Communication method and apparatus

Abstract

The present invention relates to a communication method and an apparatus for transmitting data, the method including: obtaining weight data; performing dimension reduction compression on the weight data to obtain first data; and transmitting the first data, the weight data being used for beamforming, and the dimension of the weight data being greater than the dimension of the first data.

Description

[Technical Field]

[0001] TECHNICAL FIELD Embodiments of the present application relate to the field of communication technologies, and more particularly to communication methods and devices. [Background technology]

[0002] 2. Description of the Related Art With the rapid development of communication technology, the access speed of air interfaces is continuously increasing, and communication networks are evolving towards multiple antennas, multiple streams, and large bandwidths.

[0003] However, the speed of development of communication devices may not match the speed of development of communication networks, which may become a bottleneck that restricts the development of communication networks.

[0004] Therefore, how to make communication devices transmit data in order to adapt to the development of communication networks has become a technical problem that needs to be urgently solved. Summary of the Invention [Problem to be solved by the invention]

[0005] The present application provides a communication method and device that allows a communication device to adapt to the evolution of a communication network when performing data transmission. [Means for solving the problem]

[0006] According to a first aspect, an embodiment of the present application provides a communication method. The method may be applied to a first communication device. The method may include: obtaining weight data; performing dimension reduction compression on the weight data to obtain first data; and transmitting the first data, where the weight data is used for beamforming, and a dimension of the weight data is greater than a dimension of the first data. The weight data being used for beamforming may alternatively be described as the weight data being used for a precoding operation.

[0007] Based on the first aspect, the amount of weight data may be reduced by performing dimensionality reduction compression on the weight data to further reduce the amount of data transmitted by the first communication device through the fronthaul interface and reduce the bandwidth requirements of the fronthaul interface, so that the first communication device can adapt to the evolution of the communication network when performing data transmission through the fronthaul interface.

[0008] In one possible design, the dimension of the weight data is the number of antennas × the number of streams × the number of radio bearers RB.

[0009] In one possible design, if a first condition is satisfied, dimensionality reduction compression is performed on the weight data to obtain first data. The first condition includes a first transmission parameter associated with the weight data being greater than or equal to a first preset threshold or a second transmission parameter associated with the weight data being less than or equal to a second preset threshold. The first transmission parameter includes one or more of a number of streams, a number of antennas, a bandwidth, or a fronthaul load, and the second transmission parameter includes a weight granularity.

[0010] Based on this possible design, the first communication device may perform dimensionality reduction compression on the weight data when the first condition is met to relieve pressure on the fronthaul interface, reduce the bandwidth requirements of the fronthaul interface, and support a larger number of streams, a larger number of antennas, smaller weight granularity, larger bandwidth, higher fronthaul load, etc. Given the rate of the fronthaul optical module, higher-spec radio functionality is enabled.

[0011] In one possible design, dimensionality reduction compression is performed on the weight data based on a first compression ratio to obtain the first data.

[0012] Based on this possible design, the first communication device may perform dimensionality reduction compression on the weight data based on a first compression ratio to ensure that data loss is controllable.

[0013] In one possible design, the first compression rate is preset or determined based on one or more of the following parameters: number of streams, number of antennas, weight granularity, bandwidth, or fronthaul load.

[0014] Based on this possible design, several feasible solutions are provided for the first communication device to determine the first compression ratio.

[0015] In one possible design, a difference between a dimension of the weight data and a dimension of the first data is a first difference, and an absolute value of a difference between a second compression ratio determined based on the first difference and the first compression ratio is less than or equal to a first threshold.

[0016] Based on this possible design, when the first communication device performs dimensionality reduction compression on the weight data, the absolute value of the difference between the second compression rate and the first compression rate is less than or equal to a first threshold, ensuring that data loss is controllable.

[0017] In one possible design, when the dimensionality reduction switch is in an on state, dimensionality reduction compression is performed on the weight data to obtain first data.

[0018] Based on this possible design, the first communication device may perform dimensionality reduction compression when the dimensionality reduction switch is in an on state, and may not perform dimensionality reduction compression when the dimensionality reduction switch is in an off state.

[0019] In one possible design, dimensionality reduction compression is performed on the weight data in one or more of a principal component analysis (PCA) method, a discrete cosine transform (DCT) method, or an autoencoder method to obtain first data.

[0020] Based on this possible design, several possible solutions are provided for the first communication device to perform dimensionality reduction compression on the weight data.

[0021] In one possible design, the first data is quantized to obtain quantized first data, and the quantized first data is transmitted.

[0022] Based on this possible design, the first data obtained through dimensionality reduction compression may be quantized based on the dimensionality reduction compression performed on the weight data, thereby achieving the effect of increasing the compression capacity and further improving the compression effect of the weight data.

[0023] In one possible design, the first communication device includes one or more of a high-specification baseband unit BBH, a central unit CU, a distributed unit DU, a baseband processing unit BBU, or a unit below BBH.

[0024] Based on this possible design, several feasible solutions are provided for the design of the first communication device.

[0025] According to a second aspect, an embodiment of the present application provides a communication method. The method is applied to a second communication device. The method may include the steps of obtaining first data; and performing dimensionality increasing decompression on the first data to obtain weight data, the weight data being used for beamforming, and a dimension of the weight data being greater than a dimension of the first data. The weight data being used for beamforming may alternatively be described as the weight data being used for a pre-coding operation.

[0026] Based on the second aspect, the amount of weight data may be reduced by performing dimensionality reduction compression on the weight data to further reduce the amount of data received by the second communication device through the fronthaul interface and reduce the bandwidth requirements of the fronthaul interface, so that the second communication device may adapt to the evolution of the communication network when performing data transmission through the fronthaul interface.

[0027] In one possible design, the dimension of the weight data is the number of antennas × the number of streams × the number of radio bearers RB.

[0028] In one possible design, a dimensionality increasing decompression is performed on the first data based on a first compression ratio to obtain the weight data.

[0029] Based on this possible design, the second communication device may perform dimensionality increasing decompression on the weight data based on the first compression ratio to ensure that data loss is controllable.

[0030] In one possible design, the first compression rate is preset, or the first compression rate is determined based on one or more parameters of the number of streams, the number of antennas, the weight granularity, the bandwidth, or the fronthaul load.

[0031] Based on this possible design, several feasible solutions are provided for the second communication device to determine the first compression ratio.

[0032] In one possible design, a difference between a dimension of the weight data and a dimension of the first data is a first difference, and an absolute value of a difference between a second compression ratio determined based on the first difference and the first compression ratio is less than or equal to a first threshold.

[0033] Based on this possible design, when the first communication device performs dimensionality reduction compression on the weight data, the absolute value of the difference between the second compression rate and the first compression rate is less than or equal to a first threshold, ensuring that data loss is controllable.

[0034] In one possible design, dimensionality increasing decompression is performed on the first data in one or more of a principal component analysis (PCA) method, a discrete cosine transform (DCT) method, or an autoencoder method to obtain weight data.

[0035] Based on this possible design, several possible solutions are provided for the second communication device to perform dimensionality increasing decompression on the weight data.

[0036] In one possible design, quantized first data is received, and the quantized first data is dequantized to obtain the first data.

[0037] Based on this possible design, the first communication device quantizes the first data obtained through the dimensionality reduction compression based on the dimensionality reduction compression performed on the weight data, to achieve the effect of increasing the compression ability and further improve the compression effect of the weight data.

[0038] In one possible design, the second communication device includes one or more of a low-specification baseband unit (BBL), a remote radio unit (RRU), an active antenna unit (AAU), or a unit below the BBL.

[0039] Based on this possible design, several feasible solutions are provided for the design of the second communication device.

[0040] According to a third aspect, an embodiment of the present application provides a communication device. The communication device may be used in a first communication device in the first aspect or a possible design of the first aspect to implement the functions performed by the first communication device. The communication device may be the first communication device, a first communication device chip or system-on-chip, or a software module capable of implementing the functions of the first aspect. The communication device may perform the functions performed by the first communication device by using hardware, or may execute corresponding software by using hardware. The hardware or software may include one or more modules corresponding to the functions, such as a transceiver module and a processing module. The transceiver module is configured to obtain weight data, which is used for beamforming. The processing module is configured to perform dimensionality reduction compression on the weight data to obtain first data, where the dimension of the weight data is greater than the dimension of the first data. The transceiver module is further configured to transmit the first data.

[0041] In one possible design, the dimension of the weight data is the number of antennas × the number of streams × the number of radio bearers RB.

[0042] In one possible design, the processing module is specifically configured to: perform dimensionality reduction compression on the weight data to obtain first data when a first condition is satisfied. The first condition includes a first transmission parameter associated with the weight data being greater than or equal to a first preset threshold, or a second transmission parameter associated with the weight data being less than or equal to a second preset threshold. The first transmission parameter includes one or more of a number of streams, a number of antennas, a bandwidth, or a fronthaul load, and the second transmission parameter includes a weight granularity.

[0043] In one possible design, the processing module is specifically configured to perform dimensionality reduction compression on the weight data based on a first compression ratio to obtain the first data.

[0044] In one possible design, the first compression rate is preset, or the first compression rate is determined based on one or more parameters of the number of streams, the number of antennas, the weight granularity, the bandwidth, or the fronthaul load.

[0045] In one possible design, a difference between a dimension of the weight data and a dimension of the first data is a first difference, and an absolute value of a difference between a second compression ratio determined based on the first difference and the first compression ratio is less than or equal to a first threshold.

[0046] In one possible design, the processing module is specifically configured to, when the dimensionality reduction switch is in an on state, perform dimensionality reduction compression on the weight data to obtain first data.

[0047] In one possible design, the processing module is specifically configured to perform dimensionality reduction compression on the weight data using one or more of a principal component analysis (PCA) method, a discrete cosine transform (DCT) method, or an autoencoder method to obtain the first data.

[0048] In one possible design, the processing module is further configured to quantize the first data to obtain quantized first data, and the transceiver module is further configured to transmit the quantized first data.

[0049] In one possible design, the first communication device includes one or more of a high-specification baseband unit BBH, a central unit CU, a distributed unit DU, a baseband processing unit BBU, or a unit below BBH.

[0050] It should be noted that the modules in the third aspect or possible designs of the third aspect may perform corresponding functions in the example method of the first aspect. For details, please refer to the detailed description in the example method. For beneficial effects, please refer to the related description in the first aspect. Details will not be described here.

[0051] According to a fourth aspect, an embodiment of the present application provides a communication device. The communication device may be used in a second communication device in the second aspect or a possible design of the second aspect to implement the functions performed by the second communication device. The communication device may be the second communication device, a second communication device chip or system-on-chip, or a software module capable of implementing the functions of the second aspect. The communication device may perform the functions performed by the second communication device by using hardware, or may execute corresponding software by using hardware. The hardware or software may include one or more modules corresponding to the functions, such as a transceiver module and a processing module. The transceiver module is configured to obtain first data. The processing module is configured to perform dimensionality-increasing decompression on the first data to obtain weight data, the weight data being used for beamforming, the dimensionality of the weight data being greater than the dimensionality of the first data.

[0052] In one possible design, the dimension of the weight data is the number of antennas × the number of streams × the number of radio bearers RB.

[0053] In one possible design, the processing module is specifically configured to perform dimensionality increasing decompression on the first data based on a first compression ratio to obtain the weight data.

[0054] In one possible design, the first compression rate is preset, or the first compression rate is determined based on one or more parameters of the number of streams, the number of antennas, the weight granularity, the bandwidth, or the fronthaul load.

[0055] In one possible design, a difference between a dimension of the weight data and a dimension of the first data is a first difference, and an absolute value of a difference between a second compression ratio determined based on the first difference and the first compression ratio is less than or equal to a first threshold.

[0056] In one possible design, the processing module is specifically configured to perform dimensionality increasing decompression on the first data in one or more of a principal component analysis (PCA) method, a discrete cosine transform (DCT) method, or an autoencoder method to obtain the weight data.

[0057] In one possible design, the transceiver module is further configured to receive quantized first data, and the processing module is further configured to dequantize the quantized first data to obtain the first data.

[0058] In one possible design, the second communication device includes one or more of a low-specification baseband unit (BBL), a remote radio unit (RRU), an active antenna unit (AAU), or a unit below the BBL.

[0059] It should be noted that the modules in the fourth aspect or possible designs of the fourth aspect may perform corresponding functions in the example method of the second aspect. For details, please refer to the detailed description in the example method. For beneficial effects, please refer to the related description in the second aspect. Details will not be described herein.

[0060] According to a fifth aspect, an embodiment of the present application provides a communication device. The communication device includes one or more processors. The one or more processors are configured to execute computer programs or instructions. Applicable computer ·program Or, when executing the instructions, the communication device is enabled to perform the communication method according to any one of the first and second aspects.

[0061] In one possible design, the communication device further includes one or more memories. The one or more memories are coupled to the one or more processors, and the one or more memories are configured to store computer programs or instructions. In one possible implementation, the memory is located external to the communication device. In another possible implementation, the memory is located internal to the communication device. In this embodiment of the present application, the processor and memory may alternatively be integrated into one component. In other words, the processor and memory may alternatively be integrated together. In one possible implementation, the communication device further includes a transceiver. The transceiver is configured to receive and / or transmit information.

[0062] In one possible design, the communication device further includes one or more communication interfaces, the one or more communication interfaces coupled to the one or more processors, the one or more communication interfaces configured to communicate with modules other than the communication device.

[0063] According to a sixth aspect, an embodiment of the present application provides a communication device. The communication device includes an input / output interface and a logic circuit. The input / output interface is configured to input and / or output information. The logic circuit is configured to perform the communication method according to any one of the first and second aspects, perform processing based on the information, and / or generate information.

[0064] According to a seventh aspect, an embodiment of the present application provides a computer-readable storage medium that stores computer instructions or a program, which, when executed on a computer, performs the communication method according to any one of the first and second aspects.

[0065] According to an eighth aspect, an embodiment of the present application provides a computer program product including computer instructions that, when executed on a computer, perform a communication method according to any one of the first and second aspects.

[0066] According to a ninth aspect, an embodiment of the present application provides a computer program product, which, when run on a computer, performs the communication method according to any one of the first and second aspects.

[0067] For the technical effects provided by any one of the designs of the fifth to ninth aspects, please refer to the technical effects provided by any one of the first and second aspects.

[0068] According to a tenth aspect, an embodiment of the present application provides a communication system, which may include a first communication device according to the third aspect and a second communication device according to the fourth aspect. [Brief explanation of the drawings]

[0069] [Figure 1] FIG. 2 is a diagram of an association between bands and bandwidth according to an embodiment of the present application.

[0070] [Figure 2] FIG. 10 is a diagram of user data and weight data according to an embodiment of the present application.

[0071] [Figure 3] 1 is a diagram of a communication system according to an embodiment of the present application;

[0072] [Figure 4] 1 is a diagram of an access network device according to an embodiment of the present application.

[0073] [Figure 5] 1 is a diagram of an access network device according to an embodiment of the present application.

[0074] [Figure 6] FIG. 1 is a diagram of a fronthaul interface according to an embodiment of the present application.

[0075] [Figure 7] FIG. 1 is a block diagram of a communication device according to an embodiment of the present application.

[0076] [Figure 8] 1 is a flowchart of a communication method according to an embodiment of the present application;

[0077] [Figure 9] FIG. 1 is a diagram of weight data processing according to an embodiment of the present application.

[0078] [Figure 10] FIG. 1 is a diagram of an autoencoder according to an embodiment of the present application.

[0079] [Figure 11] FIG. 10 is a diagram illustrating performing dimensionality reduction compression on weight data based on TTI according to an embodiment of the present application.

[0080] [Figure 12] FIG. 1 is a diagram of weight data processing according to an embodiment of the present application.

[0081] [Figure 13] FIG. 1 is a diagram of a communication device according to an embodiment of the present application.

[0082] [Figure 14] FIG. 1 is a block diagram of a communication device according to an embodiment of the present application. DETAILED DESCRIPTION OF THE INVENTION

[0083] Before describing the embodiments of the present application, technical terms used in the embodiments of the present application will be explained.

[0084] The fronthaul interface is, for example, an architecture based on a remote radio unit (RRU) / active antenna unit (AAU) and a building baseband unit (BBU). The interface between the RRU / AAU and the BBU is sometimes called the fronthaul interface. For further explanation of the fronthaul interface, see below.

[0085] For example, the fronthaul interface may include one or more of a common public radio interface (CPRI) or an enhanced common public radio interface (eCPRI).

[0086] With the rapid development of communication technology (e.g., 5.5G), air interface access speeds are continuously increasing, and communication networks (also referred to as wireless networks) are evolving toward multiple antennas (e.g., including 128 transmission channels (128T), 128T), multiple streams, and large bandwidths (e.g., 400 megahertz (MHz)). As a result, the bandwidth requirements based on the fronthaul interface are continuously increasing.

[0087] For example, as shown in Figure 1, millimeter wave (mmWave) may support a bandwidth of 800 MHz and a rate of 18 gigabits per second (Gbps). The under 6 GHz (U6GHz) band may support a bandwidth of 200 MHz to 400 MHz and a rate of 9 Gbps. The C-band may support a bandwidth of 100 MHz and a rate of 1.8 Gbps. Frequency division duplex (FDD) bands The area is , may correspond to ~100 MHz and ~1 Gbps, where "~" represents approximately. Ultra-large bandwidth is understood to be the basis for higher rates such as 10 Gbps. Sub100G is fully used to achieve a 10 Gbps experience and improve the user experience rate. The value of the user experience rate may depend on one or more of the bandwidth, the number of streams, or quadrature amplitude modulation (QAM).

[0088] However, the development speed of communication devices may not match the development speed of communication networks, which becomes a bottleneck that restricts the development of communication networks.

[0089] For example, a module configured to implement a fronthaul interface function includes a fronthaul optical module. A baseband signal may be transmitted from a BBU to an AAU / RRU through the fronthaul interface. If the transmission rate of the fronthaul optical module is low, the baseband signal cannot be transmitted to the AAU / RRU at a higher rate. As a result, wireless performance cannot be further improved. Specifically, the fronthaul optical module may become a bottleneck that restricts the development of communication networks.

[0090] For example, the fronthaul interface is eCPRI. With the development of multiple antennas and large bandwidth, the bandwidth of eCPRI is also insufficient. A new communication method needs to be proposed so that the fronthaul interface's capability can support the development of multiple antennas and large bandwidth.

[0091] For example, eCPRI may be re-segmented. However, this method requires significant changes to the hardware architecture of the communication network, which is costly. In addition to eCPRI re-segmentation techniques, solutions that do not change the hardware architecture or only change it slightly may also be studied.

[0092] Specifically, the data in eCPRI mainly includes user data and weight data. As the number of antennas and bandwidth increase, the required bandwidth of eCPRI also increases, and the proportion of weight data in the total data in eCPRI continues to increase (the proportion can approach 80% at most). However, currently, the bandwidth of eCPRI is limited. As a result, eCPRI may not support wireless evolution.

[0093] The user data may be downlink data, for example, data transmitted through the BBU to the RRU / AAU and then transmitted by an antenna to the terminal device over the air interface. Alternatively, the user data may be uplink data, for example, data received by an antenna over the air interface and then transmitted by the RRU / AAU to the BBU.

[0094] The weight data may be a value used for beamforming, and the value may be multiplied with a data portion (such as user data or control data) in a pre-coding phase to form a directional beam to achieve the effect of spatial division multiplexing. The weight data may be pre-configured, configured through an operational interface, estimated based on an uplink reference signal, or calculated based on channel information fed back by a terminal device, but this is not limited thereto.

[0095] For example, as shown in Figure 2, a communication scenario with a fronthaul bandwidth of 128T@200MHz and a large proportion of weight data is used as an example. Regarding weight granularity, when the weight granularity is 4RB, the weight data proportion is approximately 50%. When the weight granularity is 2RB, the weight data proportion is approximately 70%. When the weight granularity is 1RB, the weight data proportion is approximately 80%. In other words, the smaller the weight granularity, the larger the weight data proportion. RB is a resource block. Regarding the number of streams, when the number of streams is 32L, compared to a scenario with 24 streams (24L), both the amount of weight data and the amount of user data increase continuously. In other words, as the number of streams increases, the amount of weight data and the amount of user data increase.

[0096] When the weight granularity is 4RB and the number of streams is 24L, the required switching bandwidth is greater than 50Gbps but less than 100Gbps, and the required eCPRI may be a 100Gbps eCPRI. When the weight granularity is 2RB and the number of streams is 24L, the required switching bandwidth is greater than 100Gbps but less than 150Gbps, and the required eCPRI may be a 150Gbps eCPRI. When the weight granularity is 4RB and the number of streams is 32L, the required switching bandwidth is greater than 100Gbps but less than 150Gbps, and the required eCPRI may be a 150Gbps eCPRI. When the weight granularity is 2RB and the number of streams is 32L, the required switching bandwidth is greater than 150Gbps but less than 200Gbps, and the required eCPRI may be a 200Gbps eCPRI.

[0097] The weight granularity may indicate the number of RBs corresponding to one weight data. For example, 4RBs may indicate that data corresponding to every four RBs is associated with the same weight data.

[0098] However, the development speed of fronthaul optical modules cannot keep up with the development speed of communication networks, so 150Gbps eCPRI or 200Gbps eCPRI may not exist. As a result, communication devices cannot perform high-speed data transmission through eCPRI and cannot meet increasing communication requirements.

[0099] In conclusion, how communication devices can perform data transmission through the fronthaul interface to adapt to the development of communication networks has become an urgent technical problem to be solved.

[0100] To solve the aforementioned technical problems, an embodiment of the present application provides a communication method, in which, after obtaining weight data, a first communication device may perform dimension reduction compression on the weight data to obtain first data, and then transmit the first data, where the weight data is used for beamforming, and the dimension of the weight data is greater than the dimension of the first data.

[0101] In this embodiment of the present application, the amount of weight data is reduced by performing dimension reduction compression on the weight data, which can further reduce the amount of data transmitted by the first communication device through the fronthaul interface and reduce the bandwidth requirements of the fronthaul interface, so that the first communication device can adapt to the evolution of the communication network when performing data transmission through the fronthaul interface.

[0102] The following describes in detail the implementation of the embodiments of the present application with reference to the accompanying drawings herein.

[0103] The communication method provided in the embodiments of the present application may be applied to any communication system, such as a long term evolution (LTE) system, a fifth generation (5G) mobile communication system, a new radio (NR) communication system, or a 3rd generation partnership project (3GPP) communication system, such as a vehicle-to-everything (V2X) system. Alternatively, the communication method may be applied to an LTE and 5G hybrid networking system, or may be applied to a non-terrestrial network (NTN) system, a device-to-device (D2D) communication system, a machine-to-machine (M2M) communication system, the internet of things (IoT), a near field communication (NFC) system, a microwave communication (uWave) system, and another next-generation communication system, e.g., a future communication system such as 6G, or a non-3GPP communication system, e.g., a wireless local area network (WLAN), without being limited thereto.

[0104] It should be noted that the above-mentioned communication systems applicable to the present application are merely examples for explanation, and the communication systems applicable to the present application are not limited thereto. A unified description is provided in this specification. The details will not be described again below.

[0105] In the following, FIG. 3 is used as an example to describe the communication system provided in an embodiment of the present application.

[0106] FIG. 3 is a diagram of a possible, non-limiting system. As shown in FIG. 3, the communication system includes a radio access network (RAN) 100 and a core network (CN) 200. The RAN 100 includes at least one RAN node (e.g., 110a and 110b in FIG. 3; collectively referred to as 110) and at least one terminal device (e.g., 120a-120j in FIG. 3; collectively referred to as 120). The RAN 100 may also include other RAN nodes, such as wireless relay devices and / or wireless backhaul devices (not shown in FIG. 3). The terminal device 120 is wirelessly connected to the RAN node 110. The RAN node 110 is wirelessly or wiredly connected to the core network 200. The core network devices in the core network 200 and the RAN nodes 110 in the RAN 100 may be different physical devices, or may be the same physical device that integrates core network logical functions and radio access network logical functions.

[0107] The RAN 100 may be a cellular system associated with the 3rd generation partnership project (3GPP), such as a 4G or 5G mobile communications system, or a future evolved system (e.g., a 6G mobile communications system). Alternatively, the RAN 100 may be an open access network (open RAN, O-RAN, or ORAN) or a cloud radio access network (CRAN) system. Alternatively, the RAN 100 may be a communications system that integrates two or more of the above systems.

[0108] The RAN node 110, which may also be referred to as an access network device, RAN entity, access node, etc., forms part of a communication system to help terminal devices implement wireless access. The multiple RAN nodes 110 in the communication system 1000 may be the same type of node or different types of nodes. In some scenarios, the roles of the RAN node 110 and the terminal device 120 are relative. For example, the network element 120i in FIG. 3 may be a helicopter or an unmanned aerial vehicle and may be configured as a mobile base station. To the terminal device 120j accessing the RAN 100 through the network element 120i, the network element 120i is a base station. However, to the base station 110a, the network element 120i is a terminal device. The RAN node 110 and the terminal device 120 may also be referred to as communication devices. For example, the network elements 110a and 110b in FIG. 3 may be understood as communication devices having base station functionality, and the network elements 120a to 120j may be understood as communication devices having terminal device functionality.

[0109] In one possible scenario, the RAN node may be a base station, an evolved NodeB (eNodeB), an access point (AP), a transmission reception point (TRP), a next-generation base station (gNB), a next-generation base station in a sixth-generation (6G) mobile communication system, a base station in a future mobile communication system, an access node in a Wi-Fi system, etc. The RAN node may be a macro base station (110a in FIG. 3), a micro base station or an indoor station (110b in FIG. 3), a relay node or a donor node, or a radio controller in a CRAN scenario. Optionally, the RAN node may alternatively be a server, a wearable device, a vehicle, a vehicle-mounted device, etc. For example, the access network device in a vehicle-to-everything (V2X) technology may be a road side unit (RSU).

[0110] In another possible scenario, multiple RAN nodes cooperate to assist terminal devices in implementing radio access, with different RAN nodes separately implementing some base station functions. For example, a RAN node may be a central 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 may be located separately or may be included in the same network element, e.g., a baseband unit (BBU). The RU may be included in a radio frequency device or radio frequency unit, e.g., a remote radio unit (RRU), an active antenna unit (AAU), or a remote radio head (RRH).

[0111] In different systems, the CU (or CU-CP and CU-UP), DU, or RU may also have different names, but those skilled in the art will understand their meanings. For example, in an ORAN system, the CU may be referred to as an O-CU (open CU), the DU may be referred to as an O-DU, the CU-CP may be referred to as an O-CU-CP, the CU-UP may be referred to as an O-CU-UP, and the RU may be referred to as an O-RU. For ease of explanation, the CU, CU-CP, CU-UP, DU, and RU are used as examples for explanation in this application. Any of the CU (or CU-CP or CU-UP), DU, and RU in this application may be implemented by using a software module, a hardware module, or a combination thereof.

[0112] A terminal device may also be referred to as a terminal, user equipment (UE), mobile station, mobile terminal, etc. Terminal devices can be widely used in various scenarios, such as 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, and smart city. Terminal devices may be mobile phones, tablet computers, computers with wireless transceiver functions, wearable devices, vehicles, unmanned aerial vehicles, helicopters, airplanes, ships, robots, robotic arms, smart home devices, etc. The device form of the terminal device is not limited in the embodiments of the present application.

[0113] The communication between the access network device and the terminal device conforms to a specific protocol layer structure. The protocol layers may include a control plane protocol layer and a user plane protocol layer. The control plane protocol layer includes a radio resource control (RRC) layer, a packet data convergence protocol (PDCP) layer, a radio link control (RLC) layer, a medium access control (MEC) layer, and a QoS layer. um The user plane protocol layer may include at least one of a service data adaptation protocol (SDAP) layer, a PDCP layer, an RLC layer, a MAC layer, a physical layer, etc.

[0114] FIG. 4 is a diagram of a radio access network (RAN). As shown in FIG. 4, the access network device includes one or more CUs, one or more DUs, and one or more radio units (RUs). For clarity, FIG. 4 shows only one CU, one DU, and one RU. The CU is configured to connect with a core network and one or more DUs. Optionally, the CU may have some core network functions. The CU may include a CU-CP and a CU-UP.

[0115] The CU and DU may be configured based on the protocol layer functions of the wireless network implemented by the CU and DU. For example, the CU is configured to implement the functions of the PDCP layer and the protocol layers above the PDCP layer (e.g., the RRC layer and / or the SDAP layer), and the DU is configured to implement the functions of the protocol layers below the PDCP layer (e.g., the RLC layer, the MAC layer, and / or the PHY layer). In another example, the CU is configured to implement the functions of the protocol layers above the PDCP layer (e.g., the RRC layer and / or the SDAP layer), and the DU is configured to implement the functions of the PDCP layer and the protocol layers below the PDCP layer (e.g., the RLC layer, the MAC layer, and / or the PHY layer).

[0116] When the CU includes a CU-CP and a CU-UP, the CU-CP is configured to implement the control plane functions of the CU, and the CU-UP is configured to implement the user plane functions of the CU. For example, when the CU is configured to implement the functions of the PDCP layer, the RRC layer, and the SDAP layer, the CU-CP is configured to implement the functions of the RRC layer and the control plane functions of the PDCP layer, and the CU-UP is configured to implement the functions of the SDAP layer and the user plane functions of the PDCP layer.

[0117] The configuration of the CU and DU is merely an example. Alternatively, the functions of the CU and DU may be configured based on requirements. For example, the CU or DU may be configured to have more protocol layer functions, or the CU or DU may be configured to have some processing functions of the protocol layers. For example, some functions of the RLC layer and functions of protocol layers above the RLC layer are configured in the CU, and the remaining functions of the RLC layer and functions of protocol layers below the RLC layer are configured in the DU. In another example, the division of the functions of the CU or DU may be performed based on the service type or another system requirement, for example, based on latency. Functions whose processing time needs to meet a low latency requirement are configured on the DU, and functions whose processing time does not need to meet a low latency requirement are configured on the CU.

[0118] For example, as shown in FIG. 5, the DU and RU may be divided or separated at the PHY layer. The DU and RU may cooperate to jointly implement PHY layer functions. One DU may be connected to one or more RUs. The functions of the DU and RU may be configured in multiple ways based on the design. For example, the DU may be configured to implement baseband functions, and the RU may be configured to implement intermediate radio frequency functions. In another example, the DU may be configured to implement higher layer functions of the PHY layer (or described as implementing H(high)-PHY functions), and the RU may be configured to implement lower layer functions of the PHY layer (or described as implementing L(low)-PHY functions), or may be configured to implement lower layer functions and radio frequency functions. The higher layer functions of the PHY layer may include some of the functions of the PHY layer, which are closer to the MAC layer. The lower layer functions of the PHY layer may include another part of the functions of the PHY layer, which are closer to the intermediate radio frequency side. There are various possible ways to divide the DU and RU. This is not limited to this. There is an interface between the DU and the RU. For example, based on different functions and / or different division schemes of the DU and the RU, the interface between the DU and the RU may be CPRI or eCPRI.

[0119] For example, in one possible design, the H-PHY functions may include one or more of the following: forward error correction (FEC) encoding / decoding, scrambling, or modulation / demodulation. The L-PHY functions may include one or more of the following: fast Fourier transform (FFT) / inverse fast Fourier transform (iFFT), digital beamforming, physical random access channel (PRACH) extraction and filtering, etc. The RU may perform radio frequency signal communication with terminal devices over the air interface via antennas.

[0120] Figure 6 is a diagram of the architecture of an access network device. The access network device includes one or more functional modules configured to perform signal processing. As shown in Figure 6, physical layer functions are used as an example. The access network device includes one or more of the following functions: encoding, rate matching, scrambling, modulation, layer mapping, precoding, resource element (RE) mapping, digital beamforming (BF), inverse fast Fourier transform (IFFT) / cyclic prefix (CP) addition, decoding, rate de-mapping, descrambling, demodulation, inverse discrete Fourier transform (IDFT), channel equalization (or channel estimation), RE de-mapping, digital beamforming, fast Fourier transform (FFT) / CP removal, digital-to-analog (DA) conversion, analog beamforming, analog-to-digital (AD) conversion, or analog beamforming.

[0121] One or more functional modules may be implemented using software, hardware, or a combination of software and hardware. Physically, one or more functional modules may be discrete or integrated. It may be understood that the aforementioned functional modules are merely examples. Based on the design, the access network device may include more modules (e.g., a scheduling module, a power control module, a hybrid automatic repeat request (HARQ) module, a stream control module, a mobility management module, or an artificial intelligence (AI) module) or may not include the specific functional modules shown in FIG. 6 (e.g., not including a digital BF module). The access network device further includes a fronthaul (FH) interface between the DU and the RU to implement communication between the DU and the RU. The fronthaul interface includes, but is not limited to, CPRI or eCPRI. In one possible implementation, the DU is located in the BBU and the RU is located in the RRU / AAU / RRH, and the interface between the BBU and the RRU / AAU / RRH may also be referred to as a fronthaul interface. To implement a fronthaul interface, the BBU and the RRU / AAU / RRH may be connected through a fronthaul network, or the DU and the RU may be connected through a fronthaul network, for example, fronthaul networks include, but are not limited to, fiber direct connect networks and wavelength division multiplexing networks.

[0122] An access network device may support one or more types of fronthaul interfaces, with different fronthaul interfaces corresponding to DUs and RUs with different functions. As shown in Figure 6, when the fronthaul interface between a DU and an RU is CPRI, the DU is configured to implement one or more baseband functions, and the RU is configured to implement one or more radio frequency functions. Compared to CPRI, when the fronthaul interface between a DU and an RU is eCPRI, some downlink and / or uplink baseband functions are moved from the DU to the RU. The division schemes for the DU and the RU are different and correspond to different categories (Cats) of eCPRI.

[0123] Figure 6 shows six examples of eCPRIs, represented by categories A, B, C, D, E, and F (which may also be represented as options A-F, options 1-6, or otherwise). It may be understood that there may be other division schemes between DU and RU, in other words, other categories of eCPRIs.

[0124] eCPRI cat A is used as an example. For downlink transmission, layer mapping is used as the division. The DU is configured to implement layer mapping and one or more previous functions (i.e., one or more of encoding, rate matching, scrambling, modulation, and layer mapping), and other functions after layer mapping (e.g., RE mapping, digital BF, or IFFT / CP addition) are transferred to the RU for implementation. For uplink transmission, RE de-mapping is used as the division. The DU is configured to perform de-mapping and one or more previous functions (i.e., one or more of decoding, rate de-matching, de-scrambling, demodulation, IDFT, channel equalization, and RE de-mapping), and other functions after de-mapping (e.g., one or more of digital BF or FFT / CP removal) are transferred to the RU for implementation.

[0125] Similarly, eCPRI cat B, cat C, cat D, cat E, and cat F correspond to different DU and RU segmentation schemes, respectively. The segmentation point and functions before the segmentation point are implemented by the DU, and functions after the segmentation point are implemented by the RU. For the segmentation points of various categories of eCPRI, please refer to Figure 6. Details will not be explained one by one. For example, for eCPRI cat B, RE mapping is used as the segmentation for downlink transmission, and RE unmapping is used as the segmentation for uplink transmission. For uplink transmission, the RE mapping function and functions before RE mapping are implemented by the DU, and functions after RE mapping and radio frequency functions are implemented by the RU. For downlink transmission, the RE unmapping function and functions before RE unmapping are implemented by the DU, and functions after RE unmapping and radio frequency functions are implemented by the RU.

[0126] The eCPRI partitioning scheme may be symmetric for the uplink and downlink, e.g., eCPRI cat B and cat C shown in FIG. 6. Alternatively, the eCPRI partitioning scheme may be asymmetric for the uplink and downlink, e.g., eCPRI cat A, cat D, cat E, and cat F shown in FIG. 6. This is not limiting. Optionally, different partitioning schemes may be configured for different channels or different channel groups for the uplink and / or downlink, i.e., different categories of eCPRI are configured. A group of channels may include one or more channels.

[0127] In one possible design, the DU is located in the BBU, and the RU is located in the RRU / AAU / RRH. A processing unit configured to implement baseband functions in the BBU is referred to as a baseband high (BBH) unit, and a processing unit configured to implement baseband functions in the RRU / AAU / RRH is referred to as a baseband low (BBL) unit.

[0128] Based on the above description of the access network device, the communication method provided in this embodiment of the present application can be applied to a first communication device side and a second communication device side. For example, the first communication device may include one or more of a BBH, CU, DU, BBU, units below the BBH, etc., or may include software modules, hardware circuits, or software modules and hardware circuits that can be installed in or connected to these modules to implement the method in this embodiment of the present application. This is not limited to this. The second communication device may include one or more of a BBL, RRU, AAU, units below the BBL, etc., or may include software modules, hardware circuits, or software modules and hardware circuits that can be installed in or connected to these modules to implement the method in this embodiment of the present application. This is not limited to this.

[0129] The first communication device and the second communication device in this embodiment of the present application may be one or more chips, and may be referred to as a system on chip. SoC ) etc. It should be noted that FIGS. 3 to 6 are merely examples of the accompanying drawings, and the number of devices included in FIGS. 3 to 6 is not limited. Furthermore, in addition to the devices shown in FIGS. 3 to 6, the communication system may further include other devices. The names of the devices and links in FIGS. 3 to 6 are not limited. In addition to the names shown in FIGS. 3 to 6, the devices and links may have other names. This is not limited.

[0130] During specific implementation, as shown in Figures 3 to 6, for example, both the first communication device and the second communication device may use the configuration structure shown in Figure 7 or may include the components shown in Figure 7. Figure 7 is a configuration diagram of a communication device 700 according to an embodiment of the present application. The communication device 700 may be the first communication device or a chip or system-on-chip in the first communication device, or may be the second communication device or a chip or system-on-chip in the second communication device. As shown in Figure 7, the communication device 700 includes a processor 701, a transceiver 702, and a communication line 703.

[0131] The communications device 700 may also include a memory 704. The processor 701, the memory 704, and the transceiver 702 may be connected via a communications link 703.

[0132] The processor 701 may be a central processing unit (CPU), a general-purpose processor, a network processor (NP), a digital signal processor (DSP), a microprocessor, a microcontroller, a programmable logic device (PLD), or any combination thereof. Alternatively, the processor 701 may be another device having processing capabilities, such as a circuit, a component, or a software module, without limitation.

[0133] The transceiver 702 is configured to communicate with another device or another communication network, which may be an Ethernet, a RAN, a WLAN, etc. The transceiver 702 may be a module, a circuit, a transceiver, or any apparatus capable of implementing communications.

[0134] The communication line 703 is configured to transmit information between the components included in the communication device 700 .

[0135] The memory 704 is configured to store instructions, which may be a computer program.

[0136] Memory 704 may be, without limitation, read-only memory (ROM) or another type of static storage device capable of storing static information and / or instructions; random access memory (RAM) or another type of dynamic storage device capable of storing information and / or instructions; or electrically erasable programmable read-only memory (EEPROM), compact disc read-only memory (CD-ROM) or another compact disc storage, optical disc storage (including compact disc, laser disc, optical disc, digital versatile disc, Blu-ray disc, etc.), magnetic disc storage medium, or another magnetic storage device.

[0137] It should be noted that the memory 704 may exist independently of the processor 701 or may be integrated with the processor 701. The memory 704 may be configured to store instructions, program codes, some data, etc. The memory 704 may be located inside the communication device 700 or outside the communication device 700, without being limited thereto. The processor 701 is configured to execute instructions stored in the memory 704 to implement the communication methods provided in the following embodiments of the present application.

[0138] In one example, processor 701 may include one or more CPUs, for example, CPU 0 and CPU 1 of FIG.

[0139] In some optional implementations, the communications device 700 includes multiple processors. For example, in addition to the processor 701 of FIG.

[0140] In an optional implementation, the communication apparatus 700 further includes an output device 705 and an input device 706. For example, the input device 706 is a device such as a keyboard, a mouse, a microphone, or a joystick, and the output device 705 is a device such as a display or a speaker.

[0141] It should be noted that the communications device 700 may be a desktop computer, a portable computer, a network server, a mobile phone, a tablet computer, a wireless terminal, an embedded device, a chip system, or a device having a structure similar to that of Figure 7. Also, the configuration structure shown in Figure 7 does not constitute a limitation on the communications device. In addition to the components shown in Figure 7, the communications device may include more or fewer components than those shown in the figure, or some components may be combined, or a different component arrangement may be used.

[0142] In this embodiment of the present application, the chip system may include the chip, or may include the chip and other discrete components.

[0143] In addition, actions, terms, etc. in the embodiments of the present application may be cross-referenced. This is not limiting. In the embodiments of the present application, the names of messages exchanged between devices, the names of parameters in messages, etc. are merely examples. Other names may be used instead in a specific implementation. This is not limiting.

[0144] Please refer to Figure 8. The communication method according to the embodiment of the present application will be described with reference to the communication systems shown in Figures 3 to 6 and by using an example in which the first communication device is a BBH and the second communication device is a BBL. Both the BBH and the BBL in the following embodiment may have the components shown in Figure 7. The processing performed by a single execution entity shown in the embodiment of the present application may alternatively be performed by multiple execution entities. These execution entities may be logically and / or physically separated. This is not limited thereto.

[0145] 8 illustrates a communication method according to an embodiment of the present application. As shown in FIG. 8, the method may include the following steps:

[0146] Step 801: The BBH obtains weight data.

[0147] The weight data may be used for beamforming. Alternatively, it may be described as follows: The weight data is a weight calculated by the BBH based on channel information fed back by the terminal device and used for beamforming, a preconfigured weight, a weight configured by operation and maintenance personnel through an operation interface, or a weight estimated by the BBH through measurements of uplink reference signals and used for beamforming. This value may be multiplied by a data portion in a precoding phase to form a directional beam to achieve the effect of spatial division multiplexing. Alternatively, it may be described as follows: The weight data is weight data used to perform a precoding operation on user data.

[0148] For example, the weight data may be determined by using a conventional pre-coding matrix determination method. There is a contradiction inAs shown in FIG. 9, the access network device may receive an uplink reference signal, such as a channel sounding reference signal (SRS), from the terminal device, perform signal measurement / channel estimation on the received SRS to obtain single-user (SU) weights, and perform downlink weight calculation on the SU weights to obtain multi-user / single-user (MU / SU) weight data (also referred to as pre-coding weight data).

[0149] The weight data may be a multidimensional matrix and is related to the number of RBs, the number of antennas, and the number of streams. The weight data has a multiplicative relationship. As the number of antennas and the number of streams increase, the weight data increases synchronously.

[0150] For example, the dimension of the weight data is the number of antennas × the number of streams × the number of RBs. The number of streams can also be described as the number of ports. In other words, the dimension of the weight data is the number of antennas × the number of ports × the number of RBs.

[0151] For example, the fronthaul interface is eCPRI, and the communication scenario is an eCPRI split scenario in which the downlink is split before the pre-coding process based on the format of cat A, cat D, cat E, or cat F shown in Figure 6. In the eCPRI split scenario, weight data may be generated through calculation in the BBH, and data pre-coding is performed in the BBL.

[0152] Step 802: The BBH performs dimension reduction compression on the weight data to obtain first data.

[0153] The dimension of the weight data may be greater than the dimension of the first data.

[0154] Specifically, singular value decomposition (SVD) is performed on the weight data, which reveals that the number of non-zero eigenvalues ​​is the number of streams. If the number of streams is too large, performance will degrade, and the number of streams of weight data is generally less than 50% of the number of antennas, so it can be determined that the weight data has a certain sparsity.

[0155] Since the weight data has certain sparsity and is not encoded and compressed, theoretically there is a large compression space to reduce the data volume of the weight data. Therefore, the dimension of the weight data can be reduced by a dimension reduction compression method to reduce the data volume of the weight data and perform data compression.

[0156] For example, the weight data is calculated in the BBH. After the weight data is calculated in the BBH and before the weight data forms the eCPRI frame, the BBH may perform dimension reduction compression on the weight data to reduce the dimension of the weight data and achieve the purpose of data compression.

[0157] Optionally, as shown in FIG. 9, a dimension reduction compression module (or described as a dimension reduction module) may be added to the BBH to perform dimension reduction compression on the weight data.

[0158] Optionally, if the first condition is met, the BBH performs dimensionality reduction compression on the weight data to obtain first data.

[0159] The first condition may include a first transmission parameter associated with the weight data being greater than or equal to a first preset threshold, or a second transmission parameter associated with the weight data being less than or equal to a second preset threshold. The first transmission parameter may include one or more of a number of streams, a number of antennas, a bandwidth, or a fronthaul load, and the second transmission parameter may include a weight granularity.

[0160] For example, if the first transmission parameter includes the number of streams, the first condition may be that the number of streams associated with the weight data is greater than or equal to a preset stream count threshold (i.e., a first preset threshold). For example, if the first transmission parameter includes the number of antennas, the first condition may be that the number of antennas associated with the weight data is greater than or equal to a preset antenna count threshold (i.e., a first preset threshold). For example, if the first transmission parameter includes bandwidth, the first condition may be that the bandwidth associated with the weight data is greater than or equal to a preset bandwidth threshold (i.e., a first preset threshold). For example, if the first transmission parameter includes fronthaul load, the first condition may be that the fronthaul load associated with the weight data is greater than or equal to a preset fronthaul load threshold (i.e., a first preset threshold). For example, if the second transmission parameter includes weight granularity, the first condition may be that the weight granularity associated with the weight data is less than or equal to a preset weight granularity threshold (i.e., a second preset threshold).

[0161] The first preset threshold and / or the second preset threshold may be preset in a protocol, or may be customized by an access network device such as a BBU or BBH, or may be obtained through calculation, without being limited thereto.

[0162] Optionally, the BBH performs dimensionality reduction compression on the weight data based on a first compression rate to obtain first data.

[0163] For example, the first compression rate may be preset in the protocol, or the first compression rate may be determined by the BBH based on one or more of the following parameters: number of streams, number of antennas, weight granularity, bandwidth, fronthaul load, etc. This is not limited thereto.

[0164] For example, a larger number of streams indicates a higher first compression ratio determined by the BBH based on the number of streams. A larger number of antennas indicates a higher first compression ratio determined by the BBH based on the number of antennas. A smaller weight granularity indicates a higher first compression ratio determined by the BBH based on the weight granularity. A larger bandwidth indicates a higher first compression ratio determined by the BBH based on the bandwidth. A larger fronthaul load indicates a higher first compression ratio determined by the BBH based on the fronthaul load.

[0165] A higher first compression ratio indicates a greater loss of weight data, and a lower first compression ratio indicates a smaller loss of weight data.

[0166] In another example, a fixed first compression ratio may be set, or a fixed data loss may be set, whereby the BBH automatically adjusts the first compression ratio. If the first compression ratio is fixed, the data loss is floating. If the data loss is fixed, the first compression ratio is floating.

[0167] Optionally, the first compression ratio may also be described as a dimensionality reduction depth, a dimensionality reduction compression depth, a dimensionality reduction degree, a dimensionality reduction compression degree, etc. This is not limited thereto.

[0168] Optionally, the difference between the dimension of the weight data and the dimension of the first data may be a first difference, and the absolute value of the difference between the second compression ratio determined based on the first difference and the first compression ratio may be less than or equal to a first threshold.

[0169] The first compression ratio is a required value (also referred to as a reference value, ideal value, etc.) of the compression ratio when the BBH performs dimension reduction compression on the weight data. After the BBH performs dimension reduction compression on the weight data based on the required value and the obtained first data is compared with the weight data, the absolute value of the difference between the actual compression ratio and the required value may be equal to or less than a first threshold. The actual compression ratio may be a second compression ratio.

[0170] Optionally, the BBH performs dimensionality reduction compression on the weight data using one or more of a principal component analysis (PCA) method, a discrete cosine transform (DCT) method, or an autoencoder method to obtain the first data.

[0171] In a first example, the BBH may perform dimensionality reduction compression on the weight data in a PCA manner to obtain first data.

[0172] The main idea of ​​PCA is to map n-dimensional features to k-dimensional features, which can also be called principal components, where n and k are positive integers and n is greater than k.

[0173] For example, the BBH may calculate the covariance matrix of the weight matrix (i.e., weight data), calculate the eigenvalues ​​and eigenvectors of the covariance matrix, and select the matrix containing the first k features with the largest eigenvalues ​​and corresponding eigenvectors as the first data, whereby the weight data can be transformed (or described as projected) into a new space to perform feature dimensionality reduction.

[0174] In a second example, the BBH may perform dimensionality reduction compression on the weight data in a DCT manner to obtain the first data.

[0175] The DCT method can convert spatial domain data into frequency domain data, providing good decorrelation performance. The DCT method has high energy compaction, can aggregate important information in the data, and can directly clip data in unimportant frequency domain areas. A quantization operation is performed on the transformed data, and unimportant coefficients are removed to reduce the data dimension. The DCT method is widely used in image data processing. For example, the DCT method is used for JPEG image compression. The discrete wavelet transform (DWT) algorithm, developed by converting the Fourier base into a wavelet base, is used in JPEG2000 and has better compression performance.

[0176] For example, the BBH may transform the spatial domain data of the weight data into the frequency domain, aggregate important information together, and directly clip the data of the unimportant frequency domain area. In other words, the BBH performs a quantization operation on the transformed weight data, removes unimportant coefficients to obtain first data, thereby achieving the effect of reducing data dimension.

[0177] In a third example, the BBH may perform dimensionality reduction compression on the weight data in an autoencoder manner to obtain the first data.

[0178] An autoencoder is a deep neural network whose input and output are the same, and the amount of data in the hidden layer of the autoencoder is much less than that of the input layer. By using a deep neural network, hidden features in the data can be extracted, and less data can be used to represent the original output, achieving the effect of dimensionality reduction.

[0179] For example, as shown in Figure 10, the autoencoder may be divided into two parts: the encoding (encoder) part is used by the BBH to perform dimension reduction compression on the weight data to obtain first data, and the decoding (decoder) part is used by the BBL to perform dimension restoration on the first data to obtain weight data.

[0180] Based on the foregoing description, when the BBH performs dimension reduction compression on the weight data, if the dimension reduction switch is in an on state, the BBH may perform dimension reduction compression on the weight data to obtain first data. Correspondingly, if the dimension reduction switch is in an off state, the BBH cannot perform dimension reduction compression on the weight data.

[0181] Optionally, the dimension reduction switch is configured in a main control module, which may be located in a BBU, a CU, a DU, etc., but is not limited thereto.

[0182] For example, the main control module may be a universal main processing and transmission unit (UMPT).

[0183] The main control module may decide whether to turn on the dimension reduction switch based on one or more of the following parameters: number of streams, number of antennas, weight granularity, bandwidth, fronthaul load, etc., but this is not limited thereto.

[0184] For example, when the number of streams is large (large number of antennas, small weight granularity, large bandwidth, or high fronthaul load), if the data traffic is about to exceed the capacity of the fronthaul optical module, the dimension reduction switch may be turned on to reduce the data volume and provide more service traffic.

[0185] Optionally, when the dimensionality reduction switch is in an on state, the BBH may perform dimensionality reduction compression on the weight data (or may be described as performing dimensionality reduction compression on the weight data by using a dimensionality reduction compression module) if a first condition is met. If the first condition is not met, the BBH may not perform dimensionality reduction compression on the weight data even if the dimensionality reduction switch is in an on state.

[0186] Optionally, when performing dimension reduction compression on the weight data, as shown in FIG. 11, the BBH may perform dimension reduction compression on the weight data within one transmission time interval (TTI) in units of one TTI to maximize the weight compression effect.

[0187] The TTI is the transmission length for independent decoding on the radio link.

[0188] Step 803: The BBH sends the first data, and the BBL receives the first data correspondingly.

[0189] The BBH may encapsulate the first data in an eCPRI frame and transmit the encapsulated eCPRI frame to the BBL. Upon receiving the encapsulated eCPRI frame, the BBL may perform de-encapsulation to obtain the first data.

[0190] Step 804: The BBL performs dimensionality increasing decompression on the first data to obtain weight data.

[0191] Optionally, the BBL performs dimensionality increasing decompression on the first data based on a first compression ratio to obtain the weight data.

[0192] For a description of the first compression ratio, please refer to the above related description of the first compression ratio, and details will not be described here.

[0193] Optionally, the first compression ratio may be obtained by the BBL through calculation, or may be obtained by the BBH through calculation and sent to the BBL. This is not limited thereto.

[0194] Optionally, when performing dimensionality increasing decompression on the first data, the BBL may perform dimensionality increasing decompression on the first data in a PCA manner to obtain weight data, may perform an inverse DCT transform on the first data in a DCT manner to obtain weight data, or may decode the first data by using a decoder in an autoencoder manner to obtain weight data, as shown in FIG. 10 .

[0195] Optionally, the manner in which the BBH performs dimensionality reduction compression on the weight data is the same as the manner in which the BBL performs dimensionality increase decompression on the first data.

[0196] For example, the manner in which the BBH performs dimensionality reduction compression on the weight data and the manner in which the BBL performs dimensionality increase decompression on the first data may be preset. Alternatively, the BBH may determine the manner in which to perform dimensionality reduction compression on the weight data and indicate the used manner to the BBL, and the BBL will perform dimensionality increase decompression on the first data in that manner.

[0197] Optionally, as shown in FIG. 9, a dimension increasing decompression module (also described as a dimension increasing module) may be added to the BBL to perform dimension increasing decompression on the weight data.

[0198] Optionally, after performing dimensionality increasing decompression on the first data to obtain weight data, the BBL may perform pre-coding based on the weight data to form directional beams to perform beamforming.

[0199] Based on the method shown in FIG. 8, dimension reduction compression is performed on the weight data, thereby reducing the data volume of the weight data. This further reduces the data volume transmitted by the access network device through the fronthaul interface, alleviating the load on the fronthaul interface and reducing the bandwidth requirements of the fronthaul interface. Therefore, more streams, more antennas, or smaller weight granularity can be supported. Given the rate of the fronthaul optical module, higher-spec radio functionality is possible. This reduces the possibility that the fronthaul interface will become a bottleneck in the development of the communication network when the development rate of the fronthaul optical module is slow, thereby allowing the access network device to adapt to the development of the communication network when transmitting data through the fronthaul interface.

[0200] In addition, in this embodiment of the present application, dimensionality reduction compression is performed by using the sparsity of the weight data, which can save fronthaul bandwidth when data loss is small (or described as data loss is controllable, or wireless performance loss is controllable) and implement the level reduction effect of the fronthaul optical module.

[0201] For example, as shown in Figure 2, the weight granularity is 2 RB and the stream is 32L. Dimensionality reduction compression is performed on the weight data, and the required switching bandwidth may be reduced from the original "greater than 150 Gbps and less than 200 Gbps" to "greater than 100 Gbps and less than 150 Gbps", and the required eCPRI is reduced from the original "200 Gbps eCPRI" to "150 Gbps eCPRI", achieving the reduction effect.

[0202] Unlike the dimensionality reduction compression performed on weight data by BBH, BBH also compresses weight data by quantizing it to reduce the number of bits occupied by the weight data, further reducing the amount of data transmitted by access network devices through the fronthaul interface, thereby reducing the load on the fronthaul interface and the bandwidth requirements of the fronthaul interface. Therefore, more streams, more antennas, or smaller weight granularity can be supported. Given the rate of the fronthaul optical module, higher-spec radio functions are enabled. This reduces the possibility that the fronthaul interface will become a bottleneck in the development of the communication network when the development rate of the fronthaul optical module is slow, thereby allowing access network devices to adapt to the development of the communication network when performing data transmission through the fronthaul interface.

[0203] For example, after generating the weight data, the BBH may quantize (also referred to as compress) the weight data. For example, the number of bits occupied by the weight data may be reduced from 16 bits to 8 bits. A quantization compression rate of 50% may be achieved compared with the weight data before quantization. The BBH may transmit the quantized weight data to the BBL. The BBL performs dequantization (also referred to as decompression) on the quantized weight data to obtain the weight data and performs beamforming based on the weight data through a pre-coding process.

[0204] In the above-mentioned method of quantizing weight data, as the amount of bits occupied by weight data (or described as the amount of quantized bits) decreases, data loss increases. In the quantization method, it is difficult to further reduce and compress the amount of bits occupied by weight data.

[0205] Based on this, the above-mentioned method of performing dimensionality reduction compression on weight data can be combined with the above-mentioned method of quantizing weight data to achieve the effect of increasing compression capacity and further improving the compression effect of weight data.

[0206] When compressing the weight data, the BBH may first perform dimension reduction compression on the weight data and then perform quantization, or may first quantize the weight data and then perform dimension reduction compression on the quantized weight data, without being limited thereto.

[0207] For example, the BBH may first perform dimension reduction compression and then quantization on the weight data. The BBH may perform dimension reduction compression on the weight data to obtain first data and quantize the first data to obtain quantized first data. The BBH may send the quantized first data to the BBL. The BBL may dequantize the quantized first data to obtain the first data and perform dimension increase decompression on the first data to obtain the weight data.

[0208] For example, the first compression ratio of the dimension reduction compression is 0.5, and the quantization compression ratio is 0.5. Assume that the dimension of the weight data is N and the amount of occupied bits is 16 bits. As shown in (a) of FIG. 12, after the BBH performs dimension reduction compression on the weight data, the weight data may be compressed from N×16 bits to 0.5N×16 bits. As shown in (b) of FIG. 12, after the BBH quantizes the weight data, the weight data may be compressed from N×16 bits to N×8 bits. As shown in (c) of FIG. 12, after the BBH performs dimension reduction compression and quantization on the weight data, the weight data may be compressed from N×16 bits to 0.5N×8 bits, thereby achieving the effect of doubling the compression capability and further improving the effect of compressing the weight data.

[0209] Optionally, in this application, data is compressed from the data layer of the fronthaul interface instead of the air interface physical layer. The reason why user data is not compressed is because source coding is performed on user data (video, file, encrypted data, etc.). Data redundancy is reduced in the source coding process. The user data is compressed through dimensionality reduction compression. Theoretically, the gain is not large, but compression is not completely impossible. In other words, the above-mentioned processes of dimensionality reduction compression and redundancy removal may be applied to user data to further improve the compression effect of data on the fronthaul interface.

[0210] It should be noted that the methods provided in the embodiments of the present application may be performed separately or in combination, and this is not limited thereto.

[0211] It may be understood that in the embodiments of the present application, an execution entity may perform some or all of the steps in the embodiments of the present application. The steps or operations are merely examples. The embodiments of the present application may further include performing other operations or variations of various operations. Furthermore, the steps may be performed in a different order than presented in the embodiments of the present application, and not all operations in the embodiments of the present application need to be performed.

[0212] The solutions provided in the embodiments of the present application have been described above mainly in terms of interactions between devices. It can be understood that, to implement the aforementioned functions, each device includes a corresponding hardware structure and / or corresponding software module for performing each function. Those skilled in the art will easily recognize that the present application can be implemented by hardware or a combination of hardware and computer software, in combination with the algorithms and steps in the examples described in the embodiments disclosed herein. Whether the functions are performed by hardware or by hardware driven by computer software depends on the specific application and design constraints of the technical solution. Those skilled in the art may use different methods to implement the described functions for each specific application, but such implementations should not be considered to go beyond the scope of the present application.

[0213] In the embodiment of the present application, the device may be divided into functional modules based on the above-mentioned method example. For example, each functional module may be obtained through division based on each corresponding function, or two or more functions may be integrated into one processing module. The integrated module may be implemented in the form of hardware or in the form of a software functional module. It should be noted that in the embodiment of the present application, the module division is an example and is merely a logical functional division. In actual implementation, other division methods may be used.

[0214] When each functional module is obtained through division based on each corresponding function, Fig. 13 shows the communication device 130. The communication device 130 may perform the action performed by the first communication device (e.g., BBH) in Figs. 8 to 12, or may perform the action performed by the second communication device (e.g., BBL) in Figs. 8 to 12. This is not limited thereto.

[0215] The communication device 130 may include a transceiver module 1301 and a processing module 1302. For example, the communication device 130 may be a software module, a hardware circuit, or a combination of a software module and a hardware circuit, or may be a chip used in a communication device, another combined component, or a component having the functionality of the aforementioned communication device. When the communication device 130 is a hardware device, the transceiver module 1301 may be a transceiver. The transceiver may include interface circuits, pins, an antenna, radio frequency circuits, etc. The processing module 1302 may be a processor (or processing circuit), such as a baseband processor. The baseband processor may include one or more CPUs. When the communication device 130 is a component having the functionality of a communication device, the transceiver module 1301 may be a radio frequency unit, and the processing module 1302 may be a processor (or processing circuit), such as a baseband processor. When the communication device 130 is a chip system, the transceiver module 1301 may be an input / output interface of the chip (e.g., a baseband chip), and the processing module 1302 may be a processor (or processing circuit) of the chip system and may include one or more central processing units. It should be understood that the transceiver module 1301 in this embodiment of the present application may be implemented by a transceiver or transceiver-related circuit components, and the processing module 1302 may be implemented by a processor or processor-related circuit components (also referred to as processing circuits).

[0216] For example, transceiver module 1301 may be configured to perform all receive and transmit operations performed by the communications device in the embodiments shown in Figures 8 through 12 and / or may be configured to support other processes of the techniques described herein. Processing module 1302 may be configured to perform all operations other than receive and transmit operations performed by the communications device in the embodiments shown in Figures 8 through 12 and / or may be configured to support other processes of the techniques described herein.

[0217] In another possible implementation, the transceiver module 1301 in Figure 13 may be replaced by a transceiver, and the functionality of the transceiver module 1301 may be integrated into the transceiver. The processing module 1302 may be replaced by a processor, and the functionality of the processing module 1302 may be integrated into the processor. Furthermore, the communication device 130 shown in Figure 13 may further include a memory.

[0218] Alternatively, when the processing module 1302 is replaced with a processor and the transceiver module 1301 is replaced with a transceiver, the communication device 130 in this embodiment of the present application may be the communication device 140 shown in FIG. 14. The processor may be a logic circuit 1401, and the transceiver may be an interface circuit 1402. Furthermore, the communication device 140 shown in FIG. 14 may further include a memory 1403.

[0219] An embodiment of the present application further provides a computer program product, which, when executed by a computer, may implement the functions of any one of the method embodiments described above.

[0220] An embodiment of the present application further provides a computer program, which, when executed by a computer, can implement the functions of any one of the above-described method embodiments.

[0221] Some embodiments of the present application further provide a computer-readable storage medium. All or part of the procedures in the aforementioned method embodiments may be implemented by a computer program that instructs associated hardware. The program may be stored in the aforementioned computer-readable storage medium. When the program is executed, the procedures in the aforementioned method embodiments may be performed. The computer-readable storage medium may be an internal storage unit (including a data transmitting end and / or a data receiving end) in any one of the aforementioned embodiments, such as a hard disk or memory of the terminal. The computer-readable storage medium may also be an external storage device of the aforementioned terminal, such as a plug-in hard disk, a smart media card (SMC), a secure digital (SD) card, or a flash card configured on the terminal. Furthermore, the computer-readable storage medium may include both an internal storage unit and an external storage device of the terminal. The computer-readable storage medium is configured to store the computer program as well as other programs and data required by the terminal. The computer-readable storage medium may further be configured to temporarily store output data or data to be output.

[0222] It should be noted that in the specification, claims, and accompanying drawings of this application, terms such as "first," "second," etc. are intended to distinguish between different objects and do not indicate a particular order. Furthermore, the terms "comprise" and "have," as well as any other variations thereof, are intended to cover a non-exclusive inclusion. 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, and may optionally further include unlisted steps or units, or may optionally further include other inherent steps or units of the process, method, product, or device.

[0223] As used herein, "at least one item" means one or more, "multiple" means two or more, "at least two items" means two, three, or more, and "and / or" is used to describe an association relationship between related entities and indicates that a three-way relationship is possible. For example, "A and / or B" may indicate that only A is present, only B is present, or both A and B are present, where A and B may be singular or plural. The symbol " / " generally indicates an "or" relationship between related entities. "At least one of the listed items" or similar expressions refers to any combination of these items, including a singular item or any combination of multiple items. For example, "at least one of a, b, or c" may refer to a, b, c, a and b, a and c, b and c, or a, b, and c, where a, b, and c may be singular or plural.

[0224] The above description of the implementation allows those skilled in the art to understand that for the purpose of simple description, the division of the above functional modules is taken as an example for explanation. In actual application, the above functions can be allocated to different functional modules and implemented based on requirements, that is, the internal structure of the device is divided into different functional modules to implement all or part of the above functions.

[0225] In some embodiments provided herein, it should be understood that the disclosed devices and methods may be implemented in other ways. For example, the device embodiments described are merely examples. For example, the division into modules or units is merely a logical division of function, and other divisions may be used in actual implementation. For example, multiple units or components may be combined or integrated into another device, or some features may be omitted or not implemented. In addition, the shown or discussed mutual couplings or direct couplings or communication connections may be implemented through some interfaces. Indirect couplings or communication connections between devices or units may be implemented electronically, mechanically, or in other ways.

[0226] The units described as separate parts may or may not be physically separate, and the parts shown as units may be one or more physical units, located in one place or distributed in different places. Some or all of the units may be selected based on actual requirements to achieve the objectives of the solutions of the embodiments.

[0227] In addition, the functional units in the embodiments of the present application may be integrated into one processing unit, each of the units may exist physically alone, or two or more units may be integrated into one unit. The integrated unit may be implemented in the form of hardware or in the form of a software functional unit.

[0228] When an integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, the integrated unit may be stored in a readable storage medium. Based on this understanding, the technical solutions in the embodiments of the present application may be essentially, or all or part of, the technical solutions may be implemented in the form of a software product. The software product is stored in a storage medium and includes several instructions for instructing a device (which may be a single-chip microcomputer, a chip, etc.) or a processor to perform all or part of the steps of the method described in the embodiments of the present application. The aforementioned storage medium includes any medium capable of storing program code, such as a USB flash drive, a removable hard disk, a ROM, a RAM, a magnetic disk, or an optical disk.

Claims

1. 1. A method of communication comprising: obtaining weight data, the weight data being used for beamforming; performing dimension reduction compression on the weight data to obtain first data, wherein the dimension of the weight data is greater than the dimension of the first data; transmitting the first data; method.

2. Performing dimensionality reduction compression on the weight data to obtain first data includes: performing dimensionality reduction compression on the weight data to obtain the first data when a first condition is satisfied, the first condition including a first transmission parameter associated with the weight data being equal to or greater than a first preset threshold or a second transmission parameter associated with the weight data being equal to or less than a second preset threshold, the first transmission parameter including one or more of a number of streams, a number of antennas, a bandwidth, or a fronthaul load, and the second transmission parameter including a weight granularity; The method of claim 1.

3. Performing dimensionality reduction compression on the weight data to obtain first data includes: performing dimensionality reduction compression on the weight data based on a first compression ratio to obtain the first data; The method according to claim 1 or 2.

4. the first compression ratio is preset; or The first compression ratio is determined based on one or more of the following parameters: number of streams, number of antennas, weight granularity, bandwidth, or fronthaul load. The method of claim 3.

5. Performing dimensionality reduction compression on the weight data to obtain first data includes: performing dimension reduction compression on the weight data using one or more methods of a principal component analysis (PCA) method, a discrete cosine transform (DCT) method, or an autoencoder method to obtain the first data; 5. The method according to any one of claims 1 to 4.

6. Transmitting the first data includes: quantizing the first data to obtain quantized first data; transmitting the quantized first data.

6. The method according to any one of claims 1 to 5.

7. 1. A method of communication comprising: acquiring first data; performing dimensionality increasing decompression on the first data to obtain weight data, the weight data being used for beamforming, and the dimension of the weight data being greater than the dimension of the first data; A method comprising:

8. Performing dimensionality increasing decompression on the first data to obtain weight data comprises: performing dimensionality increasing decompression on the first data based on a first compression ratio to obtain the weight data; The method of claim 7.

9. the first compression ratio is preset; or the first compression ratio is determined based on one or more parameters of a number of streams, a number of antennas, a weight granularity, a bandwidth, or a fronthaul load. The method of claim 8.

10. Performing dimensionality increasing decompression on the first data to obtain weight data comprises: performing dimension increasing decompression on the first data using one or more of a principal component analysis (PCA) method, a discrete cosine transform (DCT) method, or an autoencoder method to obtain the weight data; 10. The method according to any one of claims 7 to 9.

11. Obtaining the first data includes: receiving quantized first data; dequantizing the quantized first data to obtain the first data.

11. The method according to any one of claims 7 to 10.

12. 1. A communications device comprising: a transceiver module configured to obtain weight data, the weight data being used for beamforming; a processing module configured to perform dimensionality reduction compression on the weight data to obtain first data, wherein a dimension of the weight data is greater than a dimension of the first data; the transceiver module is further configured to transmit the first data. Device.

13. The processing module specifically: and configured to perform dimension reduction compression on the weight data to obtain the first data when a first condition is satisfied, the first condition including a first transmission parameter associated with the weight data being equal to or greater than a first preset threshold or a second transmission parameter associated with the weight data being equal to or less than a second preset threshold, the first transmission parameter including one or more of a number of streams, a number of antennas, a bandwidth, or a fronthaul load, and the second transmission parameter including a weight granularity.

13. The apparatus of claim 12.

14. The processing module specifically: configured to perform dimensionality reduction compression on the weight data based on a first compression ratio to obtain the first data; 14. Apparatus according to claim 12 or 13.

15. the first compression ratio is preset; or the first compression ratio is determined based on one or more parameters of a number of streams, a number of antennas, a weight granularity, a bandwidth, or a fronthaul load.

15. The apparatus of claim 14.

16. The processing module specifically: The method is configured to perform dimension reduction compression on the weight data using one or more methods of a principal component analysis (PCA) method, a discrete cosine transform (DCT) method, or an autoencoder method to obtain the first data.

16. Apparatus according to any one of claims 12 to 15.

17. the processing module is further configured to quantize bits occupied by the first data to obtain quantized first data; the transceiver module is further configured to transmit the quantized first data.

17. Apparatus according to any one of claims 12 to 16.

18. 1. A communications device comprising: a transceiver module configured to acquire first data; a processing module configured to perform dimensionality increasing decompression on the first data to obtain weight data, the weight data being used for beamforming, and a dimension of the weight data being greater than a dimension of the first data; and An apparatus having:

19. The processing module specifically: configured to perform dimensionality increasing decompression on the first data based on a first compression ratio to obtain the weight data; 20. The apparatus of claim 18.

20. the first compression ratio is preset; or the first compression ratio is determined based on one or more parameters of a number of streams, a number of antennas, a weight granularity, a bandwidth, or a fronthaul load.

20. The apparatus of claim 19.

21. The processing module specifically: configured to perform dimension increasing decompression on the first data using one or more methods of a principal component analysis (PCA) method, a discrete cosine transform (DCT) method, or an autoencoder method to obtain the weight data; 21. Apparatus according to any one of claims 18 to 20.

22. The transceiver module is further configured to receive quantized first data; the processing module is further configured to dequantize the quantized first data to obtain the first data.

22. Apparatus according to any one of claims 18 to 21.

23. A communication device, the communication device comprising a processor, the processor coupled to a memory, the processor configured to perform the communication method of any one of claims 1 to 6.

24. 12. A communication device, the communication device comprising a processor, the processor coupled to a memory, the processor configured to perform the communication method of any one of claims 7 to 11.

25. 12. A computer-readable storage medium storing computer instructions or programs, the computer-readable storage medium storing computer instructions or programs that, when executed on a computer, perform the communication method according to any one of claims 1 to 6 or perform the communication method according to any one of claims 7 to 11.

26. A computer program product, the computer program product including computer instructions, which, when part or all of the computer instructions are executed on a computer, perform the communication method according to any one of claims 1 to 6 or perform the communication method according to any one of claims 7 to 11.

27. A communication system comprising a communication device according to any one of claims 12 to 17 and 23 and a communication device according to any one of claims 18 to 22 and 24.

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