Data transmission method and apparatus

Abstract

Disclosed in the present application are a data transmission method and apparatus. The method comprises: a transmitter device generating and transmitting first signaling, which comprises information of a base matrix, indication information of the base matrix, information of a compression coefficient matrix, and indication information of the compression coefficient matrix, wherein the base matrix comprises at least one base vector, the base vector corresponds to a first vector in an original data matrix, second vectors in the original data matrix other than the first vector form a non-base matrix, and the base matrix performs data compression on the non-base matrix to obtain the compression coefficient matrix; and a receiver device receiving the first signaling, and obtaining the original data matrix on the basis of the first signaling. The present application provides a method for reducing the overheads of dictionary data transmission during dictionary compression, and proposes how to perform standardized transmission on data and information generated during the process of the method, thereby ensuring the reliability of a data decompression process.

Description

Data transmission method and apparatus

[0001] This application claims priority to Chinese Patent Application No. 202510183449.4, filed on February 19, 2025, entitled "Data Transmission Method and Apparatus", the entire contents of which are incorporated herein by reference. Technical Field

[0002] This application relates to the field of communication technology, and in particular to a data transmission method and apparatus. Background Technology

[0003] With the increasing demand for communication services, massive data transmission consumes more transmission resources. To reduce resource consumption and improve transmission efficiency, data compression technology has been proposed. Dictionary compression is a typical data compression technique. Simply put, dictionary compression transforms the original data matrix using a dictionary to obtain a transformed matrix. A portion of the data in the transformed matrix is ​​transmitted as compressed data to the receiving device, while the remaining data, consisting of zero elements or extremely small values ​​close to zero, is not transmitted. This reduces the amount of data transmitted, achieving the effect of reducing transmission resource consumption.

[0004] The problem with existing technologies is that dictionaries are additional data that needs to be transmitted besides compressed data, requiring extra transmission resources. Furthermore, there is no proposed standardization or instruction for the transmission of related data or information during the dictionary compression process. This results in high transmission resource consumption, and the reliability of the receiving device in decompressing the compressed data to obtain the original data cannot be guaranteed. Summary of the Invention

[0005] This application provides a data transmission method and apparatus, which provides a method to reduce the overhead of transmitting dictionary data during dictionary compression, and proposes a method for standardizing the transmission of data and information generated during the process, thereby ensuring the reliability of the data decompression process.

[0006] In a first aspect, this application provides a data transmission method, the method comprising: generating a first signaling, the first signaling including information of a basis matrix, indication information of the basis matrix, information of a compression coefficient matrix, and indication information of the compression coefficient matrix; wherein, the basis matrix includes at least one basis vector, the basis vectors corresponding to a first vector in the original data matrix, a second vector in the original data matrix other than the first vector forming a non-basis matrix, and the basis matrix compressing the non-basis matrix to obtain a compression coefficient matrix; the information of the basis matrix includes the values ​​of the basis vectors and the positions of the first vectors corresponding to the basis vectors in the original data matrix, the indication information of the basis matrix includes attribute information of the basis matrix, the information of the compression coefficient matrix includes the second element value and the position of the second element value in the compression coefficient matrix, the indication information of the compression coefficient matrix includes attribute information of the compression coefficient matrix, and the second element value is a non-zero element value; and sending the first signaling.

[0007] The above method can be applied to a first communication device, which can be a network device or a terminal device, or a module (such as a chip system) in a network device or terminal device, or a logical node, logical module, or software that can realize all or part of the functions of a network device or terminal device. There are no limitations on this.

[0008] The first signaling generated by the transmitting device includes information about the basis matrix, its indication, the compression coefficient matrix, and the positions of the basis vectors in the original data matrix. After this information is sent to the receiving device, the receiving device determines the data, size, zero values, and non-zero values ​​of both the basis matrix and the compression coefficient matrix. This allows the receiving device to determine the non-basis matrix based on the basis and compression coefficient matrices. Then, by combining this information with the positions of the basis vectors in the original data matrix, the basis and non-basis matrices are concatenated to obtain the original data matrix. This process reduces the resource consumption of the transmitting device while ensuring the accuracy of the compressed data information obtained by the receiving device, thus guaranteeing the reliability of decompressing the data to obtain the original data matrix.

[0009] In one feasible implementation, the first signaling is carried in a Media Access Control-Control Element (MAC CE) or in Radio Resource Control (RRC) signaling.

[0010] Sending the first signaling via MAC CE or RRC signaling ensures the reliability of the transmission process.

[0011] In one feasible implementation, the correlation between any two first vectors is less than a preset correlation; and / or the correlation between the second vector and at least one first vector is greater than or equal to the preset correlation.

[0012] In one feasible implementation, the indication information of the basis matrix includes basis matrix indication information and / or basis matrix size indication information, wherein the basis matrix indication information is used to indicate that the current information is basis matrix information, and the basis matrix size indication information is used to indicate the size of the basis matrix.

[0013] In one feasible implementation, the basis matrix includes at least one basis vector, which corresponds to a first vector in the original data matrix, including: the basis vector in the basis matrix is ​​the first vector, and the element value of the basis vector is the original data; or the basis vector in the basis matrix is ​​the quantization vector of the first vector, and the element value of the basis vector is the first quantization value.

[0014] In one feasible implementation, when the basis vectors in the basis matrix are the quantization vectors of the first vector, the indication information of the basis matrix further includes at least one of the following: the index of the first quantization value, the quantization bit corresponding to the maximum value of the first quantization value, and the quantization bit corresponding to the minimum value of the first quantization value.

[0015] Using the index of the first quantization value to represent the element value in the basis vector can reduce the memory space occupied by compressed data, thereby improving compression efficiency.

[0016] By indicating relevant information about the first quantization value, the receiving device can decompress the basis vector represented by the first quantization value, thus avoiding incorrect identification of the index of the first quantization value.

[0017] In one feasible implementation, the indication information of the compression coefficient matrix includes compression coefficient indication information and / or compression coefficient matrix size indication information, wherein the compression coefficient matrix indication information is used to indicate that the current information is compression coefficient information, and the compression coefficient matrix size indication information is used to indicate the size of the compression coefficient matrix.

[0018] In one feasible implementation, the first quantization value is the one with the smallest absolute difference between the element values ​​of the basis vector and the multiple quantization values ​​corresponding to the basis matrix.

[0019] This implementation method can reduce the amount of information loss in compressed data.

[0020] In one feasible implementation, the multiple quantization values ​​corresponding to the basis matrix are determined based on the maximum and minimum element values ​​of the basis matrix.

[0021] This implementation method can reduce the number of quantization quantities generated, thereby reducing quantization complexity.

[0022] In one feasible implementation, the second element value is the second quantization value, which is the value obtained by mapping the third element value in the compression coefficient matrix, and the third element value is greater than a preset threshold.

[0023] In one feasible implementation, the information of the basis matrix includes a first bitmap, wherein a first value or a second value in the first bitmap is used to indicate the position of the first vector corresponding to the basis vector in the original data matrix.

[0024] In one feasible implementation, the information in the compression coefficient matrix includes a second bitmap, where a first or second value in the second bitmap is used to indicate the position of the second element value in the compressed data matrix.

[0025] In one feasible implementation, the indication information of the base matrix further includes the size of the first bitmap; and / or the indication information of the compression coefficient matrix further includes the size of the second bitmap.

[0026] In one feasible implementation, the indication information of the compression coefficient matrix also includes a bitmap conversion method, which is used to characterize the sorting method used when the second bitmap is converted into the second bit sequence. The sorting method includes row sorting or column sorting.

[0027] Representing the second bitmap as a second bit sequence reduces the overhead of transmitting the second bitmap. Indicating the sorting method helps the receiving device reconstruct the second bitmap from the second bit sequence, thereby enabling the receiving device to determine the specific position of the second element value in the compression coefficient matrix.

[0028] In one feasible implementation, the first signaling also includes first information, which indicates the business data type of the original data matrix.

[0029] In one feasible implementation, the business data type includes at least one of the following: scatter plot, multipath information, location information, and artificial intelligence (AI) feature data.

[0030] By indicating the type of business data used for compressed data, the receiving device can determine which business to apply the compressed data to, thereby improving data processing efficiency.

[0031] In one feasible implementation, when the first signaling is carried in the MAC CE, the first information is carried in the logical channel identifier LCID or the extended logical channel identifier eLCID field in the MAC header.

[0032] In one feasible implementation, the first signaling also includes second information, which indicates the number A of the original data matrices.

[0033] The first signaling includes information about A base matrices, indication information of the base matrices, information about the compression coefficient matrix, indication information of the compression coefficient matrix, and the number of segments A. After obtaining the number of segments A, the receiving device can decompress the A compression coefficient matrices to obtain A raw data matrices, and then concatenate the A raw data matrices to obtain the concatenated raw data (text). This further ensures the efficiency and accuracy of the data decompression process.

[0034] Secondly, this application provides a data transmission method. The method includes: receiving a first signaling message, the first signaling message including information about a basis matrix, indication information about the basis matrix, information about a compression coefficient matrix, and indication information about the compression coefficient matrix; wherein the basis matrix includes at least one basis vector, the basis vectors corresponding to a first vector in the original data matrix, and a second vector in the original data matrix other than the first vector forming a non-basis matrix; the basis matrix compresses the non-basis matrix to obtain a compression coefficient matrix; the information about the basis matrix includes the values ​​of the basis vectors and the positions of the corresponding first vectors in the original data matrix; the indication information about the basis matrix includes attribute information about the basis matrix; the information about the compression coefficient matrix includes the values ​​of the second elements and the positions of the second element values ​​in the compression coefficient matrix; the indication information about the compression coefficient matrix includes attribute information about the compression coefficient matrix; and the second element value is a non-zero element value; and obtaining the original data matrix based on the first signaling message.

[0035] The above method can be applied to a second communication device. The first communication device can be a network device or a terminal device, or a module (such as a chip system) within a network device or terminal device. It can also be a logical node, logical module, or software capable of implementing all or part of the functions of a network device or terminal device. No limitation is imposed in this regard.

[0036] In one feasible implementation, the first signaling further includes second information, which indicates the number A of the original data matrices. The method further includes concatenating the A original data matrices according to the second information in the first signaling to obtain the original data text.

[0037] Thirdly, a communication device is provided, which includes units or modules for performing the possible methods in either the first or second aspect described above.

[0038] Fourthly, embodiments of this application provide a communication device, the communication device including at least one processor coupled to a memory; wherein the at least one processor is configured to execute a computer program or instructions stored in the memory, such that the methods that may be implemented in either the first or second aspect described above are executed.

[0039] Fifthly, embodiments of this application provide a communication system, which includes a first communication device and a second communication device, wherein the first communication device is used to perform the method described in any one of the first aspects, and the second communication device is used to perform the method described in any one of the second aspects.

[0040] Sixthly, embodiments of this application provide a computer-readable storage medium storing computer instructions that, when executed, cause the computer to perform the method described in any of the above methods.

[0041] In a seventh aspect, embodiments of this application provide a computer program product, the computer program product comprising: computer program code, which, when executed by a computer, causes the computer to perform the method described in any of the above methods.

[0042] Eighthly, embodiments of this application provide a chip coupled to a memory for reading and executing program instructions in the memory, so that the device in which the chip is located implements the method described in any of the above methods. Attached Figure Description

[0043] The accompanying drawings used in the embodiments of this application are described below.

[0044] Figure 1A is a schematic diagram of the architecture of the communication system used in the embodiments of this application.

[0045] Figure 1B is a schematic diagram of the architecture of another communication system provided in an embodiment of this application.

[0046] Figure 2 is a flowchart of a data transmission method provided in an embodiment of this application.

[0047] Figure 3A is a schematic diagram of the spatial projection relationship between a vector and a basis matrix provided in an embodiment of this application.

[0048] Figure 3B is a schematic diagram of a dictionary conversion provided in an embodiment of this application.

[0049] Figure 3C is a schematic diagram of a coefficient selection provided in an embodiment of this application.

[0050] Figure 4A is a schematic diagram of a MAC CE format provided in an embodiment of this application.

[0051] Figure 4B is a schematic diagram of the R / LCID header in a UL MAC PDU provided in an embodiment of this application.

[0052] Figure 4C is a schematic diagram of the format of a MAC CE carrying first signaling provided in an embodiment of this application.

[0053] Figure 4D is a detailed schematic diagram of the format of a MAC CE carrying first signaling provided in an embodiment of this application.

[0054] Figure 4E is a schematic diagram of another detailed format of the MAC CE carrying the first signaling provided in the embodiment of this application.

[0055] Figure 5A is a schematic diagram of another method and MAC CE constituting the first signaling provided in the embodiment of this application.

[0056] Figure 5B is a schematic diagram of another method provided in the embodiments of this application, in which the MAC CE constitutes the first signaling.

[0057] Figure 6A is a schematic diagram of carrying first signaling in RRC signaling according to an embodiment of this application.

[0058] Figure 6B is a schematic diagram of another method of carrying first signaling in RRC signaling according to an embodiment of this application.

[0059] Figure 6C shows an RRC data format for indicating different business data types provided in an embodiment of this application.

[0060] Figure 7 is a schematic diagram of the structure of a communication device provided in an embodiment of this application.

[0061] Figure 8 is a schematic diagram of another communication device provided in an embodiment of this application. Detailed Implementation

[0062] The technical solutions in the embodiments of this application will be described below with reference to the accompanying drawings. The terms "system" and "network" in the embodiments of this application can be used interchangeably. Unless otherwise stated, " / " indicates that the objects before and after are in an "or" relationship; for example, A / B can represent A or B. "And / or" in this application is merely a description of the relationship between related objects, indicating that three relationships can exist. For example, A and / or B can represent: A alone, A and B simultaneously, and B alone, where A and B can be singular or plural. Furthermore, in the description of this application, unless otherwise stated, "multiple" refers to two or more. "At least one of the following" or similar expressions refer to any combination of these items, including any combination of single or plural items. For example, at least one of a, b, or c can represent: a, b, c, ab, ac, bc, or abc, where a, b, and c can be one or multiple. Furthermore, to facilitate a clear description of the technical solutions in the embodiments of this application, the terms "first" and "second" are used in the embodiments of this application to distinguish between network elements and similar items with essentially the same function. Those skilled in the art will understand that the terms "first" and "second" do not limit the quantity or execution order, and that the terms "first" and "second" are not necessarily different.

[0063] References to "one embodiment" or "some embodiments" in the embodiments described in this application mean that one or more embodiments of this application include a specific feature, structure, or characteristic described in connection with that embodiment. Therefore, the phrases "in one embodiment," "in some embodiments," "in other embodiments," "in still other embodiments," etc., appearing in different parts of this specification do not necessarily refer to the same embodiment, but rather mean "one or more, but not all, embodiments," unless otherwise specifically emphasized. The terms "comprising," "including," "having," and variations thereof mean "including but not limited to," unless otherwise specifically emphasized.

[0064] Furthermore, in the embodiments of this application, the words "exemplary," "for example," etc., are used to indicate that they are examples, illustrations, or descriptions. Any embodiment or design scheme described as "exemplary" in this application should not be construed as being more preferred or advantageous than other embodiments or design schemes. Specifically, the use of the term "exemplary" is intended to present the concept in a concrete manner.

[0065] In the embodiments of this application, the terms "information," "signal," "message," "channel," and "singaling" may sometimes be used interchangeably. It should be noted that, without emphasizing their distinction, their intended meanings are consistent. Similarly, "of," "corresponding (relevant)," and "corresponding" may sometimes be used interchangeably. It should be noted that, without emphasizing their distinction, their intended meanings are consistent. Furthermore, the " / " mentioned in this application can be used to indicate an "or" relationship.

[0066] The following detailed embodiments further illustrate the objectives, technical solutions, and beneficial effects of this application. It should be understood that the following are merely specific embodiments of this application and are not intended to limit the scope of protection of this application. Any modifications, equivalent substitutions, improvements, etc., made based on the technical solutions of this application should be included within the scope of protection of this application.

[0067] In the various embodiments of this application, unless otherwise specified or in case of logical conflict, the terminology and / or descriptions of different embodiments are consistent and can be referenced by each other. The technical features of different embodiments can be combined to form new embodiments according to their inherent logical relationship.

[0068] The system architecture involved in the embodiments of this application is described below.

[0069] Figure 1A is a schematic diagram of the architecture of the communication system 1000 used in an embodiment of this application. As shown in Figure 1A, the communication system includes a wireless access network 100 and a core network 200. Optionally, the communication system 1000 may also include the Internet 300. The wireless access network 100 may include at least one network device (110a and 110b in Figure 1A) and at least one terminal device (120a-120j in Figure 1A). The terminal device is wirelessly connected to the network device, and the network device is wirelessly or wired connected to the core network. The core network device and the network device may be independent physical devices, or the functions of the core network device and the logical functions of the network device may be integrated on the same physical device, or a single physical device may integrate some of the functions of the core network device and some of the functions of the network device. Terminal devices and network devices can be interconnected via wired or wireless means. Figure 1A is only a schematic diagram; the communication system may also include other network devices, such as wireless relay devices and wireless backhaul devices, which are not shown in Figure 1A.

[0070] Optionally, in practical applications, the wireless communication system may simultaneously include one or more network devices (also known as access network devices) and one or more terminal devices. A network device may simultaneously serve one or more terminal devices. A terminal device may also simultaneously access one or more network devices. This application embodiment does not limit the number of terminal devices and network devices included in the wireless communication system.

[0071] In this context, a network device can be an entity on the network side used to transmit or receive signals. A network device can also be an access device that allows terminal devices to wirelessly connect to the wireless communication system; for example, a network device can be a base station. Base stations can broadly encompass various names listed below, or be interchangeable with them, such as: radio access network (RAN) node, Node B, evolved Node B (eNB), next-generation Node B (gNB), access network equipment in open radio access network (O-RAN), relay station, access point, transmitting and receiving point (TRP), transmitting point (TP), master eNB (MeNB), secondary eNB (SeNB), multi-standard radio (MSR) node, home base station, network controller, access node, wireless node, access point (AP), transmission node, transceiver node, building baseband unit (BBU), remote radio unit (RRU), active antenna unit (AAU), remote radio head (RRH), centralized unit (CU), and distributed unit (CU). Network equipment includes units (DU), radio units (RU), centralized unit control plane (CU-CP) nodes, centralized unit user plane (CU-UP) nodes, positioning nodes, etc. Base stations can be macro base stations, micro base stations, relay nodes, donor nodes, or similar entities, or combinations thereof. Network equipment can also refer to communication modules, modems, or chips installed within the aforementioned equipment or devices. Network equipment can also be mobile switching centers and equipment that performs base station functions in device-to-device (D2D), vehicle-to-everything (V2X), and machine-to-machine (M2M) communications; network-side equipment in 6G networks; and equipment performing base station functions in future communication systems. Network equipment can support networks using the same or different access technologies.The embodiments of this application do not limit the specific technology or device form used in the network device.

[0072] Network devices can be fixed or mobile. For example, base stations 110a and 110b are stationary and are responsible for wireless transmission and reception in one or more cells from terminal device 120. The helicopter or drone 120i shown in Figure 1A can be configured to act as a mobile base station, and one or more cells can move depending on the location of the mobile base station 120i. In other examples, the helicopter or drone (120i) can be configured as a terminal device communicating with base station 110b.

[0073] In this application, the communication device used to implement the above-mentioned network access functions can be an access network device, a network device with some access network functions, or a device capable of supporting the implementation of access network functions, such as a chip system, hardware circuit, software module, or hardware circuit plus software module. This device can be installed in the access network device or used in conjunction with the access network device. In the method of this application, the example of an access network device being used as the communication device to implement the access network device functions is described.

[0074] A terminal device can be a user-side entity used to receive or transmit signals, such as a mobile phone. Terminal devices can be used to connect people, things, and machines. They can communicate with one or more core networks via network devices. Terminal devices include handheld devices with wireless connectivity, other processing devices connected to a wireless modem, or vehicle-mounted devices. Terminal devices can be portable, pocket-sized, handheld, computer-embedded, or vehicle-mounted mobile devices. Terminal devices can be widely used in various scenarios, such as cellular communication, D2D, V2X, point-to-point (P2P), machine-to-machine (M2M), machine-type communication (MTC), Internet of Things (IoT), virtual reality (VR), augmented reality (AR), industrial control, autonomous driving, telemedicine, smart grids, smart furniture, smart offices, smart wearables, smart transportation, smart cities, drones, robots, remote sensing, passive sensing, positioning, navigation, autonomous delivery, and mobility.Examples of terminal devices include: user equipment (UE) conforming to the 3rd Generation Partnership Project (3GPP) standard, fixed equipment, mobile equipment, handheld devices, wearable devices, cellular phones, smartphones, session initiated protocol (SIP) phones, laptops, personal computers, smart books, vehicles, satellites, global positioning system (GPS) devices, drones, helicopters, aircraft, ships, remote control devices, smart home devices, industrial equipment, personal communication service (PCS) phones, wireless local loop (WLL) stations, personal digital assistants (PDAs), wireless network cameras, tablets, handheld computers, mobile internet devices (MIDs), wearable devices such as smartwatches, VR devices, AR devices, wireless terminals in industrial control, terminals in vehicle-to-everything (V2X) systems, wireless terminals in self-driving vehicles, wireless terminals in smart grids, wireless terminals in transportation safety, and smart city applications. Wireless terminals in various scenarios include smart gas pumps, high-speed rail terminals, and smart home terminals such as smart speakers, smart coffee machines, and smart printers. Terminal devices can be wireless devices in these scenarios or devices installed on wireless devices, such as communication modules, modems, or chips. Terminal devices can also be called terminals, user equipment (UE), mobile stations (MS), mobile terminals (MT), etc. Terminal devices can also be used in future wireless communication systems. Terminal devices can be used in dedicated network equipment or general-purpose equipment. The embodiments of this application do not limit the specific technologies or device forms used in the terminal devices.

[0075] Optionally, the terminal device can be used to act as a base station. For example, the UE can act as a scheduling entity, providing sidelink signaling between UEs in V2X, D2D, or P2P, etc. As shown in Figure 1A, cellular phone 120a and car 120b communicate with each other using sidelink signaling. Cellular phone 120a communicates with smart home device 120e without relaying communication signals through base station 110b.

[0076] In this application, the communication device used to implement the functions of the terminal device can be a terminal device, a terminal device having some of the functions of the aforementioned terminal device, or a device capable of supporting the implementation of the functions of the aforementioned terminal device, such as a chip system. This device can be installed in the terminal device or used in conjunction with the terminal device. In this application, the chip system can be composed of chips or include chips and other discrete components. The technical solutions provided in this application are described using the example of a terminal device or UE as the communication device.

[0077] Optionally, wireless communication systems typically consist of cells, with base stations providing cell management and sending signals to one or more mobile stations within the cell.

[0078] A mobile station (MS) provides communication services. A base station includes a baseband unit (BBU) and a remote radio unit (RRU). The BBU and RRU can be located in different locations; for example, the RRU can be deployed remotely to a high-traffic area, while the BBU is located in a central equipment room. Alternatively, the BBU and RRU can be located in the same equipment room. The BBU and RRU can also be different components within the same rack. Optionally, a cell can correspond to one carrier or a member carrier.

[0079] In some deployments, the network devices mentioned in the embodiments of this application may be devices including CU, DU, or CU and DU, or devices with control plane CU nodes (central unit-control plane (CU-CP)) and user plane CU nodes (central unit-user plane (CU-UP)) and DU nodes. For example, the network devices may include gNB-CU-CP, gNB-CU-UP, and gNB-DU.

[0080] In some deployments, one or more RAN nodes collaborate to assist terminals in achieving wireless access, with different RAN nodes each implementing some of the base station's functions. For example, RAN nodes can be CUs, DUs, CU-CPs, CU-UPs, or RUs. CUs and DUs can be configured separately or included in the same network element, such as a BBU. RUs can be included in radio frequency equipment or radio frequency units, such as RRUs, AAUs, or RRHs.

[0081] In different systems, CU (or CU-CP and CU-UP), DU, or RU may have different names, but those skilled in the art will understand their meaning. For example, in an ORAN system, CU can also be called O-CU (open CU), DU can also be called O-DU, CU-CP can also be called O-CU-CP, CU-UP can also be called O-CU-UP, and RU can also be called O-RU. Any of the units among CU (or CU-CP, CU-UP), DU, and RU in this application can be implemented through software modules, hardware modules, or a combination of software modules and hardware modules.

[0082] In this embodiment, the apparatus for implementing the functions of a network device can be a network device itself; it can also be an apparatus capable of supporting the network device in implementing those functions, such as a chip system, hardware circuit, software module, or a hardware circuit plus a software module. This apparatus can be installed in the network device or used in conjunction with the network device. In this embodiment, the example of a network device being used to implement the functions of a network device is provided only and does not constitute a limitation on the solutions described in this embodiment.

[0083] It is understood that this application can be used in communication between network devices and terminal devices.

[0084] Communication between network devices and terminal devices follows a specific protocol layer structure. This protocol layer structure can include a control plane protocol layer structure and a user plane protocol layer structure. For example, the control plane protocol layer structure can include the functions of protocol layers such as the radio resource control (RRC) layer, the packet data convergence protocol (PDCP) layer, the radio link control (RLC) layer, the medium access control (MAC) layer, and the physical layer. Similarly, the user plane protocol layer structure can include the functions of protocol layers such as the PDCP layer, the RLC layer, the MAC layer, and the physical layer. In one possible implementation, a service data adaptation protocol (SDAP) layer can be included above the PDCP layer.

[0085] Optionally, the protocol layer structure between network devices and terminal devices may also include an artificial intelligence (AI) layer for transmitting AI-related data.

[0086] Taking data transmission between network devices and terminal devices as an example, data transmission needs to pass through user plane protocol layers, such as the SDAP layer, PDCP layer, RLC layer, MAC layer, and physical layer. The SDAP layer, PDCP layer, RLC layer, MAC layer, and physical layer can also be collectively referred to as the access layer. Based on the direction of data transmission, it is divided into sending and receiving; each of these layers is further divided into a sending part and a receiving part. Taking downlink data transmission as an example, after the PDCP layer obtains data from the upper layer, it transmits the data to the RLC layer and MAC layer. The MAC layer then generates a transport block, and finally, it is wirelessly transmitted through the physical layer. Data is encapsulated in corresponding ways at each layer. For example, data received by a layer from the upper layer is considered a Service Data Unit (SDU) of that layer. After encapsulation by that layer, it becomes a Protocol Data Unit (PDU) and is then passed to the next layer.

[0087] For example, the terminal device may also have an application layer and a non-access layer. The application layer can be used to provide services to applications installed on the terminal device. For instance, downlink data received by the terminal device can be sequentially transmitted from the physical layer to the application layer, and then provided to the application by the application layer. Alternatively, the application layer can acquire data generated by the application and sequentially transmit the data to the physical layer for transmission to other communication devices. The non-access layer can be used to forward user data, such as forwarding uplink data received from the application layer to the SDAP layer, or forwarding downlink data received from the SDAP layer to the application layer.

[0088] It should be understood that the number and type of each device in the communication system shown in Figure 1A are for illustrative purposes only, and this application is not limited thereto. In actual applications, the communication system may include more terminal devices, more access network devices, and other network elements, such as core network devices and / or network elements used to implement artificial intelligence functions.

[0089] It is understandable that all or part of the functions implemented by one or more of the terminal devices, access network devices, core network devices, or network elements used to implement artificial intelligence functions can be virtualized, that is, implemented through one or more of dedicated or general-purpose processors and corresponding software modules. Among these, the terminal devices and access network devices involve air interface transmission, and the transmit and receive functions of this interface can be implemented in hardware. Core network devices, such as operation administration and maintenance (OAM) network elements, can also be virtualized. Optionally, one or more of the functions of the virtualized terminal devices, access network devices, core network devices, or network elements used to implement artificial intelligence functions can be implemented by cloud devices, such as cloud devices in over-the-top (OTT) systems.

[0090] Alternatively, refer to Figure 1B, which is a schematic diagram of another communication system architecture provided in an embodiment of this application. This communication system may include at least one transmitting device and at least one receiving device. The transmitting device may be the terminal device described in Figure 1A above, and correspondingly, the receiving device is a network device. Alternatively, the transmitting device may be a terminal device, and correspondingly, the receiving device may be a terminal device. Alternatively, the transmitting device may be a network device, and correspondingly, the receiving device may be a network device.

[0091] Terminal devices typically contain a communication module that performs the corresponding communication functions, or a chip within the terminal device responsible for communication functions, such as a modem chip (also known as a baseband chip), or a system-on-a-chip (SoC) chip or system-in-a-package (SIP) chip that includes a modem module. The terminal device also contains program instructions for performing the corresponding communication functions.

[0092] In some embodiments, the terminal device may also be a device or module that is connected to the communication system shown above and has corresponding communication functions. The terminal device typically contains a communication module, circuit, or chip that performs the corresponding communication functions, and the terminal device is also configured with program instructions for performing the corresponding communication functions.

[0093] The functions of network devices can be executed by modules (such as chips) within the network device, or by a control subsystem that includes network device functions. This control subsystem can be a control center in application scenarios such as smart grids, industrial control, intelligent transportation, and smart cities. Similarly, the functions of terminal devices can be executed by modules (such as chips, modems, application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or software (such as program code in memory) within the terminal device, or by a device that includes terminal device functions; there are no restrictions on this.

[0094] The prior art of the embodiments of this application is described below.

[0095] Dictionary compression technology: Dictionary compression transforms the original data matrix using a dictionary to obtain a transformed matrix. A dictionary is a basis matrix composed of several basis vectors, where each row or column is a basis vector. Projecting the vectors in the original data matrix onto these basis vectors results in sparse coefficients, meaning the transformed matrix is ​​sparse. Only the non-zero coefficients of the transformed matrix are transmitted, thus reducing the amount of data transmitted compared to directly transmitting the original data, thereby achieving data compression. The dictionary can be predefined or obtained from the data to be compressed.

[0096] This process may specifically include the following steps:

[0097] 1. Data Preprocessing: Arrange the elements of the initial data to be transmitted into a matrix. Compress and transmit the matrix, or a subset of its rows and columns, as raw data (segments). The initial data may be floating-point data, complex numbers, or randomly arranged data. Different rows (columns) in the matrix may correspond to the numbers before and after the decimal point in floating-point data, or the real or imaginary part of complex numbers, or data arranged according to a certain rule. In some cases, the initial data itself is a matrix arranged according to a certain rule, meaning this step is optional.

[0098] 2. Dictionary transformation: Performing a dictionary transformation on the data involves multiplying the data matrix on the left by a dictionary (in matrix form) to obtain a sparse matrix called the coefficient matrix.

[0099] 3. Coefficient Selection: In the coefficient matrix, select the values ​​with relatively large absolute values ​​for the corresponding coefficients. Coefficients with relatively small absolute values ​​can be uniformly quantized as zero coefficients.

[0100] 4. Coefficient Quantization: Quantize the selected coefficients. Transmit the quantized coefficients as compressed data.

[0101] In the implementation of the aforementioned dictionary compression technology, the sending device transmits compressed data and needs to indicate information such as the compressed data, the compression dictionary, relevant data from the data generation process, the format of the compressed data or related data, and the space occupied, so that the receiving device can decompress the compressed data based on the relevant information. Existing technologies do not provide standardized definitions for the transmission and indication of this information.

[0102] Example 1: Based on the above description, please refer to Figure 2, which is a flowchart of a data transmission method provided in this application embodiment. As shown in Figure 2, the method includes the following steps:

[0103] 201. The transmitting device generates a first signaling message, which includes information about a basis matrix, indication information about the basis matrix, information about a compression coefficient matrix, and indication information about the compression coefficient matrix. The basis matrix includes at least one basis vector, which corresponds to a first vector in the original data matrix. Second vectors in the original data matrix, excluding the first vector, form a non-basis matrix. The basis matrix compresses the non-basis matrix to obtain the compression coefficient matrix. The information about the basis matrix includes the values ​​of the basis vectors and the positions of the corresponding first vectors in the original data matrix. The indication information about the basis matrix includes attribute information about the basis matrix. The information about the compression coefficient matrix includes the values ​​of the second elements and their positions in the compression coefficient matrix. The indication information about the compression coefficient matrix includes attribute information about the compression coefficient matrix, and the second element value is a non-zero element value.

[0104] In this application's embodiments, the transmitting device refers to a device that needs to transmit data. For example, it can be a terminal device, a network device, or a core network element. This application's embodiments do not impose any limitations on this.

[0105] In this embodiment of the application, it is assumed that the original data matrix to be sent by the sending device is as follows: Select a first vector from these vectors, for example, columns 1 and 4. Obtain the basis matrix based on the selected first vector. The vectors in the basis matrix can be called basis vectors. The basis matrix is ​​multiplied by the non-basis matrix (formed as a dictionary) with the second vector (excluding the first vector) from the original matrix to obtain the compression coefficient matrix. In this example, the non-basis matrix... Assuming the compression coefficient matrix Then T = B × X1. Since the (compressed) dictionary is selected from the original data matrix, there is no need to acquire or transmit dictionary data separately, which reduces the transmission cost of dictionary data.

[0106] Furthermore, due to the low correlation between the basis matrix and the non-basis matrix, the compression coefficient matrix T obtained after multiplying them contains elements (including zero elements) with values ​​less than a preset threshold. These elements can be mapped to 0. Other elements greater than the preset threshold are considered the second element value. For example, assuming a13, a22, and a24 in the compression coefficient matrix T are less than the preset threshold, then the compression coefficient matrix... When the sending device transmits data, it only needs to transmit the second element of the compression coefficient matrix T, and does not need to transmit the zero element. Therefore, the amount of data transmitted by the sending device is less than the actual amount of data that needs to be transmitted in the original data matrix, achieving the effect of data compression.

[0107] The basis vectors, corresponding to the first vector in the original data matrix, have two meanings:

[0108] (1) The basis vectors in the basis matrix are the first vectors.

[0109] In other words, the first vector selected from the original data matrix directly forms the basis matrix.

[0110] Corresponding to the example above, that is

[0111] (2) The basis vectors in the basis matrix are the quantization vectors of the first vector, and the element values ​​of the basis vectors are the first quantization values.

[0112] For example, the chosen basis vectors are (This embodiment uses column vectors as an example; however, basis vectors can also be row vectors, and this application does not limit this.) The basis vectors are quantized. Assume the maximum value of the non-zero elements in the basis vectors is b11 = 3.9, and the minimum value is b24 = 0.9. Quantization values ​​between 0.9 and 3.9 include 1, 2, 3, and 4. Optionally, the first quantization value corresponding to each original data can be the one with the smallest absolute difference from the original data among the multiple quantization values ​​corresponding to the basis vector. Then b11 maps to 4, b24 maps to 1, b21 maps to 1, and b14 maps to 2. Quantization vector

[0113] The quantization values ​​between 0.9 and 3.9 mentioned above, which are 1, 2, 3, and 4 (with quantization values ​​set with 1 as the interval), are just examples. The corresponding quantization values ​​can also be 1, 1.5, 2, 2.5, 3, 3.5, and 4 (with quantization values ​​set with 0.5 as the interval). This application does not limit the specific values.

[0114] Optionally, the settings for the quantization value and the interval between quantization values ​​can allow each raw data point to be mapped to a value between the maximum and minimum values. For example, The maximum value is 2.7, and the minimum value is 1.4. The quantization values ​​between the maximum and minimum values ​​include 1.4, 1.6, 1.8, 2, 2.2, 2.4, and 2.6. Therefore, 1.4 is mapped to 1.4, and 2.7 is mapped to 2.6.

[0115] In this method, the element values ​​in the first vector are quantized into the first quantized value, which increases the number of repeated values ​​in the basis matrix (or increases the redundancy). As a result, less information can be used to represent the repeated values ​​(for example, b11, b11, b11 can be represented as 3 b11), which can reduce the resource overhead of transmitting the basis matrix.

[0116] Optionally, the first element value can be represented by the index of the first quantized value.

[0117] For example, the first element in the base matrix is ​​the first quantized value, and its corresponding index is... Where M-1 is the number of the first quantization values. This represents the index of the l-th first quantized value. Assuming b11 is quantized to 4, it is the 4th first quantized value corresponding to the basis matrix B (M=4), meaning the index of the first quantized value corresponding to b11 is... Then the information of the basis matrix corresponding to b11 can be represented as follows:

[0118] Understandably, the transmitting device will also send the correspondence between the first quantized value and the index of the first quantized value to the receiving device, so that the receiving device can obtain the corresponding first quantized value after obtaining the index of the first quantized value.

[0119] Furthermore, since minimum values ​​(including zero) less than a preset threshold can be omitted and only their positions in the base matrix are indicated, the first element value can represent only the elements in the base matrix greater than the preset value. Therefore, quantization is performed only on these elements.

[0120] Since the first quantization value may be a relatively large value (occupying a large amount of memory space), while the index of the first quantization value is a smaller value (occupying a small amount of memory space), using the index of the first quantization value to represent the first quantization value (or the first element value) in the basis matrix can reduce the memory space occupied by the first element value, thereby improving compression efficiency.

[0121] Optionally, the information of the basis matrix includes a first bitmap, where a first value or a second value is used to indicate the position of the first vector corresponding to the basis vector in the original data matrix.

[0122] The first and second values ​​in the first bitmap are different values ​​in the bitmap and can be used to represent different meanings. For example, the first value is "0" and the second value is "1". "0" represents the second vector at that position, and "1" represents the first vector at that position. Therefore, assuming the first bitmap is 011001, it means that the second, third, and sixth columns of the original data matrix are the first vectors (selected as basis vectors, or quantized as basis vectors), and the first, fourth, and fifth columns are the second vectors. Alternatively, the first and second values ​​can be opposite, or the meanings represented by "0" and "1" can be opposite; this application does not limit this.

[0123] Using the first bitmap to represent the position of the first vector in the basis matrix can reduce the complexity of representing the position of the basis vector, reduce the occupation of transmission resources, and thus improve transmission efficiency.

[0124] The first signaling also includes indication information of the basis matrix, which may specifically include attribute information of the basis matrix.

[0125] Optionally, the indication information of the basis matrix includes basis matrix indication information and / or basis matrix size indication information, wherein the basis matrix indication information is used to indicate that the current information is basis matrix information, and the basis matrix size indication information is used to indicate the size of the basis matrix.

[0126] Specifically, the basis matrix indicator information is "11", indicating that the currently transmitted data is the element value of the basis matrix, and the first bit map transmitted is the position information of the basis vector in the basis matrix. The size indicator information of the basis matrix is ​​P×Q, indicating that the basis matrix is ​​a matrix with P rows and Q columns.

[0127] In this embodiment, the base matrix indication information indicates that the current information is base matrix information, so that the receiving device can obtain the base matrix data. The base matrix size indication information indicates the size of the base matrix, so that the receiving device can obtain a base matrix of the corresponding size and fill the matrix of the corresponding size with the first element value.

[0128] Optionally, when the basis matrix is ​​composed of quantization vectors, the indication information of the basis matrix may further include at least one of the following: the index of the first quantization value, the quantization bit corresponding to the maximum value of the first quantization value, and the quantization bit corresponding to the minimum value of the first quantization value.

[0129] As described above, the first element in the base matrix can be the first quantization value. This first quantization value can be indicated by its index, combined with the correspondence between the first quantization value and its index. Therefore, the indication information of the base matrix can also include the index of the first quantization value. For example, in the aforementioned base matrix B, the corresponding first quantization values ​​include 1, 2, 3, and 4, a total of four values, and the index of the first quantization value is M = 4. The correspondence between the maximum value L1 of the first quantization value and the quantization bit T can be... For example, if the maximum value of the first quantization value is 4, the number of quantization bits occupied is... Bits. The correspondence between the minimum value S1 of the first quantization and the quantization bits T can also be: For example, the minimum value of the first quantization is 1, and the number of quantization bits occupied is... Bit.

[0130] In this embodiment of the application, by indicating the relevant information of the first quantization value, the receiving device can restore the basis matrix represented by the first quantization value, thereby avoiding incorrect identification of the index of the first quantization value.

[0131] Optionally, the indication information of the base matrix may also include the size of the first bitmap.

[0132] When indicating the position of the first element value in the base matrix through the first bit map, the size of the first bit map can also be indicated. For example, if the size of the original data matrix is ​​P×Q, the size indication information of the first bit map is 1×Q, which means that the first bit map is a matrix with 1 row and Q columns, or a vector with Q element values.

[0133] It should be noted that since the base matrix and the first bitmap have corresponding sizes (same number of columns, and fixed at 1 row), the base matrix indication information may or may not include the size indication information of the first bitmap. In other words, if the compression coefficient matrix indication information includes the size indication information of the first bitmap, the size indication information of the base matrix may not be included.

[0134] In the examples above, the first vector is a row vector in the original data matrix. Understandably, the first vector corresponding to the basis vectors can also be a row vector in the original data matrix; this is not a limitation.

[0135] The first signaling also includes information about the compression coefficient matrix and its indication. The compression coefficient matrix information includes the second element value and its position within the base matrix. For example, if the compression coefficient matrix information is {a12, [1,2]}, it means that the second element value in the first row and second column of the compression coefficient matrix is ​​a12. The second element value is a non-zero value, or a value greater than a preset threshold. Elements in the compression coefficient matrix less than the preset threshold can be mapped to zero and do not need to be transmitted.

[0136] Furthermore, assuming the basis matrix is ​​B, the non-basis matrix is ​​X1, and the compression coefficient matrix is ​​T, where T = B × X1. The second element value can be the product element obtained by multiplying the element values ​​of the basis matrix and the non-basis matrix, or it can be the second quantized value obtained by quantizing the product element.

[0137] Similar to the process of quantizing the first element value to obtain the first quantized value described in the previous example, after the second element value is quantized into the second quantized value, the redundancy of the compression coefficient matrix is ​​increased. As a result, less information can be used to characterize the repeated values ​​in the compression coefficient matrix, which can reduce the resource overhead of transmitting the compression coefficient matrix.

[0138] Alternatively, the value of the second element can be represented by the index of the second quantization value.

[0139] For example, the second element in the compression coefficient matrix is ​​the second quantization value, and its corresponding index is... Where N-1 is the number of the second quantization values. This represents the index of the l-th second quantization value. Assuming a12 is quantized to 4, it is the 5th second quantization value corresponding to the compression coefficient matrix T (N=5), meaning the index of the second quantization value corresponding to a12 is... Then the information of the compression coefficient matrix corresponding to a12 can be represented as follows:

[0140] Understandably, the transmitting device will also send the correspondence between the second quantized value and the index of the second quantized value to the receiving device, so that the receiving device can obtain the corresponding second quantized value after obtaining the index of the second quantized value.

[0141] Since the second quantization value may be a relatively large value (occupying a large amount of memory space), while the index of the second quantization value is a smaller value (occupying a small amount of memory space), using the index of the second quantization value to represent the second quantization value (or the second element value) in the basis matrix can reduce the memory space occupied by the second element value, thereby improving compression efficiency.

[0142] Optionally, the first signaling includes a second bitmap, which includes a first value or a second value, and the position of the second element value in the compression coefficient matrix is ​​represented by the position of the first value or the second value in the second bitmap.

[0143] Similar to the aforementioned description of the first bitmap, the first and second values ​​in the second bitmap are different values ​​in the bitmap and can be used to represent different meanings. For example, the first value is "0" and the second value is "1". "0" represents a zero element at that position, and "1" represents a second element value with a non-zero value at that position. Alternatively, the first and second values ​​can be opposite, or "0" and "1" can represent opposite meanings; this application does not limit this. For example, the second bitmap... If the sending device transmits the second element value sequence 1, 3, 2, 4, 2 (if the second element value is zero, it does not need to be transmitted again in the second element value sequence), then, if the second element value sequence is arranged in rows, 1 is located in the first row and first column of the base matrix, 3 is located in the first row and second column of the base matrix, 2 is located in the first row and fourth column of the base matrix, and so on. If the first element value sequence is arranged in columns, then 1 is located in the first row and first column of the base matrix, 3 is located in the second row and first column of the base matrix, and so on.

[0144] Using a second bitmap to represent the position of the second element value in the base matrix can reduce the complexity of representing the position of the second element value, reduce the occupation of transmission resources, and thus improve transmission efficiency.

[0145] The first signaling also includes indication information of the compression coefficient matrix, which may specifically include attribute information of the compression coefficient matrix.

[0146] Optionally, the indication information of the compression coefficient matrix includes compression coefficient indication information and / or compression coefficient matrix size indication information, wherein the compression coefficient indication information is used to indicate that the current information is compression coefficient information, and the compression coefficient matrix size indication information is used to indicate the size of the compression coefficient matrix.

[0147] Specifically, the compression coefficient matrix indicator information is "00", indicating that the currently transmitted data is the second element value corresponding to the compression coefficient matrix, and the transmitted second bitmap is the position information of the second element value in the compression coefficient matrix. The size indicator information of the compression coefficient matrix is ​​I×J, indicating that the compression coefficient matrix is ​​an I-row, J-column matrix.

[0148] In this embodiment, the compression coefficient matrix indication information indicates that the current information is a compression coefficient matrix, so that the receiving device can obtain the data of the compression coefficient matrix. The compression coefficient matrix size indication information indicates the size of the compression coefficient matrix, so that the receiving device can obtain a compression coefficient matrix of the corresponding size and fill the matrix of the corresponding size with the second element value.

[0149] Optionally, when the compression coefficient matrix is ​​composed of quantization vectors, the indication information of the compression coefficient matrix may further include at least one of the following: the index of the second quantization value, the quantization bit corresponding to the maximum value of the second quantization value, and the quantization bit corresponding to the minimum value of the second quantization value.

[0150] As described above, the second element value in the compression coefficient matrix can be the second quantization value. The second quantization value can be indicated by its index, combined with the correspondence between the second quantization value and its index. Therefore, the indication information of the compression coefficient matrix can also include the index of the second quantization value. For example, in the aforementioned compression coefficient matrix T, the corresponding second quantization value includes N values, and the index of the second quantization value is N. The correspondence between the maximum value L2 of the second quantization value and the quantization bit T can be... The correspondence between the minimum value S2 of the second quantization and the quantization bits T can also be:

[0151] In this embodiment of the application, by indicating the relevant information of the second quantization value, the receiving device can restore the compression coefficient matrix represented by the second quantization value, thereby avoiding incorrect identification of the index of the second quantization value.

[0152] Optionally, the indication information of the compression coefficient matrix also includes the size of the second bitmap.

[0153] When indicating the position of the second element value in the compression coefficient matrix through the second bitmap, the size of the second bitmap can also be indicated. For example, if the size indication information of the second bitmap is P×J, it means that the second bitmap is a matrix with P rows and J columns.

[0154] It should be noted that since the compression coefficient matrix and the second bitmap have corresponding (or the same) sizes, the compression coefficient matrix indication information may or may not include the size indication information of the second bitmap. In other words, if the compression coefficient matrix indication information includes the size indication information of the second bitmap, it may not include the size indication information of the compression coefficient matrix.

[0155] Optionally, the second bitmap is represented as a second bit sequence, and the indication information of the compression coefficient matrix also includes bitmap conversion indication information. The bitmap conversion indication information is used to indicate the sorting method used when the second bitmap is converted into the second bit sequence. The sorting method includes row sorting or column sorting.

[0156] As described above, the position of the second element value in the compression coefficient matrix can be represented as a second bitmap. To reduce transmission resource consumption, the transmitting device can represent the second bitmap as a second bit sequence for transmission. The bitmap is converted to a bit sequence, which can be sorted by row. For example, the elements in the second bitmap Bit2, sorted by row, are: 11011010. Alternatively, they can be sorted by column. For example, the elements in the second bitmap Bit2, sorted by column, are: 11100110. The indication information in the compression coefficient matrix can indicate whether the second bitmap was sorted by row or by column when converted to the second bit sequence.

[0157] In this embodiment, representing the second bitmap as a second bit sequence reduces the overhead of transmission resources for sending the second bitmap. The indication of the sorting method helps the receiving device reconstruct the second bit sequence from the second bitmap, thereby enabling the receiving device to determine the specific position of the compressed data in the compression coefficient matrix.

[0158] Optionally, the information indicating the compression coefficient matrix may also include the size of the second bit sequence.

[0159] Since the second bit sequence is a sequence, it is usually 1×P*J in size, where P*J is the sequence length and 1 represents a row.

[0160] Optionally, the second bit sequence is a plurality of split second sub-bit sequences (or second bit vectors), each second sub-bit sequence representing the bit sequence of each row or column vector in the compression coefficient matrix. For example, if the second bit sequence is 11011010 (sorted by row), it can also be represented by second sub-bit sequence 1 = 1101 (bit sequence of the first row vector) and second sub-bit sequence 2 = 1010 (bit sequence of the second row vector). The receiving device determines whether each row vector in the compression coefficient matrix corresponds to a non-zero second element value based on each second sub-bit sequence.

[0161] Optionally, the second bitmap includes QJ second bit vectors of length J. Here, Q is the number of columns in the original data matrix, and J is the number of columns (or elements) of the basis vectors. J is also the number of rows (or elements) of the second bit vectors.

[0162] Optionally, the second bitmap includes QJ bits of length K. i The second bit vector of K. i ≤J, 1≤i≤QJ. Specifically, when only one basis vector is selected as the dictionary to compress one or more second vectors, the length of the obtained second bit vector is K. i =1; When all J basis vectors in the basis matrix are used as a dictionary to compress certain second bit vectors, the length of the resulting second bit vector is K. i =J. That is to say, the length of the second bit vector depends on the number of basis vectors used as the dictionary.

[0163] The first signaling may also include the position of the second vector (a vector in a non-basis matrix) in the original data matrix.

[0164] The position of the second vector in the original data matrix can be indicated directly, or indirectly by indicating the position of the first vector corresponding to the basis matrix in the original data matrix.

[0165] For example, in the aforementioned example, the first signaling can indicate the first vector in the first column and the first vector in the fourth column of the original data matrix X corresponding to the basis matrix B. The receiving device can infer the second vector in the second, third, fifth and sixth columns of the original data matrix corresponding to the non-basis matrix based on this information; or the first signaling can indicate the second vector in the second, third, fifth and sixth columns of the original data matrix corresponding to the non-basis matrix.

[0166] Based on the above description, when sending the first signaling, the sending device can send the information shown in Table 1 below:

[0167] Table 1

[0168] As shown in Table 1, the information of the base matrix under each number corresponds to the indicator information of the base matrix under that number. Similarly, the information of the compression coefficient matrix with the same number corresponds to the indicator information of the compression coefficient matrix.

[0169] Optionally, the first signaling may also include indication information regarding the business data type of the compressed data.

[0170] The business data type of compressed data refers to the type of business-related data the compressed data (or the corresponding original data) belongs to. For example, business data types include at least one of the following: scatter plots, multipath information, location information, artificial intelligence (AI) feature data, etc. Indicating the business data type of compressed data helps the receiving device determine which business application to use that compressed data for, thereby improving data processing efficiency.

[0171] 202. The sending device sends the first signaling. Correspondingly, the receiving device receives the first signaling.

[0172] Optionally, the first signaling is carried in a medium access control-control element (MAC CE) or in radio resource control (RRC) signaling.

[0173] The sending device sends a MAC CE or RRC signaling (including uplink RRC or downlink RRC), and the receiving device receives the signaling and obtains the compressed data information and compressed data indication information contained therein.

[0174] 203. The receiving device obtains the original data matrix based on the first signaling.

[0175] After receiving the first signaling, the receiving device obtains the base matrix and compression coefficient matrix, and decompresses the data according to the indication information of the base matrix and the compression coefficient matrix to obtain the original data matrix.

[0176] Optionally, the first signaling also includes segmentation indication information, which indicates the number T of segments corresponding to the original data. After obtaining the number T of segments, the receiving device concatenates the T original data segments to obtain the concatenated original data text.

[0177] Specifically, the compressed data information and compression data indication information included in the first signaling are not for a single data segment, but for multiple data segments. That is, the information included in the first signaling is shown in Table 2 below:

[0178] Table 2

[0179] As shown in Table 2, the first signaling includes information about R basis matrices, information about the compression coefficient matrix, indication information of the basis matrices, indication information of the compression coefficient matrix, and the number of segments A. After obtaining the number of segments A, the receiving device can decompress the data based on the basis matrices and the compression coefficient matrix to obtain R non-basis matrices, and then obtain R original data matrices. These R original data matrices are then concatenated to obtain the concatenated original data (text). This further ensures the efficiency and accuracy of the data decompression process.

[0180] As can be seen, in this embodiment, the generated first signaling includes information about the basis matrix, the indication information of the basis matrix, the information about the compression coefficient matrix, the indication information of the compression coefficient matrix, and the positions of the basis vectors in the original data matrix. After this information is sent to the receiving device, the receiving device determines the data, size, zero values, and non-zero values ​​of the basis matrix and the compression coefficient matrix, respectively. This allows the receiving device to determine the non-basis matrix based on the basis matrix and the compression coefficient matrix, and then, combined with the positions of the basis vectors in the original data matrix, concatenate the basis matrix and the non-basis matrix to finally obtain the original data matrix. This process reduces the resource consumption of the sending device in transmitting data and ensures the accuracy of the compressed data information obtained by the receiving device, thereby ensuring the reliability of obtaining the original data matrix by decompressing the data based on the compressed data information.

[0181] Example 2: This example describes in detail the data compression process performed by the sending device.

[0182] In the above data transmission method, the core steps of data compression at the sending end device include the following four steps: 1) Data splitting (splitting the vectors in the original data matrix into basis matrices or non-basis matrices); 2) Dictionary transformation (multiplying the basis matrix as a dictionary with the non-basis matrix to obtain the compression coefficient matrix); 3) Coefficient selection (obtaining the non-zero element values ​​in the compression coefficient matrix); 4) Quantization (coefficients & / dictionary) (quantizing the non-zero element values ​​in the basis matrix or compression coefficient matrix).

[0183] 1) Data splitting

[0184] Optionally, the correlation between the basis vectors and the basis matrix is ​​less than a preset correlation; and / or the correlation between the non-basis vectors and the basis matrix is ​​greater than or equal to the preset correlation.

[0185] In the process of splitting the original data matrix, assume that the basis matrix composed of the already determined basis vectors is D, and the transpose of D is Di. T Find a vector x in the original data matrix. i The correlation with the basis matrix is ​​determined by the following method: x i The correlation x is obtained by orthogonally projecting it onto the column space of the basis matrix D.p Then project it onto the null space corresponding to the basis matrix to obtain the correlation. Then calculate x p and The ratio of vector x i The degree of correlation p with matrix D.

[0186] Referring to Figure 3A, which is a schematic diagram of the spatial projection relationship between a vector and a basis matrix provided in an embodiment of this application, as shown in Figure 3A, x i The correlation of the projection onto the horizontal column space is x. p The correlation of the projection onto the null space in the vertical direction is Where, x p =DD T x i ,

[0187] When p ≤ preset correlation degree, x i →Basis vector; when p > preset correlation degree, x i →Non-basis vector.

[0188] The code corresponding to the above process of determining basis vectors and non-basis vectors includes the following two parts:

[0189] Part 1: Intermediate quantities needed for calculating vector projection

[0190] Part Two: Determining the correlation between vectors and basis matrices

[0191] 2) Dictionary conversion

[0192] Refer to Figure 3B, which is a schematic diagram of a dictionary transformation provided by an embodiment of this application. As shown in Figure 3B, the non-basic matrix Y i The original data to be compressed is multiplied by the basis matrix D0 on the left as a dictionary to obtain the compression coefficient matrix X. i The process of multiplying a basis matrix with a non-basis matrix is ​​called dictionary transformation.

[0193] Given a sparse matrix with M rows and LM columns, and a dictionary with M columns, the pseudocode for the execution steps is as follows:

[0194] Notice:

[0195] ①The dictionary transformation in the above diagram can be left-multiplying by a dictionary D0, or it can be left-multiplying by the transpose of a dictionary. Or multiply by the conjugate transpose of a dictionary.

[0196] ② Each column of the compression coefficient matrix is ​​a coefficient vector, and the non-basic matrix Y in the figure above is an example. i Each column in the matrix represents a column from the original data matrix that was not selected as base information.

[0197] 3) Coefficient selection

[0198] Referring to Figure 3C, which is a schematic diagram of coefficient selection provided in an embodiment of this application, the coefficient selection step is used to filter out coefficients (the second element value) in the compression coefficient matrix that are greater than a preset threshold, thereby obtaining the corresponding filtered coefficient sequence Z and bitmap B. The value of the second element value in bitmap B is set to "1", and the values ​​of the remaining elements are "0". The corresponding pseudocode for the execution steps is as follows:

[0199] 4) Quantification

[0200] As described in Embodiment 1 above, a first quantized value can be obtained by quantizing the first element value in the base matrix, or a second quantized value can be obtained by quantizing the second element value in the compression coefficient matrix. When transmitting the base matrix, the index of the first quantized value is used to indicate the first element value, and when transmitting the compression coefficient matrix, the index of the second quantized value is used to indicate the second element value.

[0201] The specific steps include:

[0202] • Obtain the min and max values ​​of the quantizer;

[0203] • The data to be compressed is quantized based on min and max. The pseudocode for the quantization execution steps is as follows:

[0204] for i = 0 to I-1

[0205] end for

[0206] Where U is the sequence to be quantized, containing a total of I elements, U max and U min These are the maximum and minimum values, respectively, and V is the quantized output sequence.

[0207] Notice:

[0208] ①Min and max can be configured by the base station through upper-layer signaling, or they can be agreed upon by the protocol, such as a dictionary, and their numerical range is [-1,1].

[0209] ② The protocol fixes a minimum and a maximum value;

[0210] ③ Implicitly obtained, for example, given min=0, the base station only needs to configure the number of quantization bits to obtain the maximum value max;

[0211] ④Min and max can be obtained from the data to be quantized. Execute the following pseudocode steps and then send it to the other end.

[0212] Given a sequence U to be quantized, containing a total of I elements:

[0213] Note: The order of steps 3) or 4) above can be reversed. The corresponding execution order is indicated as follows:

[0214] ① As stipulated in the agreement;

[0215] ②Or the base station indicates this via RRC signaling dictCompressionOrder;

[0216] A key point here is that the execution order of core steps differs for different types of business data (including scatter plots, multipath information, location information, AI feature data, etc.), and instructions are required.

[0217] The beneficial effects of changing the order of steps 3) or 4) are as follows: step 3) before step 4) can effectively reduce the quantization range of the data and improve the quantization accuracy; while step 4) before step 3) can be more conducive to filtering out useful data.

[0218] Example 3: As described in Example 1 above, the first signaling can be carried in MAC CE or RRC signaling. This example provides a detailed description of the first signaling being carried in MAC CE.

[0219] Referring to Figure 4A, which is a schematic diagram of a MAC CE format provided in an embodiment of this application, as shown in Figure 4A, a MAC CE, as shown in gray in the figure, is added to carry the first signaling in the uplink (UL) MAC protocol data unit (PDU) (the uplink is taken as an example, but the downlink can also be used). The UL MAC PDU includes a MAC service data unit (SDU), a MAC CE, and padding information (this information is optional and is abbreviated as opt in the figure). The MAC CE used to carry the first signaling, like other MAC CEs in the MAC PDU, has a reserved / logical channel ID field (R / LCID) header (subheader) and a fixed-length or variable-length MAC CE. The logical channel ID field can also be referred to as the extended logical channel ID field (eLCID).

[0220] Optionally, when the first signaling is carried in the MAC CE, the indication information of the service data type is carried in the logical channel identifier LCID or extended logical channel identifier eLCID field in the MAC header.

[0221] Referring to Figure 4B, which is a schematic diagram of the R / LCID header in a UL MAC PDU provided in an embodiment of this application, the R / LCID header includes 8 bytes, totaling 64 bits. This indicates that R + LCID = 8 bytes, or eLCID = 8 bytes. Taking R + LCID = 8 bytes as an example, R occupies 2 bytes, and LCID occupies 6 bytes. The values ​​in LCID are shown in the table below:

[0222] Table 4

[0223] As shown in Table 4, the 6 bytes occupied by LCID include bits 37-42 as reserved fields. The LCID values ​​of these reserved fields can be used to indicate the data type of a business application. Specific examples are shown in the table below:

[0224] Table 5

[0225] More business data types can be indicated using more reserved fields, without limitation.

[0226] In addition, the first signaling also includes information about the base matrix, indication information of the base matrix, information about the compression coefficient matrix, indication information of the compression coefficient matrix, and the position of the basis vectors in the original data matrix. The form of the first signaling in the MAC CE can be seen in Figure 4C, which is a schematic diagram of the format of a MAC CE carrying the first signaling according to an embodiment of this application. As shown in Figure 4C, the MAC CE, excluding the R / LCID header, may include the content of the first signaling. Some of this content is optional information, such as the position of the base matrix in the original data matrix (which may be preset and does not need to be indicated in the first signaling). Furthermore, the value of the first bitmap may be included in the information of the base matrix, and the value of the second bitmap may be included in the information of the compression coefficient matrix, or it may be separate information. The structure in Figure 4C is only a reference and does not limit the method implementation of the embodiments of this application.

[0227] Furthermore, when the same first signaling carries information from multiple raw data segments, information of the same category can be carried in adjacent fields; that is, adjacent fields include similar information from multiple raw data segments. Refer to Figure 4D, which is a detailed schematic diagram of the format of a MAC CE carrying the first signaling provided in an embodiment of this application. As shown in Figure 4D, the indicator information field of the base matrix carries the indicator information of the base matrix corresponding to the 1st to Rth raw data segments. The indicator information field of the compression coefficient matrix carries the indicator information of the compression coefficient matrix corresponding to the 1st to Rth raw data segments. And so on. In addition, the figure also provides examples of the indicator information of the specific base matrix corresponding to each raw data segment, as well as the information of the base matrix: the index of the second quantization value, the quantization bits of the minimum value of the second quantization value, the quantization bits of the maximum value in the second quantization value, and the index of the second quantization value are arranged sequentially. Other examples are similar.

[0228] Alternatively, as shown in Figure 4E, this is another detailed schematic diagram of the MAC CE format carrying the first signaling provided in an embodiment of this application. Information from the same raw data segment can be carried in adjacent fields.

[0229] As can be seen, in this embodiment of the application, a MAC CE format for carrying the first signaling is defined. All information of the first signaling is carried in the MAC CE, which can ensure that the sending device transmits the content of the first signaling to the receiving device at the same time, so that the receiving device can accurately receive the content of the first signaling, thereby ensuring the timeliness of data decompression based on the first signaling and obtaining the data sent by the sending device.

[0230] Optionally, the content of the first signaling message can be sent partly via MAC CE and partly obtained through other means. That is, the first signaling message can be sent via MAC CE in conjunction with other messages.

[0231] Referring to Figure 5A, which is a schematic diagram of another method and MAC CE constituting the first signaling according to an embodiment of this application, as shown in Figure 5A, the data content type in Table a can be indicated by the sending device sending a first message to the receiving device. Alternatively, it can be agreed upon by simultaneous configuration of the sending and receiving devices. In the first signaling, the indication information regarding the data content type is indicated by the index in the table. Other information, such as the index of the first quantization value in the indication information of the basis matrix, is still indicated by the value in the MAC CE.

[0232] Referring also to Figure 5B, which is a schematic diagram of another method and MAC CE constituting the first signaling according to an embodiment of this application. As shown in Figure 5B, the indication information about the data content type in Table b, as well as the matrix size of the base matrix, the matrix size of the compression coefficient matrix, the size of the first bitmap, and the size of the second bitmap, are all indicated by the first message sent from the sending device to the receiving device. This can also be achieved through simultaneous configuration by both the sending and receiving devices. In the first signaling, the relevant content is indicated by carrying the index value from Table b. Unrelated content in Table b can be indicated by the value in the MAC CE. For example, the maximum value of the second quantization value occupies 5 quantization bits, and the maximum value of the first quantization value occupies 4 quantization bits, etc.

[0233] As can be seen, this application embodiment defines a method for carrying the first signaling by combining other messages with the MAC CE. Using this method to send the first signaling can reduce memory usage in the MAC CE, improve the efficiency of transmitting information related to compressed data, and thus improve the efficiency of data transmission and decompression.

[0234] Example 4: This application example describes in detail the first signaling bearer in RRC signaling.

[0235] Referring to Figure 6A, which is a schematic diagram of carrying first signaling in RRC signaling according to an embodiment of this application, as shown in Figure 6A, the information types configured in the first signaling include: information of the base matrix (dictionary) and the indication information of the base matrix (dicInfo), information of the compression coefficient matrix and the indication information of the compression coefficient matrix (coefficientInfo), the position information of the basis vectors in the original data matrix (bitmap1), and the position information of the second element value in the compression coefficient matrix (bitmap2). A detailed description follows:

[0236] dicInfo: This defines the index of the first quantized value after quantization of the M basis vectors (each vector is of length N) in the basis matrix, the quantization bits of the maximum value of the first quantized value (max), and the quantization bits of the minimum value of the first quantized value (min).

[0237] coefficientInfo: This defines the index of the second element value of the second quantized value after compression of the LM second vectors (L is the total number of vectors in the original data matrix) in the compression coefficient matrix obtained by compressing them with the basis vectors, the quantization bits of the maximum value (max) of the second quantized value, and the quantization bits of the minimum value (min) of the second quantized value.

[0238] bitmap1: Used to indicate the first vector in the original data matrix (corresponding to the basis vector in the basis matrix).

[0239] bitmap2: Used to indicate the position of the second element value (greater than a preset threshold) in the compressed data matrix.

[0240] Alternatively, refer to Figure 6B, which is another schematic diagram of carrying the first signaling in RRC signaling according to an embodiment of this application. As shown in Figure 6B, an index sequence can be created to place quantization bits or data values ​​in various types of indication information. In Figure 6B, dictData is created to represent the D1 index sequences occupied by the basis vectors in the basis matrix. Where D1 = M * n1, M is the total number of basis vectors, and n1 is the number of elements contained in each basis vector.

[0241] CoeffData and bitmapPartitionData have similar formats.

[0242] Alternatively, refer to Figure 6C, which illustrates an RRC data format for indicating different business data types provided in this embodiment. As shown in Figure 6C, a single-layer direct indication can be used to indicate the first signaling corresponding to the original data of different business data types. Specifically, a first signaling is created corresponding to the business data type AI-Split-Data, then a first signaling is created corresponding to the business data type Position-Data, and so on. In nested indication, different business data types are first categorized, including AI data (AI-DataInfo), sensing data (sensing-DataInfo), etc., and then a first signaling is created for each business data type. Using a single-layer direct indication to carry the first signaling in RRC reduces the complexity of the RRC data format. Using a nested indication to carry the first signaling facilitates data management and improves the scalability and flexibility of the RRC data format. Furthermore, the pre-indication of business graph categories allows for a more accurate determination of the structure of subsequent data, facilitating effective error detection and fault tolerance during the initial parsing stage and reducing communication errors caused by data format mismatches.

[0243] Please refer to Figure 7, which is a schematic diagram of a communication device provided in an embodiment of this application. This communication device 1500 can be used to execute any of the methods described in the foregoing embodiments.

[0244] As shown in Figure 7, the communication device includes a processing module 1501 and a transceiver module 1502. The processing module 1501 may be one or more processors, and the transceiver module 1502 may be a transceiver or a communication interface. This communication device can be used to implement the functions of devices such as the first communication device and the second communication device involved in any of the above method embodiments. These devices may be hardware devices, software functions running on dedicated hardware, or virtualization functions instantiated on a platform (e.g., a cloud platform). Optionally, the communication device may also include a storage module 1503 for storing the program code and data of the communication device.

[0245] In a first example, the communication device can function as a transmitting device or a chip of a transmitting device in the embodiments of Figures 2 to 6C, and execute the steps performed by the transmitting device in the above method embodiments. The transceiver module 1502 supports communication with the receiving device. The processing module 1501 can be used to support the execution of actions other than sending and receiving performed by the transmitting device in the above method embodiments.

[0246] Specifically, processing module 1501 is used to generate a first signaling, which includes information about a basis matrix, indication information about the basis matrix, information about a compression coefficient matrix, and indication information about the compression coefficient matrix. The basis matrix includes at least one basis vector, which corresponds to a first vector in the original data matrix. Second vectors in the original data matrix, excluding the first vector, form a non-basis matrix. The basis matrix compresses the non-basis matrix to obtain the compression coefficient matrix. The information about the basis matrix includes the values ​​of the basis vectors and the positions of the corresponding first vectors in the original data matrix. The indication information about the basis matrix includes attribute information about the basis matrix. The information about the compression coefficient matrix includes the values ​​of the second elements and their positions in the compression coefficient matrix. The indication information about the compression coefficient matrix includes attribute information about the compression coefficient matrix, and the second element value is a non-zero element value. Transceiver module 1502 is used to send the first signaling.

[0247] In one feasible implementation, the first signaling is carried in a Media Access Control-Control Element (MAC CE) or in Radio Resource Control (RRC) signaling.

[0248] In one feasible implementation, the correlation between any two first vectors is less than a preset correlation; and / or the correlation between the second vector and at least one first vector is greater than or equal to the preset correlation.

[0249] In one feasible implementation, the indication information of the basis matrix includes basis matrix indication information and / or basis matrix size indication information, wherein the basis matrix indication information is used to indicate that the current information is basis matrix information, and the basis matrix size indication information is used to indicate the size of the basis matrix.

[0250] In one feasible implementation, the basis matrix includes at least one basis vector, which corresponds to a first vector in the original data matrix, including: the basis vector in the basis matrix is ​​the first vector, and the element value of the basis vector is the original data; or the basis vector in the basis matrix is ​​the quantization vector of the first vector, and the element value of the basis vector is the first quantization value.

[0251] In one feasible implementation, when the basis vectors in the basis matrix are the quantization vectors of the first vector, the indication information of the basis matrix further includes at least one of the following: the index of the first quantization value, the quantization bit corresponding to the maximum value of the first quantization value, and the quantization bit corresponding to the minimum value of the first quantization value.

[0252] Using the index of the first quantization value to represent the element value in the basis vector can reduce the memory space occupied by compressed data, thereby improving compression efficiency.

[0253] By indicating relevant information about the first quantization value, the receiving device can decompress the basis vector represented by the first quantization value, thus avoiding incorrect identification of the index of the first quantization value.

[0254] In one feasible implementation, the indication information of the compression coefficient matrix includes compression coefficient indication information and / or compression coefficient matrix size indication information, wherein the compression coefficient matrix indication information is used to indicate that the current information is compression coefficient information, and the compression coefficient matrix size indication information is used to indicate the size of the compression coefficient matrix.

[0255] In one feasible implementation, the first quantization value is the one with the smallest absolute difference between the element values ​​of the basis vector and the multiple quantization values ​​corresponding to the basis matrix.

[0256] This implementation method can reduce the amount of information loss in compressed data.

[0257] In one feasible implementation, the multiple quantization values ​​corresponding to the basis matrix are determined based on the maximum and minimum element values ​​of the basis matrix.

[0258] This implementation method can reduce the number of quantization quantities generated, thereby reducing quantization complexity.

[0259] In one feasible implementation, the second element value is the second quantization value, which is the value obtained by mapping the third element value in the compression coefficient matrix, and the third element value is greater than a preset threshold.

[0260] In one feasible implementation, the information of the basis matrix includes a first bitmap, wherein a first value or a second value in the first bitmap is used to indicate the position of the first vector corresponding to the basis vector in the original data matrix.

[0261] In one feasible implementation, the information in the compression coefficient matrix includes a second bitmap, where a first or second value in the second bitmap is used to indicate the position of the second element value in the compressed data matrix.

[0262] In one feasible implementation, the indication information of the base matrix further includes the size of the first bitmap; and / or the indication information of the compression coefficient matrix further includes the size of the second bitmap.

[0263] In one feasible implementation, the indication information of the compression coefficient matrix also includes a bitmap conversion method, which is used to characterize the sorting method used when the second bitmap is converted into the second bit sequence. The sorting method includes row sorting or column sorting.

[0264] Representing the second bitmap as a second bit sequence reduces the overhead of transmitting the second bitmap. Indicating the sorting method helps the receiving device reconstruct the second bitmap from the second bit sequence, thereby enabling the receiving device to determine the specific position of the second element value in the compression coefficient matrix.

[0265] In one feasible implementation, the first signaling also includes first information, which indicates the business data type of the original data matrix.

[0266] In one feasible implementation, the business data type includes at least one of the following: scatter plot, multipath information, location information, and artificial intelligence (AI) feature data.

[0267] By indicating the type of business data used for compressed data, the receiving device can determine which business to apply the compressed data to, thereby improving data processing efficiency.

[0268] In one feasible implementation, when the first signaling is carried in the MAC CE, the first information is carried in the logical channel identifier LCID or the extended logical channel identifier eLCID field in the MAC header.

[0269] In one feasible implementation, the first signaling also includes second information, which indicates the number A of the original data matrices.

[0270] The first signaling includes information about A base matrices, indication information of the base matrices, information about the compression coefficient matrix, indication information of the compression coefficient matrix, and the number of segments A. After obtaining the number of segments A, the receiving device can decompress the A compression coefficient matrices to obtain A raw data matrices, and then concatenate the A raw data matrices to obtain the concatenated raw data (text). This further ensures the efficiency and accuracy of the data decompression process.

[0271] In a second example, the communication device can function as a receiving device or a chip within a receiving device in the embodiments of Figures 2 to 6C, and execute the steps performed by the receiving device in the above method embodiments. The transceiver module 1502 supports communication with the transmitting device. The processing module 1501 can be used to support the execution of actions other than sending and receiving performed by the receiving device in the above method embodiments.

[0272] Specifically, the transceiver module 1502 is used to receive a first signaling, which includes information about a basis matrix, indication information about the basis matrix, information about a compression coefficient matrix, and indication information about the compression coefficient matrix. The basis matrix includes at least one basis vector, which corresponds to a first vector in the original data matrix. Second vectors in the original data matrix, excluding the first vector, form a non-basis matrix. The basis matrix compresses the non-basis matrix to obtain a compression coefficient matrix. The information about the basis matrix includes the values ​​of the basis vectors and the positions of the corresponding first vectors in the original data matrix. The indication information about the basis matrix includes attribute information about the basis matrix. The information about the compression coefficient matrix includes the values ​​of the second elements and their positions in the compression coefficient matrix. The indication information about the compression coefficient matrix includes attribute information about the compression coefficient matrix, and the second element value is a non-zero element value. The processing module 1501 is used to obtain the original data matrix based on the first signaling.

[0273] In one feasible implementation, the first signaling further includes second information, which indicates the number A of the original data matrices. The processing module 1501 is further configured to: concatenate the A original data matrices according to the second information in the first signaling to obtain the original data text.

[0274] The processing module 1501 may be a processor that can execute computer execution instructions stored in the storage module to cause the chip to perform the methods involved in any of the above embodiments.

[0275] Please refer to Figure 8, which is a schematic diagram of another communication device provided in an embodiment of this application. The communication device 1600 can be a transmitting device or a chip or system-on-a-chip in the transmitting device; it can also be a receiving device or a chip or system-on-a-chip in the receiving device. As shown in Figure 8, the communication device 1600 includes a processor 1601, a communication interface 1602, and a communication line 1603.

[0276] Furthermore, the communication device 1600 may also include a memory 1604. The processor 1601, the memory 1604, and the communication interface 1602 can be connected via a communication line 1603.

[0277] The processor 1601 can be a central processing unit (CPU), a network processor (NP), a digital signal processor (DSP), a microprocessor, a microcontroller, a programmable logic device (PLD), or any combination thereof. The processor 1601 can also be other devices with processing capabilities, such as circuits, devices, or software modules, without limitation.

[0278] Communication interface 1602 is used for communication with other devices or other communication networks. These other communication networks can be Ethernet, radio access network (RAN), wireless local area network (WLAN), etc. Communication interface 1602 can be a module, circuit, transceiver, or any device capable of enabling communication.

[0279] Communication line 1603 is used to connect different components in communication device 1600, enabling communication between them. Communication line 1603 can be a peripheral component interconnect (PCI) bus or an extended industry standard architecture (EISA) bus, etc. This bus can be divided into address bus, data bus, control bus, etc. For ease of illustration, only one thick line is used in Figure 8, but this does not indicate that there is only one bus or one type of bus.

[0280] The memory 1604 may be a device with storage function, used to store instructions and / or data. The instructions may be computer programs.

[0281] For example, the memory 1604 may be a read-only memory (ROM) or other type of static storage device capable of storing static information and / or instructions; it may also be a random access memory (RAM) or other type of dynamic storage device capable of storing information and / or instructions; it may also be an electrically erasable programmable read-only memory (EEPROM), a compact disc read-only memory (CD-ROM) or other optical disc storage, optical disc storage (including compressed optical discs, laser discs, optical discs, digital universal optical discs, Blu-ray discs, etc.), magnetic disk storage media or other magnetic storage devices, etc., without limitation.

[0282] It should be noted that the memory 1604 can exist independently of the processor 1601 or can be integrated with the processor 1601. The memory 1604 can be used to store instructions, program code, or some data, etc. The memory 1604 can be located inside or outside the communication device 1600, without limitation. The processor 1601 is used to execute the instructions stored in the memory 1604 to implement the communication method provided in the following embodiments of this application.

[0283] In one example, processor 1601 may include one or more CPUs, such as CPU0 and CPU1 in Figure 8.

[0284] As an optional implementation, the communication device 1600 may include multiple processors, for example, in addition to processor 1601 in FIG8, it may also include processor 1607.

[0285] As an optional implementation, the communication device 1600 also includes an output device 1605 and an input device 1606. Exemplarily, the input device 1606 is a liquid crystal display (LCD), a light-emitting diode (LED) display device, a cathode ray tube (CRT) display device, or a projector, etc. For example, the input device 1606 can be a keyboard, mouse, microphone, joystick, touchscreen device, or sensing device, etc. The output device 1605 is a display screen, a speaker, etc.

[0286] It should be noted that the communication device 1600 may be a desktop computer, a portable computer, a web server, a mobile phone, a tablet computer, a wireless terminal, an embedded device, a chip system, or a device with a similar structure to that shown in Figure 8. Furthermore, the composition shown in Figure 8 does not constitute a limitation on the communication device. In addition to the components shown in Figure 8, the communication device may include more or fewer components than shown, or combine certain components, or have different component arrangements.

[0287] This application provides a communication system that includes the aforementioned means or devices for transmitting end devices and means or devices for receiving end devices.

[0288] This application provides a computer-readable storage medium storing computer instructions that, when executed, cause the computer to perform the method described in any of the above methods.

[0289] This application provides a computer program product, which includes computer program code. When the computer program code is run, it causes the computer to perform the method described in any of the above methods.

[0290] This application provides a chip coupled to a memory for reading and executing program instructions in the memory, so that the device containing the chip implements the method described in any of the above methods.

[0291] In the above embodiments, the descriptions of each embodiment have their own emphasis. Parts not described in detail in a particular embodiment can be found in the relevant descriptions of other embodiments. It should be noted that, for the sake of simplicity, the foregoing method embodiments are all described as a series of actions. However, those skilled in the art should understand that this application is not limited to the described order of actions, as some steps may be performed in other orders or simultaneously according to this application. Furthermore, those skilled in the art should also understand that the embodiments described in the specification are preferred embodiments, and the actions and modules involved are not necessarily essential to this application.

[0292] In the several embodiments provided in this application, it should be understood that the disclosed apparatus can be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative; for instance, the division of the units described above is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be through some interfaces; the indirect coupling or communication connection between devices or units may be electrical or other forms.

[0293] The units described above as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0294] The above-described embodiments are only used to illustrate the technical solutions of this application, and are not intended to limit them. Although this application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of this application.

Claims

1. A data transmission method, characterized in that, The method includes: A first signaling is generated, comprising information about a basis matrix, indication information about the basis matrix, information about a compression coefficient matrix, and indication information about the compression coefficient matrix. The basis matrix includes at least one basis vector, which corresponds to a first vector in the original data matrix. A second vector in the original data matrix, excluding the first vector, forms a non-basis matrix. The basis matrix compresses the non-basis matrix to obtain the compression coefficient matrix. The information about the basis matrix includes the values ​​of the basis vectors and the positions of the corresponding first vectors in the original data matrix. The indication information about the basis matrix includes attribute information about the basis matrix. The information about the compression coefficient matrix includes the values ​​of the second elements and their positions in the compression coefficient matrix. The indication information about the compression coefficient matrix includes attribute information about the compression coefficient matrix, and the second element value is a non-zero element value. Send the first signaling.

2. A data transmission method, characterized in that, The method includes: The system receives a first signaling message, which includes information about a basis matrix, indication information about the basis matrix, information about a compression coefficient matrix, and indication information about the compression coefficient matrix. The basis matrix includes at least one basis vector, which corresponds to a first vector in the original data matrix. A second vector in the original data matrix, excluding the first vector, forms a non-basis matrix. The basis matrix compresses the non-basis matrix to obtain the compression coefficient matrix. The information about the basis matrix includes the values ​​of the basis vectors and the positions of the corresponding first vectors in the original data matrix. The indication information about the basis matrix includes attribute information about the basis matrix. The information about the compression coefficient matrix includes the values ​​of the second elements and their positions in the compression coefficient matrix. The indication information about the compression coefficient matrix includes attribute information about the compression coefficient matrix, and the second element value is a non-zero element value. The original data matrix is ​​obtained based on the first signaling.

3. The method according to claim 1 or 2, characterized in that, The first signaling is carried in at least one of the following signaling: Media Access Control - Control Element (MAC CE), Radio Resource Control (RRC) signaling.

4. The method according to any one of claims 1-3, characterized in that, The correlation between any two of the first vectors is less than a preset correlation; and / or the correlation between the second vector and at least one of the first vectors is greater than or equal to a preset correlation.

5. The method according to any one of claims 1-4, characterized in that, The indication information of the basis matrix includes basis matrix indication information and / or basis matrix size indication information. The basis matrix indication information is used to indicate that the current information is a basis matrix, and the basis matrix size indication information is used to indicate the size of the basis matrix.

6. The method according to claim 5, characterized in that, The basis matrix includes at least one basis vector, which corresponds to the first vector in the original data matrix, including: The basis vectors in the basis matrix are the first vectors, and the element values ​​of the basis vectors are the original data; or The basis vectors in the basis matrix are the quantization vectors of the first vector, and the element values ​​of the basis vectors are the first quantization values.

7. The method according to claim 6, characterized in that, When the basis vectors in the basis matrix are the quantization vectors of the first vector, the indication information of the basis matrix further includes at least one of the following: the index of the first quantization value, the quantization bit corresponding to the maximum value of the first quantization value, and the quantization bit corresponding to the minimum value of the first quantization value.

8. The method according to any one of claims 1-7, characterized in that, The compression coefficient matrix indication information includes compression coefficient indication information and / or compression coefficient matrix size indication information. The compression coefficient matrix indication information is used to indicate that the current information is compression coefficient information, and the compression coefficient matrix size indication information is used to indicate the size of the compression coefficient matrix.

9. The method according to any one of claims 1-8, characterized in that, The second element value is the second quantization value, which is the value obtained by mapping the third element value in the compression coefficient matrix, and the third element value is greater than a preset threshold.

10. The method according to any one of claims 1-9, characterized in that, The information of the basis matrix includes a first bitmap, and a first value or a second value in the first bitmap is used to indicate the position of the first vector corresponding to the basis vector in the original data matrix.

11. The method according to any one of claims 1-10, characterized in that, The information in the compression coefficient matrix includes a second bitmap, where a first or second value in the second bitmap is used to indicate the position of the second element value in the compressed data matrix.

12. The method according to claim 10 or 11, characterized in that, The indication information of the base matrix also includes the size of the first bitmap; and / or the indication information of the compression coefficient matrix also includes the size of the second bitmap.

13. The method according to claim 12, characterized in that, The indication information of the compression coefficient matrix also includes a bitmap conversion method, which is used to characterize the sorting method used when the second bitmap is converted into the second bit sequence. The sorting method includes row sorting or column sorting.

14. The method according to any one of claims 1-13, characterized in that, The first signaling also includes first information, which is used to indicate the business data type of the original data matrix.

15. The method according to claim 14, characterized in that, The business data types include at least one of the following: scatter plots, multipath information, location information, and artificial intelligence (AI) feature data.

16. The method according to any one of claims 3-15, characterized in that, When the first signaling is carried in the MAC CE, the first information is carried in the logical channel identifier (LCID) or extended logical channel identifier (eLCID) field in the MAC header.

17. The method according to any one of claims 1-16, characterized in that, The first signaling also includes second information, which indicates the number A of the original data matrix.

18. The method according to claim 17, characterized in that, The method also includes: Based on the second information in the first signaling, the A original data matrices are concatenated to obtain the original data text.

19. A communication device, characterized in that, Used to implement the method as described in any one of claims 1, 3 to 17, or to implement the method as described in any one of claims 2 to 18.

20. The apparatus according to claim 19, characterized in that, The device is a terminal device or a network device, or a chip in a terminal device or a network device.

21. A communication device, characterized in that, The communication device includes at least one processor coupled to a memory; The at least one processor is configured to execute a computer program or instructions stored in the memory, such that the method as described in any one of claims 1, 3 to 17 is implemented, or the method as described in any one of claims 2 to 18 is implemented.

22. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a computer program that, when executed, causes the method as described in any one of claims 1, 3 to 17 to be implemented, or causes the method as described in any one of claims 2 to 18 to be implemented.

23. A computer program, characterized in that, When the computer program is run, it causes the method as described in any one of claims 1, 3 to 17 to be implemented, or causes the method as described in any one of claims 2 to 18 to be implemented.

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