatial beamforming weight data is a spatial beamforming weight matrix with a weight dimension of the number of horizontal antennas × the number of vertical antennas. Figure 13 shows a schematic diagram of the rearranged spatial beamforming weight data corresponding to a single stream.

[0112] S103: Perform a first processing on the rearranged spatial beamforming weight data in at least one directional dimension of the antenna array surface to convert the rearranged spatial beamforming weight data into angular domain, thereby obtaining angular domain beamforming weight data corresponding to the first stream.

[0113] The first processing refers to a processing method of converting the rearranged spatial beamforming weight data from the spatial domain to the angular domain, such as but not limited to any one of IFFT, IDFT, IDCT, etc.

[0114] At least one directional dimension includes but is not limited to the following three: horizontal direction, vertical direction, and horizontal and vertical direction. In other words, in the embodiment of the present application, the spatial domain to angular domain conversion can be performed on the rearranged spatial domain beamforming weight data only in the horizontal direction, the spatial domain to angular domain conversion can be performed on the rearranged spatial domain beamforming weight data only in the vertical direction, and the spatial domain to angular domain conversion can be performed on the rearranged spatial domain beamforming weight data in both the vertical and horizontal directions.

[0115] In some possible embodiments, when the structure of the antenna array surface is a regularly arranged antenna array (for example, there are M*N antennas arranged in M ​​rows and N columns), the rearranged spatial beamforming weight data can be subjected to a point-wise Fourier transform processing in at least one directional dimension of the antenna array surface, and the angular domain beamforming weight data corresponding to the first stream is an angular domain beamforming weight matrix.

[0116] In other possible embodiments, when the antenna array structure is an irregularly arranged antenna array, the rearranged spatial beamforming weight data can be Fourier transformed with multiple points in at least one directional dimension of the antenna array to obtain multiple angular beamforming weight matrices. The angular beamforming weight data corresponding to the first stream includes multiple angular beamforming weight matrices, each of which corresponds to a regularly arranged antenna array. For example, FIG14 shows schematic diagrams of performing a 12-point IFFT transform and a 4-point IFFT transform on the rearranged spatial beamforming weight data, respectively. The transformed effect is shown in FIG15 , which is equivalent to performing an IFFT transform on the spatial beamforming weight data of multiple regularly arranged antenna arrays. In this way, the complexity of subsequent compression processing can be reduced, and the applicability of the solution can be improved.

[0117] S104, dividing the angular domain beamforming weight data into one or more subsets; compressing each subset according to a target compression bit width corresponding to each subset in the one or more subsets to obtain compressed beamforming weight data for each subset;

[0118] When the embodiment of the present application compresses the angular domain beamforming weight data, the angular domain beamforming weight data is adaptively bit-width compressed to fully utilize the sparsity of the beamforming weight data in the angular domain to obtain a high compression rate. Exemplarily, the angular domain beamforming weight data is divided into one or more subsets; according to the target compression bit width of the angular domain beamforming weight data corresponding to the first stream and the effective bit width of each subset in the one or more subsets, the target compression bit width corresponding to each subset in the one or more subsets is determined; according to the target compression bit width corresponding to each subset in the one or more subsets, each subset is compressed. In other words, the angular domain beamforming weight data is divided into one or more subsets, and different subsets can have different target compression bit widths (of course, it is not ruled out that different subsets can have the same target compression bit width), and compression is performed separately.

[0119] The target compression bit width can refer to the bit width to be achieved after data is compressed. For example, if 3-bit data needs to be compressed to 2 bits, then 2 bits is the target compression bit width. The target compression bit width can also refer to the compression amount, that is, the difference between the compression amount and the compression amount. For example, if 3-bit data needs to be compressed to 2 bits, then 3 bits - 2 bits = 2 bits is the target compression bit width. For ease of description, this article uniformly uses the target compression bit width as an example of the bit width to be achieved after data is compressed.

[0120] It can be understood that in the embodiment of the present application, the target compression bit width can also be replaced by other descriptions, such as target compression bits.

[0121] In a specific implementation, the target compression bit width corresponding to the subset may include the target compression bit width of each element in the subset, that is, the bit width to be achieved after each element is compressed. The effective bit width of the subset may include the effective bit width of each element in the subset, that is, the number of bits occupied by valid information in the element.

[0122] It is understood that the effective bit width of each element and the actual bit width of each element (i.e., the actual bit width occupied, which may also be referred to as the original bit width or default bit width, etc.) may be different, and the effective bit width ≤ the actual bit width. For example, if the protocol or system stipulates that the default bit width of each element is 8 bits, and the valid information of an element only occupies 6 bits, then the element may include 6 bits of valid information and 2 bits of redundant information (such as padded with 0s). In this case, the actual bit width of the element is 8 bits, and the effective bit width is 6 bits.

[0123] In one possible implementation, the target compressed bit width of the angular domain beamforming weight data corresponding to the first stream can be calculated based on a transmission time interval (TTI) scheduling information. Exemplarily, the target compressed bit width of the angular domain beamforming weight data corresponding to the first stream satisfies the following relationship:

[0124] Among them, N bit is the target compressed bit width of the angular domain beamforming weight data corresponding to the first stream; T, α, β are constant coefficients; N U is the number of users; Q m,i is the modulation order; N RB,i is the number of scheduled RBs; N rank,i The number of scheduled flows.

[0125] Here are two specific examples:

[0126] Example 1, step S103, performs a first processing on the rearranged spatial beamforming weight data in a directional dimension (e.g., a first directional dimension) of the antenna array face to obtain angular beamforming weight data. The first directional dimension is a dimension corresponding to a first direction, which can be a horizontal direction or a vertical direction, without limitation. Optionally, the number of antennas on the antenna array face in the first direction is greater than or equal to the number of antennas on the antenna array face in the second direction.

[0127] As shown in FIG16 , it is a schematic diagram of angular domain beamforming weight data obtained after performing IFFT in the horizontal dimension. The angular domain beamforming weight data shows obvious sparsity in the horizontal dimension.

[0128] It can be understood that when the antenna array is a regularly arranged antenna array, the angular domain beamforming weight data is an angular domain beamforming weight matrix, and when the antenna array is an irregularly arranged antenna array, the angular domain beamforming weight data is multiple angular domain beamforming weight matrices. Therefore, the angular domain beamforming weight data includes one or more angular domain beamforming weight matrices.

[0129] Each angular-domain beamforming weight matrix is ​​processed as follows: the matrix is ​​divided into at least one subset according to its rows (or columns), wherein one subset corresponds to a row (or column) of the matrix. It is understood that the direction of the rows (or columns) of the matrix corresponds to the first directional dimension.

[0130] In other words, each angular domain beamforming weight matrix is ​​divided into rows (or columns); according to the target compression bit width of the angular domain beamforming weight data corresponding to the first stream (or the target compression bit width of the matrix) and the effective bit width of each element in each row (or column), the target compression bit width corresponding to each element in each row (or column) is determined; and according to the target compression bit width corresponding to each element in each row (or column), the element is compressed.

[0131] The above example 1 performs a one-dimensional beam transformation (such as IFFT) on the spatial domain beamforming weight data of a single stream, transforms it to the angular domain, and adaptively compresses the angular domain beamforming weight data according to the granularity of a single horizontal / vertical (i.e., row / column of the matrix) beam block. This fully utilizes the sparsity of the angular domain beamforming weight data, obtains a higher compression rate, and has the effect of reducing the forward transmission traffic.

[0132] Example 2, step S103, performs a first processing on the rearranged spatial beamforming weight data in two directional dimensions (e.g., a first directional dimension and a second directional dimension) of the antenna array to obtain angular beamforming weight data. The first directional dimension is the dimension corresponding to the first direction, and the second directional dimension is the dimension corresponding to the second direction. The first direction is horizontal, and the second direction is vertical; alternatively, the second direction is horizontal, and the first direction is vertical, without limitation.

[0133] As shown in FIG17 , it is a schematic diagram of angular domain beamforming weight data obtained after the first processing in the horizontal and vertical dimensions respectively. The angular domain beamforming weight data shows obvious sparsity in both the horizontal and vertical dimensions.

[0134] It can be understood that when the antenna array is a regularly arranged antenna array, the angular domain beamforming weight data is an angular domain beamforming weight matrix (corresponding to a regular antenna array). When the antenna array is an irregularly arranged antenna array, the angular domain beamforming weight data is multiple angular domain beamforming weight matrices (corresponding to multiple regular antenna arrays respectively), or it can be a single angular domain beamforming weight matrix (corresponding to an irregular antenna array), which is not limited in the embodiments of the present application.

[0135] Taking the example of angular beamforming weight data being an angular beamforming weight matrix, the angular beamforming weight data can be processed as follows: peak data in the angular beamforming weight data is determined; signal reconstruction of the peak data is performed based on the structure of the antenna array surface corresponding to the angular beamforming weight data to obtain a main signal (optionally, position information corresponding to the main signal on the antenna array surface can also be determined); and the main signal is subtracted from the angular beamforming weight data to obtain a residual signal. The peak data and the residual signal are two different subsets. Peak data can be understood as data corresponding to the amplitude peak in the angular beamforming weight data. For example, the portion indicated by the arrow in Figure 17 is the portion where the peak data is located. It is understood that the peak data described above can also be replaced by other descriptions, such as fitted sub-diameters, pulse signals, or signal peaks, without limitation. Position information can be a position index, such as a row index or column index, or other information representations, without limitation.

[0136] In other words, the angular domain beamforming weight data is divided into the main signal and the residual signal; the main signal and the residual signal can be compressed and transmitted with different target compression bit widths. Among them, only the peak data of the main signal can be compressed.

[0137] In the above example 2, by performing a two-dimensional beam transformation (such as IFFT) on the spatial domain beamforming weight data of a single stream, transforming it into the angular domain, and then using the peak data and the residual signal to compress them according to different target compression bit widths, a better compression effect can be achieved, which can reduce the forward transmission traffic.

[0138] S105: Send the compressed beamforming weight data of each subset and the bit width information corresponding to each subset.

[0139] The bit width information corresponding to each subset is used to determine the target compressed bit width corresponding to each subset. In one implementation, the bit width information corresponding to each subset is the target compressed bit width corresponding to each subset. In another implementation, the bit width information corresponding to each subset is an indication information (e.g., an identifier), which can indicate the target compressed bit width corresponding to each subset. Of course, the above two implementations are only examples and are not limited thereto.

[0140] Specifically, the compressed beamforming weight data of each subset in the one or more subsets and the bit width information corresponding to each subset are sent to the second device through the fronthaul network.

[0141] For Example 1 above, the target compression bit width corresponding to each row of each matrix and the compressed element data of each row can be packaged and sent from the first device (e.g., BBU) to the second device (e.g., AAU). Optionally, the number of subsets, i.e., the number of rows M1 of each matrix, can also be sent. Optionally, the number of elements N1 of each subset (i.e., the number of elements in each row of each matrix) can also be sent.

[0142] For example, taking the beamforming weight data of each RBG as containing L (number of streams) × Ntx (number of transmitting antennas) complex elements, L and Ntx are positive integers. The number of data elements of the beamforming weight data of each RBG remains unchanged after compression by the above method, that is, each stream has Ntx complex elements. The BBU and AAU can agree on the number of subsets to be divided (such as M1, M1 is a positive integer) and the number of elements in each subset (it is understood that the number of elements in different subsets can be different). Then, in S105, the data sent may include:

[0143] 1) The compressed complex elements of each row of each matrix;

[0144] 2) A bit width indication W for each row of each matrix (W includes the target compression bit width corresponding to each element in the row. The bit width indication W for different rows can be different, such as W1, W2, ..., Wn, etc., all of which are positive integers). The real and imaginary parts of each element in each row can use different bit width indications respectively;

[0145] 3) Number of subsets (e.g., M1). Of course, M1 may not be transmitted from the BBU to the AAU. For example, the number of subsets can be agreed upon between the BBU and the AAU.

[0146] 4) The number of elements in each subset: Of course, the number of elements in each subset may not be transmitted from the BBU to the AAU. For example, the number of elements in each subset may be agreed upon between the BBU and the AAU.

[0147] For Example 2 above, the compressed peak data, the target compressed bit width of the compressed peak data, the compressed residual signal, and the target compressed bit width of the compressed residual signal can be packaged and sent from the first device (e.g., BBU) to the second device (e.g., AAU). Optionally, the location information of the peak data can also be sent. Optionally, the data volume of the compressed peak data (e.g., M2 complex elements) and the data volume of the compressed residual signal (e.g., N2 complex elements) can also be sent.

[0148] For example, the beamforming weight data for each RBG contains L (number of streams) × Ntx (number of transmitting antennas) complex elements, where L and Ntx are positive integers. The number of data elements in the beamforming weight data for each RBG remains unchanged after compression using the above method, i.e., each stream has Ntx complex elements. The BBU and AAU can agree on the need to divide the data into two categories: the first category (corresponding to peak data) has M2 complex elements, and the second category (corresponding to residual signals) has N2 complex elements, where M2 and N2 are positive integers. Then, in S105, the data to be sent may be:

[0149] 1) Each complex element in the first type of data after compression;

[0150] [Corrected 03.03.2025 according to Rule 91] 2) each complex element in the second type of data after compression;

[0151] 3) The bit width of each complex element of the first type of data is indicated, for example, by W21(1, 2, ..., M2). Each complex element of the first type of data can be indicated by two indexes, I2(1, 2, ..., M2) and J2(1, 2, ..., M2), and both the real and imaginary parts of the complex element are quantized using W21(1, 2, ..., M2);

[0152] 4) a bit width indication of each complex element of the second type of data, for example, W22(1, 2, ..., N2) is used as the indication, and both the real part and the imaginary part of the complex element are quantized using W22(1, 2, ..., N2);

[0153] 5) Position information of each element in the first type of data, such as I2(1,2,…,M2) and J2(1,2,…,M2);

[0154] 6) The number of elements of the first type of data (M2). Of course, M2 does not need to be transmitted from the BBU to the AAU. For example, M2 can be agreed upon between the BBU and the AAU;

[0155] 7) The number of elements of the second type of data (N2). Of course, N2 may not be transmitted from the BBU to the AAU. For example, N2 can be agreed upon between the BBU and the AAU.

[0156] The embodiment of the present application performs a beam transformation from the spatial domain to the angular domain on the spatial domain beamforming weight data according to the single-stream granularity and in combination with the structure of the antenna array, so that the obtained angular domain beamforming weight data has good sparsity to facilitate subsequent compression. When compressing the angular domain beamforming weight data, the angular domain beamforming weight data is classified (such as by row classification, or by classification of the main signal and the residual signal, etc.) and adaptive bit width compression is performed (that is, different classes can be compressed according to different target compression bit widths). The sparsity of the angular domain beamforming weight data is fully utilized to obtain a high compression rate, which can effectively reduce the fronthaul traffic. In addition, it can also reduce or even avoid forcibly abandoning certain directions in the angular domain, thereby reducing or even avoiding MU demodulation performance loss.

[0157] In one possible design, the elements corresponding to the weight data of multiple RBGs can be transformed in the third dimension in the beam domain (such as IFFT), transforming the third dimension from the frequency domain to the delay domain. The first two dimensions (such as the horizontal dimension and the vertical dimension mentioned above) are combined to form a three-dimensional beam transformation and bit width compression, which can achieve better sparsity and compression rate.

[0158] Exemplarily, beamforming weight data corresponding to multiple resource block groups are obtained, and the multiple resource block groups include a first resource block group; the beamforming weight data corresponding to the multiple resource block groups are arranged according to a third direction dimension, the third direction dimension is the dimension corresponding to the third direction, and the multiple resource block groups are arranged in the third direction, that is, the third direction is the frequency domain dimension, and the third direction is different from the first direction and the second direction. For example, as shown in Figure 18, the frequency domain dimension is perpendicular to the plane where the horizontal antenna dimension and the vertical antenna dimension are located; the beamforming weight data corresponding to the multiple resource block groups are subjected to a second processing in the third direction dimension to convert the beamforming weight data corresponding to the multiple resource block groups from the frequency domain to the delay domain, and obtain delay domain beamforming weight data corresponding to the multiple resource block groups; the delay domain beamforming weight data are compressed.

[0159] The second processing may refer to the first processing, for example, including but not limited to any one of IFFT, IDFT, IDCT, etc. In other words, the transformation method and compression method in the third dimension may refer to the transformation method and compression method in Example 1 or Example 2 above, and will not be repeated here.

[0160] The above introduces the compression method, and the following introduces the decompression method.

[0161] Referring to Figure 19, which is a flowchart of another data processing method provided in an embodiment of the present application, the method can be applied to a second device, which can be a device in an access network device, for example, an AAU. Unless otherwise specified, the "second device" in this application can refer to the second device itself (such as an AAU), or a component in the second device (such as a processor, chip, or chip system, etc.), or a logical module or software that can implement all or part of the functions of the second device. The method includes:

[0162] S201: Receive compressed beamforming weight data of each subset in one or more subsets and bit width information corresponding to each subset, where the bit width information corresponding to each subset is used to determine a target compressed bit width corresponding to each subset;

[0163] It can be understood that the content received by the second device in S201 here corresponds to the content sent by the first device in S105 above. Therefore, the specific description of the content received by the second device in S201 here refers to the specific description of the content sent by the first device in S105 above, and will not be repeated.

[0164] S202. Decompress each subset according to bit width information corresponding to each subset to obtain angle-domain beamforming weight data corresponding to a first stream transmitted on a first resource block group;

[0165] Exemplarily, the second device can determine the original bit width of each subset (such as the original bit width of each element in each subset, for example, the protocol stipulates or the system agrees on the size of the original bit width of each element. The second device can determine the target compressed bit width corresponding to each subset based on the bit width information corresponding to each subset (such as the target compressed bit width of each element in each subset, that is, the bit width of each element after compression), and decompress each subset based on the original bit width and target compressed bit width (for example, restore each element from the compressed bit width to the original bit width). The specific decompression method is not limited in this application.

[0166] S203: Perform a third processing on the angular domain beamforming weight data in at least one directional dimension of the antenna array surface to convert the angular domain beamforming weight data into the spatial domain, thereby obtaining rearranged spatial domain beamforming weight data.

[0167] The third processing is an inverse processing of the first processing, for example, any one of fast Fourier transform (FFT), discrete Fourier transform (DFT), and discrete cosine transform (DCT).

[0168] S204: Restore the rearranged spatial beamforming weight data to obtain spatial beamforming weight data corresponding to the first stream transmitted on the first resource block group.

[0169] It can be understood that the second device uses the opposite method of the first device to perform decompression, so the decompression process can refer to the compression process above and will not be elaborated here.

[0170] Of course, the above is only an example of a possible decompression process. The actual decompression method is not limited to this, and the embodiments of the present application do not limit the decompression method.

[0171] It can be understood that the above embodiments can be implemented separately or in combination with each other without limitation.

[0172] The method provided by the embodiment of the present application is described above in conjunction with the accompanying drawings, and the device provided by the embodiment of the present application is described below in conjunction with the accompanying drawings.

[0173] The present application provides a communication device 210, which may be, for example, a satellite, a base station, a terminal, or an access point, or a device within a satellite, a base station, a terminal, or an access point. The device 210 includes modules, units, or means for executing the method steps in the above method embodiments. The functions, units, or means may be implemented by software or hardware, or may be implemented by hardware executing the corresponding software implementation.

[0174] 20 , the apparatus 210 may include a processing module 211 and a transceiver module 212. The transceiver module 212 may include only a sending module, or only a receiving module, or both a sending module and a receiving module, without limitation.

[0175] When the device 210 is located at the first device:

[0176] The processing module 211 is configured to obtain spatial beamforming weight data corresponding to a first stream transmitted on a first resource block group; rearrange the spatial beamforming weight data to obtain rearranged spatial beamforming weight data; perform a first process on the rearranged spatial beamforming weight data in at least one directional dimension of an antenna array plane to convert the rearranged spatial beamforming weight data into an angular domain to obtain angular domain beamforming weight data corresponding to the first stream; divide the angular domain beamforming weight data into one or more subsets; and compress each subset according to a target compression bit width corresponding to each subset in the one or more subsets to obtain compressed beamforming weight data for each subset.

[0177] The transceiver module 212 is configured to transmit the compressed beamforming weight data of each subset and the bit width information corresponding to each subset. The bit width information corresponding to each subset is used to determine the target compression bit width corresponding to each subset.

[0178] In one possible design, when the processing module 211 obtains the spatial beamforming weight data corresponding to the first stream transmitted on the first resource block group, it is specifically used to: obtain the spatial beamforming weight data corresponding to multiple streams transmitted on the first resource block group, wherein the dimension of the spatial beamforming weight data corresponding to the multiple streams is a spatial beamforming weight matrix of P*Q, P is the number of antennas on the antenna array, Q is the number of streams transmitted on the first resource block group, and P and Q are positive integers; determine a column from the spatial beamforming weight matrix, and the determined column is the spatial beamforming weight data corresponding to the first stream.

[0179] In one possible design, the processing module 211 rearranges the spatial beamforming weight data, specifically for: rearranging the spatial beamforming weight data according to the structure of the antenna array, and the rearranged spatial beamforming weight data is a spatial beamforming weight matrix with a weight dimension of the number of horizontal antennas × the number of vertical antennas.

[0180] In one possible design, when the processing module 211 performs a first processing on the rearranged spatial beamforming weight data in at least one directional dimension of the antenna array surface, it is specifically used to: if the structure of the antenna array surface is a regularly arranged antenna array, then the rearranged spatial beamforming weight data is subjected to a Fourier transform processing with a number of points in at least one directional dimension of the antenna array surface to obtain an angular beamforming weight matrix, and the angular beamforming weight data corresponding to the first stream includes an angular beamforming weight matrix; or, if the structure of the antenna array surface is an irregularly arranged antenna array, then the rearranged spatial beamforming weight data is subjected to Fourier transform processing with a plurality of points in at least one directional dimension of the antenna array surface to obtain multiple angular beamforming weight matrices, and the angular beamforming weight data corresponding to the first stream includes multiple angular beamforming weight matrices, and each of the multiple angular beamforming weight matrices corresponds to a regularly arranged antenna array.

[0181] In one possible design, the processing module 211 can also be used to determine the target compression bit width corresponding to each subset in one or more subsets based on the target compression bit width of the angular domain beamforming weight data corresponding to the first stream and the effective bit width of each subset in the one or more subsets.

[0182] In one possible design, when the processing module 211 performs the first processing on the rearranged spatial beamforming weight data in at least one directional dimension of the antenna array surface, the processing module 211 is specifically configured to: perform the first processing on the rearranged spatial beamforming weight data in a first directional dimension of the antenna array surface to obtain angular beamforming weight data, wherein the first directional dimension is a dimension corresponding to the first direction; the angular beamforming weight data includes one or more angular beamforming weight matrices;

[0183] When dividing the angular domain beamforming weight data into one or more subsets, the processing module 211 is specifically configured to divide the elements in one or more angular domain beamforming weight matrices into at least one subset according to the rows of the matrices, wherein one subset corresponds to one row of the matrix.

[0184] In one possible design, the number of antennas on the antenna array surface in the first direction is greater than or equal to the number of antennas on the antenna array surface in the second direction.

[0185] In one possible design, when the processing module 211 performs the first processing on the rearranged spatial beamforming weight data in at least one directional dimension of the antenna array surface, the processing module 211 is specifically configured to: perform the first processing on the rearranged spatial beamforming weight data in a first directional dimension and a second directional dimension of the antenna array surface, respectively, to obtain angular beamforming weight data, where the first directional dimension is a dimension corresponding to the first direction, and the second directional dimension is a dimension corresponding to the second direction;

[0186] When dividing the angular domain beamforming weight data into one or more subsets, the processing module 211 is specifically used to: determine the peak data in the angular domain beamforming weight data; reconstruct the peak data according to the structure of the antenna array to obtain a main signal; and subtract the main signal from the angular domain beamforming weight data to obtain a residual signal; wherein the peak data and the residual signal are two different subsets.

[0187] In one possible design, the transceiver module 212 can also be used to send position information corresponding to the main signal on the antenna array.

[0188] In a possible design, the processing module 211 may also be configured to calculate a target compressed bit width of the angular domain beamforming weight data corresponding to the first stream according to TTI scheduling information.

[0189] In one possible design, the processing module 211 can also be used to: obtain beamforming weight data corresponding to multiple resource block groups, the multiple resource block groups including a first resource block group; arrange the beamforming weight data corresponding to the multiple resource block groups according to a third direction dimension, the third dimension direction is the dimension corresponding to the third direction, and the third direction is different from the first direction and the second direction; perform a second processing on the beamforming weight data corresponding to the multiple resource block groups in the third direction dimension to convert the beamforming weight data corresponding to the multiple resource block groups into the delay domain, and obtain delay domain beamforming weight data corresponding to the multiple resource block groups; and perform compression processing on the delay domain beamforming weight data.

[0190] In one possible design, the first processing is any one of IFFT, IDFT, and IDCT.

[0191] When the device 210 is located in the second device:

[0192] The transceiver module 212 is configured to receive the compressed beamforming weight data and bit width information of each subset in one or more subsets, wherein the bit width information corresponding to each subset is used to determine a target compressed bit width corresponding to each subset;

[0193] Processing module 211 is used to decompress each subset according to the bit width information corresponding to each subset to obtain angular domain beamforming weight data corresponding to the first stream transmitted on the first resource block group; perform a third processing on the angular domain beamforming weight data in at least one directional dimension of the antenna array surface to convert the angular domain beamforming weight data into the spatial domain to obtain rearranged spatial domain beamforming weight data; and restore the rearranged spatial domain beamforming weight data to obtain spatial domain beamforming weight data corresponding to the first stream transmitted on the first resource block group.

[0194] In one possible design, the third processing is any one of FFT, DFT, and DCT.

[0195] It should be understood that all relevant contents of each step involved in the above method embodiment can be referred to the functional description of the corresponding functional module and will not be repeated here.

[0196] Based on the same technical concept, referring to FIG. 21 , an embodiment of the present application further provides a communication device 220, including:

[0197] At least one processor 221; and a communication interface 223 communicatively connected to the at least one processor 221; the at least one processor 221 executes instructions stored in the memory 222, causing the apparatus to perform the method steps of the above-mentioned method embodiment through the communication interface 223. The communication interface 223 can be used to perform the functions of the above-mentioned transceiver module 212, and the processor 221 can be used to perform the functions of the above-mentioned processing module 211.

[0198] Optionally, the memory 222 is located outside the device 220 .

[0199] Optionally, the apparatus 220 includes the memory 222, the memory 222 being connected to the at least one processor 221, and the memory 222 storing instructions executable by the at least one processor 221. FIG21 uses dashed lines to indicate that the memory 222 is optional for the apparatus 220.

[0200] The processor 221 and the memory 222 may be coupled via an interface circuit or may be integrated together, which is not limited here.

[0201] The specific connection medium between the processor 221, memory 222, and communication interface 223 is not limited in the embodiments of the present application. In Figure 21, the processor 221, memory 222, and communication interface 223 are connected via a bus 224. The bus is represented by a bold line in Figure 21. The connection between other components is only for schematic illustration and is not intended to be limiting. The bus can be divided into an address bus, a data bus, a control bus, etc. For ease of illustration, Figure 21 only uses a single bold line, but this does not mean that there is only one bus or one type of bus.

[0202] The specific connection medium between the processor 221, memory 222, and communication interface 223 is not limited in the embodiments of the present application. In Figure 21, the processor 221, memory 222, and communication interface 223 are connected via a bus 224. The bus is represented by a bold line in Figure 21. The connection between other components is only for schematic illustration and is not intended to be limiting. The bus can be divided into an address bus, a data bus, a control bus, etc. For ease of illustration, Figure 21 only uses a single bold line, but this does not mean that there is only one bus or one type of bus.

[0203] Based on the same technical concept, an embodiment of the present application further provides a communication device 230. Referring to FIG. 22 , the communication device 230 includes a processor 231 and an interface circuit 232. The interface circuit 232 is electrically coupled to the processor 231. The processor 231 executes the method steps in the above-described method embodiment through logic circuits or by executing code instructions. Optionally, the communication device 230 also includes a memory. The interface circuit 232 can be used to perform the functions of the above-described transceiver module 212, and the processor 231 can be used to perform the functions of the above-described processing module 211.

[0204] It should be understood that the processors mentioned in the embodiments of the present application can be implemented by hardware or software. When implemented by hardware, the processor can be a logic circuit, an integrated circuit, etc. When implemented by software, the processor can be a general-purpose processor that is implemented by reading software code stored in a memory.

[0205] Exemplarily, the processor 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. The general-purpose processor may be a microprocessor or any conventional processor, etc.

[0206] It should be understood that the memory mentioned in the embodiments of the present application may be a volatile memory or a non-volatile memory, or may include both volatile and non-volatile memories. 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), which is used as an external cache. By way of example and not limitation, many forms of RAM are available, such as 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 RAM bus random access memory (DR RAM).

[0207] 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.

[0208] It should be noted that the memory described herein is intended to include, but not be limited to, these and any other suitable types of memory.

[0209] Based on the same technical concept, an embodiment of the present application further provides a computer-readable storage medium, including a program or instructions. When the program or instructions are run on a computer, the method in the above method embodiment is executed.

[0210] Based on the same technical concept, an embodiment of the present application further provides a computer program product, including instructions, which, when executed on a computer, enables the method in the above method embodiment to be executed.

[0211] Those skilled in the art will appreciate that the embodiments of the present application can be provided as methods, systems, or computer program products. Therefore, the present application can adopt the form of a complete hardware embodiment, a complete software embodiment, or an embodiment in combination with software and hardware. Moreover, the present application can adopt the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to magnetic disk storage, CD-ROM, optical storage, etc.) that contain computer-usable program code.

[0212] The present application is described with reference to the flowcharts and / or block diagrams of the methods, devices (systems), and computer program products according to the present application. It should be understood that each flow and / or box in the flow chart and / or block diagram, as well as the combination of the flow chart and / or box in the flow chart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device produce a device for implementing the functions specified in one or more flow charts and / or one or more boxes in the block diagram.

[0213] These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce a product including an instruction device that implements the functions specified in one or more processes in the flowchart and / or one or more boxes in the block diagram.

[0214] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, so that the instructions executed on the computer or other programmable device provide steps for implementing the functions specified in one or more processes in the flowchart and / or one or more boxes in the block diagram.

Claims

1. A data processing method, characterized in that: include: Acquire spatial beamforming weight data corresponding to a first stream transmitted on a first resource block group; Rearranging the spatial beamforming weight data to obtain rearranged spatial beamforming weight data; performing a first processing on the rearranged spatial beamforming weight data in at least one directional dimension of the antenna array surface to convert the rearranged spatial beamforming weight data into an angular domain to obtain angular domain beamforming weight data corresponding to the first stream; Dividing the angular domain beamforming weight data into one or more subsets; compressing each subset according to a target compression bit width corresponding to each subset in the one or more subsets to obtain compressed beamforming weight data for each subset; The compressed beamforming weight data of each subset and the bit width information corresponding to each subset are sent, where the bit width information corresponding to each subset is used to determine a target compression bit width corresponding to each subset.

2. The method according to claim 1, wherein The acquiring spatial beamforming weight data corresponding to the first stream transmitted on the first resource block group includes: Acquire spatial beamforming weight data corresponding to multiple streams transmitted on the first resource block group, wherein the spatial beamforming weight data corresponding to the multiple streams has a dimension of P*Q spatial beamforming weight matrix, where P is the number of antennas on the antenna plane, Q is the number of streams transmitted on the first resource block group, and P and Q are positive integers; A column is determined from the spatial beamforming weight matrix, where the determined column is the spatial beamforming weight data corresponding to the first stream.

3. The method according to claim 1 or 2, wherein: Rearranging the spatial beamforming weight data includes: The spatial beamforming weight data is rearranged according to the structure of the antenna array, and the rearranged spatial beamforming weight data is a spatial beamforming weight matrix with a weight dimension of the number of horizontal antennas×the number of vertical antennas.

4. The method according to any one of claims 1 to 3, wherein The performing a first processing on the rearranged spatial beamforming weight data in at least one directional dimension of the antenna array plane includes: If the structure of the antenna array surface is a regularly arranged antenna array, performing a point-wise Fourier transform processing on the rearranged spatial beamforming weight data in at least one directional dimension of the antenna array surface to obtain an angular beamforming weight matrix, and the angular beamforming weight data corresponding to the first stream includes the angular beamforming weight matrix; or If the structure of the antenna array surface is an irregularly arranged antenna array, the rearranged spatial beamforming weight data is subjected to Fourier transform processing at multiple points in at least one directional dimension of the antenna array surface to obtain multiple angular beamforming weight matrices. The angular beamforming weight data corresponding to the first stream includes the multiple angular beamforming weight matrices, and each of the multiple angular beamforming weight matrices corresponds to a regularly arranged antenna array.

5. The method according to any one of claims 1 to 4, characterized in that The method further comprises: The target compressed bit width corresponding to each of the one or more subsets is determined according to the target compressed bit width of the angular domain beamforming weight data corresponding to the first stream and the effective bit width of each of the one or more subsets.

6. The method according to any one of claims 1 to 5, wherein: The performing a first processing on the rearranged spatial beamforming weight data in at least one directional dimension of the antenna array plane includes: performing a first processing on the rearranged spatial beamforming weight data in a first directional dimension of the antenna array plane to obtain angular beamforming weight data, wherein the first directional dimension is a dimension corresponding to the first direction; the angular beamforming weight data includes one or more angular beamforming weight matrices; The dividing the angular domain beamforming weight data into one or more subsets includes: Elements in the one or more angular domain beamforming weight matrices are divided into at least one subset according to the rows of the matrices, where one subset corresponds to one row of the matrix.

7. The method according to claim 6, wherein The number of antennas on the antenna array surface in the first direction is greater than or equal to the number of antennas on the antenna array surface in the second direction.

8. The method according to any one of claims 1 to 5, wherein: The performing a first processing on the rearranged spatial beamforming weight data in at least one directional dimension of the antenna array plane includes: Performing a first processing on the rearranged spatial beamforming weight data in a first directional dimension and a second directional dimension of the antenna array plane, respectively, to obtain angular beamforming weight data, wherein the first directional dimension is a dimension corresponding to the first direction, and the second directional dimension is a dimension corresponding to the second direction; The dividing the angular domain beamforming weight data into one or more subsets includes: Determine peak data in the angular domain beamforming weight data; reconstruct the peak data according to the structure of the antenna array to obtain a main signal; subtract the main signal from the angular domain beamforming weight data to obtain a residual signal; wherein the peak data and the residual signal are two different subsets.

9. The method according to claim 8, wherein The method further comprises: The position information of the main signal corresponding to the transmission on the antenna array surface.

10. The method according to claim 5, wherein The method further comprises: A target compressed bit width of the angular domain beamforming weight data corresponding to the first stream is calculated according to a transmission time interval TTI scheduling information.

11. The method according to any one of claims 1 to 10, wherein: Also includes: Acquire beamforming weight data corresponding to a plurality of resource block groups, the plurality of resource block groups including the first resource block group; Arranging beamforming weight data corresponding to the plurality of resource block groups according to a third direction dimension, where the third dimension is a dimension corresponding to the third direction, and the third direction is different from the first direction and the second direction; performing a second processing on the beamforming weight data corresponding to the plurality of resource block groups in the third direction dimension to convert the beamforming weight data corresponding to the plurality of resource block groups into a delay domain, thereby obtaining delay-domain beamforming weight data corresponding to the plurality of resource block groups; The delay-domain beamforming weight data is compressed.

12. The method according to any one of claims 1 to 11, wherein: The first processing is any one of Inverse Fast Fourier Transform (IFFT), Inverse Discrete Fourier Transform (IDFT), and Inverse Discrete Cosine Transform (IDCT).

13. A data processing method, characterized in that: include: receiving compressed beamforming weight data of each subset in one or more subsets and bit width information corresponding to each subset, wherein the bit width information corresponding to each subset is used to determine a target compression bit width corresponding to each subset; Decompressing each subset according to the bit width information corresponding to each subset to obtain angle-domain beamforming weight data corresponding to the first stream transmitted on the first resource block group; performing a third processing on the angular domain beamforming weight data in at least one directional dimension of the antenna array plane to convert the angular domain beamforming weight data into a spatial domain to obtain rearranged spatial domain beamforming weight data; The rearranged spatial beamforming weight data is restored to obtain the spatial beamforming weight data corresponding to the first stream transmitted on the first resource block group.

14. The method according to claim 13, wherein The third processing is any one of fast Fourier transform FFT, discrete Fourier transform DFT, and discrete cosine transform DCT.

15. A system, characterized in that: include: A first device, configured to perform the method according to any one of claims 1 to 12; The second device is configured to perform the method according to claim 13 or 14.

16. A communication device, characterized in that: The method comprises a module for executing the method according to any one of claims 1 to 12, or a module for executing the method according to claim 13 or 14.

17. A communication device, characterized in that: The method comprises a processor and an interface circuit, wherein the interface circuit is electrically coupled to the processor, and the processor causes the method according to any one of claims 1 to 12 to be executed through a logic circuit or by executing code instructions, or causes the method according to claim 13 or 14 to be executed.

18. A computer-readable storage medium, characterized in that The storage medium stores a computer program or instruction. When the computer program or instruction is executed, the method according to any one of claims 1 to 12 is executed, or the method according to claim 13 or 14 is executed.

19. A computer program product, characterized in that The invention comprises instructions, which, when executed on a computer, enable the method according to any one of claims 1 to 12 to be executed, or enable the method according to claim 13 or 14 to be executed.

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