Communication method and communication apparatus

Abstract

A communication method and a communication apparatus. The communication method comprises: a first communication apparatus acquiring a signal represented by means of a 2M-nion, M being an integer greater than or equal to 2; and sending the signal to a second communication apparatus by means of at least one antenna group, wherein antennas comprised in each antenna group correspond to different spatial domain dimensions. Therefore, the sending of the signal represented by means of the 2M-nion is realized. Specifically, the algebraic properties of the 2M-nion comprise the replacement of a matrix inversion operation with a conjugate operation . Compared with a solution in which a signal is represented by means of a complex number, the present technical solution allows a signal to be represented by means of a hypercomplex number, thereby reducing the signal processing complexity to a certain extent.

Description

Communication methods and communication devices

[0001] This application claims priority to Chinese Patent Application No. 202510126262.0, filed on January 27, 2025, entitled "Communication Method and Communication Apparatus", the entire contents of which are incorporated herein by reference. Technical Field

[0002] This application relates to the field of wireless communication technology, and more specifically, to a communication method and a communication device. Background Technology

[0003] In multiple-input multiple-output (MIMO) communication systems, complex numbers can be used to represent MIMO signals and MIMO channels. For example, modulation, waveforms, channels, or multi-antenna transmission in wireless communication can all be represented using complex numbers. Using complex numbers to represent MIMO signals has become a mature signal processing method; however, the processing complexity is high when using complex numbers to represent MIMO signals. Therefore, reducing the processing complexity is a pressing issue. Summary of the Invention

[0004] This application provides a communication method aimed at reducing the complexity of signal processing in multi-antenna transmission systems.

[0005] Firstly, a communication method is provided. This method can be executed by a first communication device. Unless otherwise specified, the "first communication device" in this application can refer to the first communication device itself (e.g., a network device or terminal device), or a component of the first communication device (e.g., a processor, chip, or chip system, such as circuits or chips responsible for communication functions in a network device or terminal device (e.g., a modem chip, also known as a baseband chip, or a system-on-chip (SoC) chip containing a modem core, or a system-in-package (SIP) chip), or it can be a logic module or software capable of implementing all or part of the first communication device. For ease of description, the following explanation uses execution by a first communication device as an example.

[0006] The communication method includes: obtaining data via 2 M The signal is represented by an atom, the signal comprising a real part and 2. M -1 imaginary part signal. The signal is transmitted through at least one antenna group, each antenna group comprising 2... M-1 There are 1 antenna, where M is an integer greater than or equal to 2.

[0007] Based on the above technical solution, the signal acquired by the first communication device can be represented by a hypercomplex number, for example, the signal can be represented by 2... M The element M is an integer greater than or equal to 2, meaning that the signal can be represented by a hypercomplex number such as a quaternion, octon, or hexadecimal. Since the hypercomplex number has the algebraic property of using conjugate operations to replace matrix inversion operations, this technical solution can reduce the signal processing complexity to a certain extent compared to the scheme of representing the signal by complex numbers.

[0008] For example, when signals are represented by complex numbers, linear precoding and linear channel equalization involve matrix inversion operations. For instance, in a 2×2 MIMO system (with 2 transmit and 2 receive antennas), this involves inverting a 2D matrix; similarly, in an N×N MIMO system (with N transmit and 2 receive antennas, where N is an integer greater than 2), this involves inverting an N×N matrix. However, when signals are represented by hypercomplex numbers (e.g., quaternions), linear precoding and linear channel equalization may not involve matrix inversion operations, or the complexity of matrix inversion operations may be reduced. For example, in a 2×2 MIMO system, using conjugation operations can replace matrix inversion operations, eliminating the need for matrix inversion; similarly, in an N×N MIMO system, this involves... The inversion operation of a 3D matrix. Therefore, it can be understood that representing signals using hypercomplex numbers can reduce the complexity of signal processing to some extent.

[0009] Secondly, a communication method is provided. This method can be executed by a second communication device. Unless otherwise specified, the "second communication device" in this application can refer to the second communication device itself (for example, if the first communication device is a network device, the second communication device can be a terminal device; or, for example, if the first communication device is a terminal device, the second communication device can be a network device, etc.), or a component of the second communication device (e.g., a processor, chip, or chip system, such as a circuit or chip responsible for communication functions in a terminal device or network device (e.g., a modem chip, also known as a baseband chip, or a SoC chip or SIP chip containing a modem core), or a logic module or software capable of implementing all or part of the functions of the second communication device. For ease of description, the following explanation uses the execution by the second communication device as an example.

[0010] The communication method includes: receiving signals through at least one antenna group, each antenna group comprising 2 antennas. M-1One antenna. The signal is processed via 2... M The atom representation, the signal comprising a real part signal and 2 M -1 is an imaginary part signal, where M is an integer greater than or equal to 2.

[0011] In conjunction with the first or second aspect, in some implementations of the first or second aspect, when M is 2, the signal includes a real part signal and three imaginary part signals, and each of the at least one antenna group includes a first antenna and a second antenna.

[0012] Wherein, the real-number portion signal is carried by the in-phase component of the continuous signal transmitted on the first antenna, and the three imaginary-number portion signals are carried by the quadrature component of the continuous signal transmitted on the first antenna, and by the in-phase component and quadrature component of the continuous signal transmitted on the second antenna, respectively. Alternatively,

[0013] The real part signal is carried by the quadrature component of the continuous signal transmitted on the first antenna, and the three imaginary part signals are carried by the in-phase component of the continuous signal transmitted on the first antenna, and the in-phase component and quadrature component of the continuous signal transmitted on the second antenna, respectively.

[0014] Based on the above technical solution, signals can be represented by quaternions, thereby dividing the number of antennas in the communication system into multiple antenna groups. Each antenna group includes two antennas, which are used to transmit one real part and three imaginary parts of the signal represented by the quaternion, respectively. For an antenna group, the signal represented by the quaternion can be transmitted through two antennas in one time slot. Compared with the signal represented by complex numbers, the signal transmission time can be reduced, thereby improving the signal transmission efficiency.

[0015] For example, when using complex number representations of signals, the signal needs to be transmitted through two time slots on two antennas. However, for quaternion signals, it can be transmitted through a single time slot on two antennas. Therefore, it can be understood that using hypercomplex number representations of signals can improve signal transmission efficiency to some extent.

[0016] In conjunction with the first or second aspect, in some implementations of the first or second aspect, the signal is carried on a channel, the channel being transmitted through the 2 M The channel is represented by a number symbol, comprising a real part channel and 2. M -1 imaginary part of the channel.

[0017] Based on the above technical solutions, channels can also be represented by hypercomplex numbers. Similar to the above-mentioned representation of signals by hypercomplex numbers, representing channels by hypercomplex numbers can reduce the complexity of channel operations to a certain extent.

[0018] In conjunction with the first or second aspect, in certain implementations of the first or second aspect, the received signal corresponding to the signal is represented as follows:

[0019] y qv =h qv x qv +n qv Or, y qv =β qv h qv p qv x qv +n qv =β qv x qv +n qv ,

[0020] Among them, y qv Indicates the received signal, n qv h represents noise. qv Indicates the channel carrying the signal, x qv Indicates the 2 M-1 The signal transmitted on each antenna, β qv p represents the transmit power normalization factor. qv This indicates the precoding corresponding to the signal.

[0021] Based on the above technical solution, when the signal and channel are represented by hypercomplex numbers, the received signal can be represented as the product of the hypercomplex number representing the signal and the hypercomplex number representing the channel, i.e., the dot product between hypercomplex numbers, rather than matrix operations, thus reducing the complexity of determining the received signal.

[0022] In conjunction with the first or second aspect, in certain implementations of the first or second aspect, when the number of transmitting antennas equals the number of receiving antennas, and the number of transmitting antennas is 2,

[0023] The channel is represented by a quaternion as: h qv =h1+h2i+h3j+h4k=(h1+h2i)+(h3+h4i)j,

[0024] The x qv Represented by quaternions: x qv =(x1+x2i)+(x3+x4i)j,

[0025] The n qv Represented by quaternions: n qv=(n1+n2i)+(n3+n4i)j,

[0026] Where h1 represents a real part channel, h2, h3, h4 represent three imaginary part channels, x1+x2i represents the complex signal corresponding to one of the two transmit antennas, x3+x4i represents the complex signal corresponding to the other of the two transmit antennas, n1+n2i represents the noise corresponding to one of the two receive antennas, and n3+n4i represents the noise corresponding to the other of the two receive antennas.

[0027] Based on the above technical solution, in a 2×2 MIMO system (with 2 transmit antennas and 2 receive antennas), the channel, transmit signal, and noise can all be represented by quaternions.

[0028] In conjunction with the first or second aspect, in some implementations of the first or second aspect, the zero-forcing channel equalization corresponding to the signal is represented as:

[0029] in, This represents the signal obtained after zero-forcing channel equalization. h qv The conjugate of |h qv | indicates h qv The model.

[0030] Based on the above technical solution, in a 2×2 MIMO system, the zero-forcing channel equalization corresponding to the signal does not require matrix inversion, which reduces the complexity of zero-forcing channel equalization.

[0031] In conjunction with the first or second aspect, in certain implementations of the first or second aspect, the zero-forcing precoding corresponding to the signal is represented as follows:

[0032] Where, p qv Indicates zero-forcing precoding, h qv The conjugate of |h qv | indicates h qv The model, the N t This indicates the number of transmitting antennas.

[0033] Based on the above technical solution, in a 2×2 MIMO system, the zero-forcing precoding corresponding to the signal does not need to undergo matrix inversion operations, which reduces the complexity of signal zero-forcing precoding.

[0034] In conjunction with the first or second aspect, in certain implementations of the first or second aspect, when the number of transmit antennas equals the number of receive antennas, and the number of transmit antennas is N, where N is an integer greater than 2, the channel passes through... The dimensional matrix is ​​represented as: H qv =A + iB + jC + kD,

[0035] Among them, H qv inverse matrix W1=[(A+iB)+(C+iD)(A-iB) -1 (C-iD)] -1 W2 = (A - iB) -1 (C-iD)W1, where the elements in matrices W1 and W2 are all complex numbers, and the elements in matrices A, B, C, and D are all real numbers.

[0036] Based on the above technical solution, in an N×N MIMO system, the channel represented by the hypercomplex number can be... The matrix inversion method uses a 3D matrix representation, and the matrix inversion process involves the inversion of complex numbers. Compared with the inversion of the N×N-dimensional channel matrix when the signal is represented by complex numbers, this method reduces the computational complexity of the channel matrix.

[0037] In conjunction with the first or second aspect, in some implementations of the first or second aspect, the zero-forcing channel equalization corresponding to the signal is represented as:

[0038] or,

[0039] in, This represents the signal obtained after zero-forcing channel equalization. H represents qv The inverse matrix, y qv This indicates the received signal. H represents qv The conjugate transpose of .

[0040] Based on the above technical solution, in an N×N MIMO system, the zero-forcing channel equalization corresponding to the signal undergoes... The matrix inversion operation, which involves the inversion of complex numbers, reduces the complexity of channel matrix operations compared to the inversion of an N×N dimensional channel matrix when the signal is represented by complex numbers. This matrix inversion reduces the complexity of zero-forcing channel equalization.

[0041] In conjunction with the first or second aspect, in certain implementations of the first or second aspect, the P qv Indicates zero-forcing precoding:

[0042] Or, P qv =[p qv,1 ,…,p qv,l ,…,p qv,L ], p qv,l =U l (:,1:r l ),

[0043] Where, p qv,l This represents the zero-forcing precoding for the l-th user. H represents qv The inverse matrix of U, where L represents the number of users, l represents the user index, and l is a positive integer less than or equal to L. l (:,1:r l ) represents matrix U l The front r l The column, the r l H represents the channel of the l-th user. qv,l The rank, the N t This indicates the number of transmit antennas, and Tr(·) represents the trace of the matrix. P represents qv The conjugate transpose of the channel H of the l-th user qv,l The singular value decomposition is represented as:

[0044] Where, Σ l H represents qv,l The singular value matrix, U l H represents qv,l The left singular matrix, V l H represents qv,l The right singular matrix.

[0045] Based on the above technical solution, in an N×N MIMO system, the zero-forcing precoding corresponding to the signal undergoes... The matrix inversion operation, which involves the inversion of complex numbers, reduces the complexity of channel matrix operations compared to the inversion of an N×N dimensional channel matrix when the signal is represented by complex numbers. This matrix inversion reduces the complexity of zero-forcing precoding.

[0046] Thirdly, a communication device is provided, which may be a first communication device, or a device or module for performing the functions of the first communication device.

[0047] One possible implementation is that the communication device may include modules or units corresponding to the methods / operations / steps / actions described in the first aspect, which may be hardware circuits, software, or a combination of hardware circuits and software.

[0048] In one design, the device may include a processing module and a communication module. The communication module is used to perform the sending and receiving actions performed by the first communication device in the method described in the first aspect above, while the processing module is used to perform processing-related actions performed by the first communication device in the method described in the first aspect above.

[0049] In one design, the device can be a terminal device, or a device, module, circuit, or chip configured in the terminal device, or a device that can be used in conjunction with the terminal device.

[0050] Fourthly, a communication device is provided, which may be a second communication device, or a device or module for performing the functions of a second communication device.

[0051] One possible implementation is that the communication device may include modules or units corresponding to the methods / operations / steps / actions described in any of the second aspects, wherein the modules or units may be hardware circuits, software, or a combination of hardware circuits and software.

[0052] In one design, the device may include a processing module and a communication module. The communication module is used to perform the sending and receiving actions performed by the second communication device in the method described in the second aspect above, while the processing module is used to perform processing-related actions performed by the second communication device in the method described in the second aspect above.

[0053] In one design, the device can be a network device, or a device, module, circuit, or chip configured in the network device, or a device that can be used in conjunction with the network device, such as an intelligent network element with a deployed radio intelligent controller (RIC).

[0054] Fifthly, a communication apparatus is provided, comprising: at least one processor for executing a computer program or instructions to perform the methods described in the first aspect and any possible implementations of the first and second aspects. Optionally, the apparatus further comprises a memory for storing the computer program or instructions. Optionally, the apparatus further comprises a communication interface through which the processor reads the computer program or instructions.

[0055] In one implementation, the device is a communication device (such as a terminal device or a network device).

[0056] In another implementation, the device is a chip, chip system, or circuit for communication equipment (such as terminal equipment or network equipment).

[0057] Sixthly, a processor is provided for performing the methods provided in the first and second aspects described above.

[0058] Unless otherwise specified, or if it does not contradict its actual function or internal logic in the relevant description, the transmission and acquisition / reception operations involved in the processor can be understood as processor output and reception, input and other operations, or as transmission and reception operations performed by radio frequency circuits and antennas. This application does not limit them in this regard.

[0059] Optionally, the device further includes: a memory for storing a program; correspondingly, at least one processor for executing the computer program or instructions in the memory.

[0060] Optionally, the device also includes a communication interface. The communication interface is coupled to the processor and can be used to input information to the processor or output information from the processor.

[0061] A seventh aspect provides a computer-readable storage medium storing program code for execution by a device, the program code including methods for performing any possible implementation of the first and second aspects described above.

[0062] Eighthly, a computer program product containing instructions is provided, which, when run on a computer, causes the computer to perform the method in any possible implementation of the first and second aspects described above.

[0063] Ninth aspect, a chip is provided, the chip including a processing circuit and a communication interface, the processing circuit reading instructions from a memory through the communication interface and executing the method provided by any of the implementations of the first and second aspects above.

[0064] Optionally, the processing circuit is one or more processors, or all or part of the control or processing circuitry included in one or more processors.

[0065] Optionally, as one implementation, the chip also includes a memory storing computer programs or instructions, and a processor for executing the computer programs or instructions in the memory. When the computer programs or instructions are executed, the processor is used to perform the methods provided by any of the implementations of the first and second aspects described above.

[0066] A tenth aspect provides a communication system, including a first communication device and a second communication device. The second communication device is used to implement the method provided in any possible implementation of the second aspect; the first communication device is used to implement the method provided in any possible implementation of the first aspect. Attached Figure Description

[0067] Figure 1 is an architecture diagram of a communication system applicable to an embodiment of this application.

[0068] Figure 2 is a schematic diagram of an Open Radio Access Network (ORAN) system architecture.

[0069] Figure 3 is a schematic diagram of a complex MIMO system.

[0070] Figure 4 is a schematic flowchart of a communication method provided in this application.

[0071] Figure 5 is a schematic diagram of a MIMO system represented by quaternions.

[0072] Figure 6 is a schematic diagram of a 4×4 MIMO system.

[0073] Figure 7 is a schematic diagram of the Alamouti encoding effect.

[0074] Figure 8 is a schematic diagram of the uplink MU-MIMO channel equalization effect.

[0075] Figure 9 is a schematic diagram of the downlink MU-MIMO precoding effect.

[0076] Figure 10 is a schematic block diagram of a communication device provided in an embodiment of this application.

[0077] Figure 11 is a schematic diagram of another communication device provided in an embodiment of this application.

[0078] Figure 12 is a schematic diagram of a chip system provided in an embodiment of this application. Detailed Implementation

[0079] To facilitate understanding of the embodiments of this application, the following points will be explained first.

[0080] First, in this application, "for indicating" can include both direct and indirect indication. When describing an indication message as indicating A, it can include whether the indication message directly indicates A or indirectly indicates A, but does not necessarily mean that the indication message carries A.

[0081] The information indicated by the instruction is called the information to be instructed. In the specific implementation process, there are many ways to indicate the information to be instructed, such as, but not limited to, directly indicating the information to be instructed, such as the information to be instructed itself or its index. It can also be indirectly indicated by indicating other information, where there is a relationship between the other information and the information to be instructed. It can also indicate only a part of the information to be indicated, while the other parts are known or pre-agreed upon. For example, the instruction of specific information can be achieved by using a pre-agreed (e.g., protocol-defined) arrangement of various pieces of information, thereby reducing instruction overhead to some extent. At the same time, common parts of various pieces of information can be identified and indicated uniformly to reduce the instruction overhead caused by individually indicating the same information.

[0082] Second, in this application, "at least one" refers to one or more, and "more than one" refers to two or more (including two). Furthermore, in the embodiments of this application, "first," "second," and various numerical designations (e.g., "#1," "#2," etc.) are merely for descriptive convenience and are not intended to limit the scope of the embodiments of this application. The sequence numbers of the processes below do not imply the order of execution; the execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of this application. It should be understood that the objects described in this way can be interchanged where appropriate to describe solutions other than those in the embodiments of this application. Moreover, in the embodiments of this application, terms such as "S410" are merely identifiers for descriptive convenience and do not limit the order of execution steps.

[0083] Third, in the embodiments of this application, the words "exemplary" or "for example" are used to indicate that they are examples, illustrations, or descriptions. Any embodiment or design that is described as "exemplary" or "for example" in this application should not be construed as being more preferred or advantageous than other embodiments or design options. Specifically, the use of the words "exemplary" or "for example" is intended to present the relevant concepts in a specific manner.

[0084] Fourth, in the implementation of this application, "protocol" may refer to standard protocols in the field of communications, such as the NR protocol and related protocols applied in future communication systems, and this application does not limit it.

[0085] Fifth, in the embodiments of this application, "corresponding, relevant", "corresponding", and "associate" can sometimes be used interchangeably. It should be noted that when their differences are not emphasized, their intended meanings are consistent.

[0086] Sixth, in the embodiments of this application, "under the circumstances", "when", and "if" can sometimes be used interchangeably. It should be noted that when the distinction is not emphasized, their intended meanings are consistent.

[0087] Seventh, the term "and / or" in this article 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 existing alone, A and B existing simultaneously, or B existing alone. Additionally, the character " / " in this article generally indicates that the preceding and following related objects have an "or" relationship.

[0088] Eighth, the terms "message", "information", or "information element (IE)" can be used interchangeably in this article. There are no restrictions on the names of messages, information, or frames, as long as they can achieve the corresponding functions.

[0089] Ninth, in this application, "send" and "receive" indicate the direction of signal transmission. For example, "send information to XX" can be understood as the destination of the information being XX, and "send information" can include direct transmission or indirect transmission through other units or modules. "Receive information from YY" can be understood as the source of the information being YY, and "receive information" can include direct reception from YY or indirect reception from YY through other units or modules. Besides air interface transmission or reception signals implemented at the whole-machine level such as network devices or terminal devices, "send" can also be understood as the "output" of a chip interface, and "receive" can also be understood as the "input" of a chip interface. For example, a modem or system-on-a-chip (SoC) chip or system-in-package (SIP) chip transmits or receives signals. "Send" or "receive" can also be performed through device components, for example, by using buses, traces, or interfaces to transmit or receive signals through several parts, modules, or chips of a device.

[0090] Tenth, in this application, in a 2×2 MIMO system, the signal, channel, precoding, or channel equalization represented by a hypercomplex number can be represented by a scalar. For example, "h" in the following text... qv " represents a channel scalar represented by a quaternion; also, for example, in the following text..." This represents the signal scalar obtained after zero-forcing channel equalization, represented by a quaternion; for example, "p" in the following text... qv "" indicates a zero-forcing precoding scalar represented by a quaternion. Furthermore, in an N×N MIMO system, where N is greater than 2, the signal, channel, precoding, or channel equalization represented by a hypercomplex number can be represented by a matrix or vector. For example, "H" in the following text... qv" represents the channel matrix; also, for example, in the following text..." This represents the signal vector obtained after zero-forcing channel equalization; for example, "P" in the following text... qv "" represents the zero-forcing precoding matrix; for example, "p" in the following text qv,l " represents the zero-forcing precoding matrix of the l-th user.

[0091] The technical solutions in this application will now be described with reference to the accompanying drawings.

[0092] The embodiments of this application can be applied to various communication systems, including but not limited to: 5th generation (5G) systems, LTE systems, Long Term Evolution-Advanced (LTE-A) systems, LTE Frequency Division Duplex (FDD) systems, LTE Time Division Duplex (TDD) systems, etc. They can also be applied to future communication systems, such as 6th generation mobile communication systems. Furthermore, they can be applied to device-to-device (D2D) communication, vehicle-to-everything (V2X) communication, machine-to-machine (M2M) communication, machine-type communication (MTC), Internet of Things (IoT) communication systems, narrowband Internet of Things (NB-IoT) systems, or other communication systems. Furthermore, it can be extended to similar wireless communication systems, such as Wireless-Fidelity (WiFi), Worldwide Interoperability for Microwave Access (WIMAX), and communication systems related to the 3rd Generation Partnership Project (3GPP), without limitation.

[0093] The communication system applicable to embodiments of this application may include one or more data transmitters and one or more data receivers. Optionally, one of the transmitters and receivers may be a terminal device and the other a network device.

[0094] Figure 1 is an architecture diagram of a communication system applicable to embodiments of this application. As shown in Figure 1, embodiments of this application can be applied to both uplink and downlink transmissions. Figure 1 only uses uplink or downlink transmission between one network device and two terminal devices (such as terminal device 1 and terminal device 2) as an example. In uplink transmission, the data sender is the terminal device, and the data receiver is the network device; in downlink transmission, the sender is the network device, and the receiver is the terminal device.

[0095] For ease of understanding, the following describes the equipment (or network elements, nodes, etc.) that may be involved in this application.

[0096] Terminal equipment: can be called user equipment (UE), access terminal, user unit, user station, mobile station, mobile station, remote station, remote terminal, mobile device, user terminal, terminal, wireless communication equipment, user agent, or user device.

[0097] Terminal devices can be devices that provide voice / data connectivity to users, such as handheld devices with wireless connectivity, in-vehicle devices, etc. Currently, examples of terminals include: mobile phones, tablets, laptops, PDAs, mobile internet devices (MIDs), wearable devices, virtual reality (VR) devices, augmented reality (AR) devices, wireless terminals in industrial control, wireless terminals in self-driving, wireless terminals in remote medical surgery, wireless terminals in smart grids, wireless terminals in transportation safety, wireless terminals in smart cities, wireless terminals in smart homes, cellular phones, cordless phones, session initiation protocol phones, wireless local loop (WLL) stations, personal digital assistants (PDAs), handheld devices with wireless communication capabilities, computing devices or other processing devices connected to wireless modems, in-vehicle devices, wearable devices, terminal devices in 5G networks, or terminal devices in future evolved public land mobile networks (PLMNs), etc., and this application does not limit these examples.

[0098] By way of example and not limitation, in this embodiment, the terminal device can also be a wearable device. Wearable devices, also known as wearable smart devices, are a general term for devices that utilize wearable technology to intelligently design and develop everyday wearables, such as glasses, gloves, watches, clothing, and shoes. Wearable devices are portable devices that are worn directly on the body or integrated into the user's clothing or accessories. Wearable devices are not merely hardware devices, but also achieve powerful functions through software support, data interaction, and cloud interaction. Broadly speaking, wearable smart devices include those that are feature-rich, large in size, and can achieve complete or partial functions without relying on a smartphone, such as smartwatches or smart glasses, as well as those that focus on a specific type of application function and require the use of other devices such as smartphones, such as various smart bracelets and smart jewelry for vital sign monitoring.

[0099] Furthermore, in this embodiment, the terminal device can also be a terminal device in an IoT system. IoT is an important component of the future development of information technology. Its main technical feature is to connect objects to the network through communication technology, thereby realizing an intelligent network of human-machine interconnection and object-to-object interconnection.

[0100] Network equipment, also known as access network equipment, provides network access functionality for terminal devices and can use transmission tunnels of different quality depending on the user's level and service requirements. Access networks can employ different access technologies. Currently, there are two types of wireless access technologies: 3GPP (3rd Generation Partnership Project) access technologies (such as those used in 3G, 4G, or 5G systems) and non-3GPP access technologies. 3GPP access technologies refer to those that conform to 3GPP standards and specifications; for example, access network equipment in 5G systems is called a next-generation node base station (gNB). Non-3GPP access technologies refer to those that do not conform to 3GPP standards and specifications; for example, air interface technologies represented by access points (APs) in Wireless Fidelity (WiFi).

[0101] An access network that uses wireless communication technology to implement access network functions can be called a radio access network (RAN). The RAN manages radio resources, provides access services to terminal devices, and facilitates the forwarding of control signals and user data between the terminal and the core network. The RAN can also be an open RAN (O-RAN).

[0102] RAN nodes, also known as radio access network devices, RAN entities, or access nodes, are used to help terminals access communication systems wirelessly. In one application scenario, an RAN node can be a base station, an evolved NodeB (eNodeB), a transmission reception point (TRP), a next-generation NodeB (gNB) in a 5G mobile communication system, a next-generation base station in a future mobile communication system, a base station in a future mobile communication system, or an access node in a WiFi system. RAN nodes can be macro base stations, micro base stations, indoor stations, relay nodes, or donor nodes.

[0103] In another application scenario, multiple RAN nodes can collaborate to help terminals achieve wireless access, with different RAN nodes implementing different functions of the base station. For example, a RAN node can be a central unit (CU), a distributed unit (DU), or a radio unit (RU). The CU performs the functions of the base station's radio resource control (RRC) protocol and packet data convergence protocol (PDCP), and can also perform the service data adaptation protocol (SDAP) function. The DU performs the functions of the base station's radio link control (RLC) layer and medium access control (MAC) layer, and can also perform some or all of the physical layer (PHY) functions. For specific descriptions of these protocol layers, refer to the relevant 3GPP technical specifications. The RU can be used to implement radio frequency signal transmission and reception. The CU and DU can be two independent RAN nodes, or they can be integrated into the same RAN node, such as within a baseband unit (BBU). RUs can be included in radio frequency equipment, such as remote radio units (RRUs) or active antenna units (AAUs). CUs can be further divided into two types of RAN nodes: CU-control plane and CU-user plane.

[0104] In different systems, RAN nodes can have different names. For example, in an Open RAN (O-RAN) system, a CU can also be called an Open CU (O-CU), a DU can also be called an Open DU (O-DU), and a RU can be called an Open RU (O-RU).

[0105] Figure 2 illustrates an exemplary ORAN system architecture provided in an embodiment of this application. The ORAN system in this embodiment may include components other than those shown in Figure 2. As shown in Figure 2, access network devices can communicate with the core network (CN) via a backhaul link and with terminals via an air interface. For example, a BBU in the access network device communicates with the core network via a backhaul link, and an RU in the access network device communicates with at least one terminal via an air interface. The BBU communicates with at least one RU via a fronthaul link; the BBU and RU may or may not be co-located. The BBU includes at least one CU and at least one DU, which can communicate via at least one midhaul link.

[0106] In this application, the RAN node can be implemented through software modules, hardware modules, or a combination of software and hardware modules. For example, the RAN node can be a server loaded with the corresponding software module. The embodiments of this application do not limit the specific technology or device form used in the RAN node.

[0107] For example, the aforementioned terminal equipment and / or access network equipment includes one or more functional modules for signal processing. Taking physical layer functions as an example, the terminal equipment and / or access network equipment includes one or more of the following functions: coding, rate matching, scrambling, modulation, layer mapping, precoding, resource element (RE) mapping, digital beamforming (BF), inverse fast Fourier transformation (IFFT) / adding a cyclic prefix (CP), decoding, rate matching dematching, descrambling, demodulation, inverse discrete Fourier transformation (IDFT), channel equalization (or channel estimation), RE demapping, digital BF, fast Fourier transform (FFT) / CP removal, digital to analog (DA) conversion, analog BF, analog to digital (AD) conversion, or analog BF.

[0108] It should be understood that the access network can provide services to the cell. Terminal devices can communicate with the cell through the transmission resources (e.g., frequency domain resources, or spectrum resources) allocated by the access network devices.

[0109] The communication systems and service scenarios described in the embodiments of this application are for the purpose of more clearly illustrating the technical solutions of the embodiments of this application, and do not constitute a limitation on the technical solutions provided in the embodiments of this application. As those skilled in the art will know, with the evolution of network architecture and the emergence of new service scenarios, the technical solutions provided in the embodiments of this application are also applicable to similar technical problems.

[0110] To facilitate understanding of the embodiments of this application, some basic concepts involved in this application will be briefly explained.

[0111] 1. Quaternion: A quaternion is a hypercomplex number consisting of one real part and three imaginary parts. For example, a quaternion can be represented as: q = q1 + q2i + q3j + q4k (1-1)

[0112] In the above equation (1-1), q1, q2, q3, and q4 are real numbers, and i, j, and k are imaginary units.

[0113] The operational properties of the imaginary unit of quaternions include: i 2 =j 2 =k 2 =ijk=-1.

[0114] Quaternion multiplication does not satisfy the commutative law: ij = k, jk = i, ki = j, ji = -k, kj = -i, ik = -j.

[0115] The conjugate of a quaternion is defined as: q * = q1-q2i-q3j-q4k.

[0116] The modulus (or length) of a quaternion is defined as:

[0117] Quaternions offer higher degrees of freedom, thus enhancing signal processing. Furthermore, quaternions possess three-dimensional (3D) transformation and rotation capabilities, and can effectively handle complex, multi-dimensional data. Compared to matrix inversion operations with binary (complex) numbers, quaternions possess important algebraic properties: inversion can be replaced by conjugation, such as: In other words, for quaternions, conjugate operations and inversion operations have equivalent effects.

[0118] 2. Complex numbers: These are binary numbers, containing a real part and an imaginary part. In wireless communication, modulation, waveforms, channels, and multi-antenna transmissions all use complex numbers. The signal physically transmitted on an antenna is a real signal, while complex signals are carried by in-phase and quadrature components. These in-phase and quadrature components are orthogonal to each other, decomposing any signal into two independent parts. For example, the in-phase component (I component) represents the part of the signal that is in phase with the reference signal. In other words, the in-phase component reflects the change of the signal in the same phase as the reference signal. Similarly, the quadrature component (Q component) represents the part of the signal that is quadrature with the reference signal. In other words, the quadrature component reflects the change of the signal in the quadrature phase of the reference signal.

[0119] For example, a modulation constellation diagram can be represented by a complex number.

[0120] Optionally, the modulation constellation diagram includes binary phase shift keying (BPSK), quadrature phase shift keying (QPSK), quadrature amplitude modulation (QAM), etc.

[0121] For example, BPSK constellation points include QPSK constellation points include 16QAM constellation points include

[0122] For example, signal waveforms can also be represented by complex numbers.

[0123] Optionally, the signal waveform includes orthogonal frequency division multiplexing (OFDM), discrete fourier transform spreading OFDM (DFT-s-OFDM), etc. For example, the OFDM waveform s(t) can be represented as:

[0124] In equation (1-2) above, k represents the subcarrier number, and a k The modulation symbol is represented by Δf, the subcarrier spacing is represented by T. CP This indicates the duration of the cyclic shift, and T represents the OFDM symbol period.

[0125] For example, a communication channel can also be represented by a complex number.

[0126] Optionally, the channel can be represented in the time domain or the frequency domain. For example, the impulse response h(t) of a time-invariant channel is expressed as:

[0127] In equation (1-3) above, P represents the number of channel multipaths, and h p τ represents the fading coefficient of the p-th path. p Let δ(·) represent the time delay of the p-th path, and let δ(·) represent the impulse function. Represents the complex field.

[0128] For example, signals transmitted by multiple antennas can also be represented by complex numbers.

[0129] Optionally, the up-conversion of the signal involves modulating the baseband complex signal s(t) to a center frequency of f. c The real part is then taken from the carrier wave and transmitted. For example, the up-converted signal x(t) can be expressed as:

[0130] In equation (1-4) above, ∠s(t) represents the phase of the complex number s(t), |s(t)|cos∠s(t) represents the in-phase component of the signal (carrying the real part information of the complex signal s(t), and |s(t)|sin∠s(t) represents the quadrature component of the signal (carrying the imaginary part information of the complex signal s(t).

[0131] 3. MIMO signals and MIMO channels: In MIMO multi-antenna transmission, complex numbers are used to represent MIMO signals and MIMO channels. For example, precoding at the transmitting end, channel equalization at the receiving end, or Alamouti coding with two antennas can be represented by the complex number z = x + yi.

[0132] For example, linear precoding or channel equalization in MIMO can be represented using complex numbers, where linear precoding or channel equalization can be zero-forcing (ZF) precoding or channel equalization, or minimum mean square error (MMSE) precoding or channel equalization, and both zero-forcing precoding or channel equalization and MMSE precoding or channel equalization require matrix inversion operations.

[0133] For example, Alamouti encoded signals can be represented using complex numbers, but in this scenario, Alamouti encoding requires transmitting signals over two time slots on two antennas.

[0134] 4. Linear precoding: This is a signal processing technique used in multi-antenna communication systems. It aims to improve the transmission performance of the communication system by linearly combining the transmitted signals at the transmitting end to maximize the quality of the received signal at the receiving end. Linear precoding optimizes channel transmission by adjusting the weight matrix and achieves better signal separation at the receiving end.

[0135] For example, as shown in Figure 3, when the MIMO signal and MIMO channel are represented by complex numbers, the precoding matrix for ZF precoding is: H + =H H (HH H ) -1 (1-5)

[0136] Since the ZF precoding matrix in equation (1-5) is the right pseudo-inverse of the channel matrix H, in order to ensure that the power of the transmitted signal remains unchanged after precoding, normalization is performed. Let β represent the power normalization factor. Then the ZF precoding matrix takes the form: W ZF =βH + =βH H (HH H ) -1 (1-6)

[0137] As can be seen from Figure 3, the channel matrix H can be represented as... As can be seen from the above, when the MIMO signal and MIMO channel are represented by complex numbers, the transmitting ZF precoding process needs to perform matrix inversion operations.

[0138] It should be understood that the minimum mean square error precoding process also requires matrix inversion operations. You can refer to the current explanations of the minimum mean square error precoding process, which will not be repeated here.

[0139] 5. Linear Channel Equalization: This is a commonly used channel equalization technique in digital communication systems, primarily used to eliminate channel distortion. Its basic idea is to construct an inverse filter so that the received signal, multiplied by the channel's impulse response, recovers the original transmitted signal.

[0140] For example, for zero-forcing channel equalization, an inverse filter can be designed so that the received signal, after being processed by the filter, can be restored to the original transmitted signal as much as possible. Using complex numbers to represent the MIMO signal and MIMO channel, assuming the channel impulse response is h(n), the received signal is y(n), and the transmitted signal is x(n), then the output of the zero-forcing channel equalization detector can be expressed as: z(n) = y(n) * h -1 (n) (1-7)

[0141] In equation (1-7) above, "*" represents the convolution operation, h -1 (n) represents the inverse filter of the channel impulse response.

[0142] It should be understood that the minimum mean square error channel equalization process also requires matrix inversion operations. Please refer to the current explanations of the minimum mean square error channel equalization process, which will not be repeated here.

[0143] 6. Alamouti coding: A space-time block coding technique primarily used in systems with two transmit antennas. It combats channel fading and noise by utilizing the diversity of time and space. In the case of complex representations of MIMO signals and MIMO channels, the Alamouti coding scheme effectively eliminates the effects of channel fading by transmitting two symbols at two different times, each transmitted through a different antenna. This allows decoding at the receiver to utilize the correlation of the signals, meaning the signal needs to be transmitted over two time slots on two antennas.

[0144] 7. Rank Adaptive Technology: In MIMO spatial multiplexing, rank adaptive technology is a key means to ensure overall system performance. If the transmitter has MIMO transmission capability, it can select single-stream or multi-stream transmission mode to serve specific users requesting services based on the current channel conditions. This adaptive selection of single-stream or multi-stream transmission mode is the rank adaptive process. If the current user is experiencing good channel conditions (e.g., located in the cell center), the transmitter can choose to transmit multi-stream data to achieve a larger data transmission volume using spatial multiplexing while ensuring a high transmission success rate. If the current user is experiencing poor channel conditions (e.g., located at the cell edge), the transmitter can choose to transmit single-stream data to ensure correct data reception first. Therefore, rank adaptive technology can effectively utilize channel state information to improve the overall system performance.

[0145] The preceding text, in conjunction with Figure 1, briefly introduces the application scenarios of the communication method provided in this application embodiment, as well as the basic concepts that may be involved in this application embodiment. Among the basic concepts, it introduces the method of using complex numbers to represent MIMO signals and MIMO channels. It should be noted that using complex numbers to represent MIMO signals and MIMO channels has formed a mature signal processing method. However, as can be seen from the description of precoding or channel equalization in the above basic concepts, when using complex numbers to represent MIMO signals and MIMO channels, precoding or channel equalization requires matrix inversion operations, which has high computational complexity.

[0146] Furthermore, as described in the above basic concepts regarding Alamouti coding, when complex numbers represent MIMO signals and MIMO channels, Alamouti-coded signals require transmission over two time slots on two antennas. Transmitting signals over two time slots may affect the efficiency of signal transmission. For example, compared to transmitting signals over one time slot using two antennas, the transmission efficiency of the complex-based Alamouti-coded signal is half that of transmitting signals over one time slot.

[0147] To address the aforementioned problems associated with using complex numbers to represent MIMO signals and MIMO channels, this application provides a communication method that represents signals using hypercomplex numbers (such as quaternions, octonions, etc.). Since hypercomplex numbers possess the algebraic property of using conjugate operations to replace matrix inversion operations, this technical solution can reduce the signal processing complexity to a certain extent compared to schemes that represent signals using complex numbers.

[0148] It should be understood that the communication method provided in this application embodiment can be applied to multi-antenna communication systems, such as the communication system shown in Figure 1. The application scenarios of the above-described embodiments of this application are merely examples and do not constitute any limitation on the scope of protection of this application.

[0149] It should also be understood that the embodiments shown below do not particularly limit the specific structure of the execution subject of the method provided in the embodiments of this application, as long as it is possible to communicate according to the method provided in the embodiments of this application by running a program that records the code of the method provided in the embodiments of this application. For example, the execution subject of the method provided in the embodiments of this application can be a device, or a functional module in the device that can call and execute a program.

[0150] Furthermore, the signals involved in the following embodiments may be reference signals, data signals, or signals transmitted in other communication systems. For example, the signals in this application may be demodulation reference signals (DMRS), channel state information-reference signals (CSI-RS), tracking reference signals (TRS), sounding reference signals (SRS), phase tracking reference signals (PT-RS), positioning reference signals (PRS), sensing reference signals (SeRS), etc.

[0151] It should be understood that the signals in this application may also be signals other than the reference signals listed above, which will not be listed here.

[0152] For example, the signal in this application can be an OFDM signal, for example, having N d A sequence S of symbols m The signal is mapped onto the corresponding subcarrier, weighted (i.e., precoding, frequency windowing, power control, etc.), and then subjected to an inverse Fourier transform to obtain the time-domain signal x. m .

[0153] It should be noted that this application does not impose any limitations on the steps involved in the OFDM signal generation process. For example, the time-domain discrete sequence may be subjected to serial-to-parallel conversion, discrete Fourier transformation (DFT), subcarrier mapping, inverse discrete Fourier transform (IDFT) (or inverse fast Fourier transform (IFFT)), parallel-to-serial conversion, addition of a cyclic prefix (CP), and digital-to-analog converter (DAC) to generate the OFDM signal to be transmitted. This application mainly concerns how to represent the signal using hypercomplex numbers and how to process the signal based on the hypercomplex number representation. The signal generation process will not be elaborated upon below.

[0154] Figure 4 is a schematic flowchart of a communication method provided in this application. It includes the following steps:

[0155] S410, the first communication device obtains information via 2 M Signals represented by atom numbers.

[0156] As one possible implementation, the first communication device can be a network device. In this implementation, the first communication device acquires data via 2... M Signals represented by elements can be downlink signals. For example, through 2 M The signal represented by the atom number can be a downlink reference signal such as DMRS or CSI-RS, or, for example, 2 M The signals represented by the atom number can be other downlink data signals sent by the network device to the terminal device, which will not be listed here.

[0157] As one possible implementation, the first communication device can be a terminal device. In this implementation, the first communication device acquires data via 2... M Signals represented by atom numbers can be uplink signals. For example, through 2 M The signal represented by the atom can be an uplink reference signal such as SRS, or, for example, 2. M The signals represented by the atomic number can be other uplink data signals sent by the terminal device to the network device, which will not be listed here.

[0158] It should be understood that the aforementioned first communication device, which is a network device or terminal device, is merely an example and does not constitute any limitation on the scope of protection of this application. The first communication device can be other devices, and in this application, the first communication device can be understood as a signal transmitting device or a transmitting end device, etc. Similarly, the second communication device mentioned below can be understood as a signal receiving device or a receiving end device, etc. This application does not limit the specific form of the first and second communication devices, as long as they can achieve the corresponding functions.

[0159] Specifically, the first communication device receives a signal, and this signal is transmitted through 2 M Atom representation. The signal passes through 2... M Atom representation can be understood as a signal sequence passing through 2 M The form of the atom is represented if the signal passes through 2 M The element representation involves the signal processing process. M Atoms need to participate in the calculations during signal processing. The following section will explain this in conjunction with a specific signal processing procedure. M How quaternions participate in the signal processing operations, as shown in Example 1 (Alamouti coding based on quaternions), Example 2 (uplink multi-user (MU) MIMO channel equalization based on quaternions), and Example 3 (downlink MU-MIMO precoding based on quaternions), will not be elaborated here.

[0160] The above 2 M The algebraic properties of atom numbers include the conjugate operation replacing matrix inversion. That is, this application uses 2... M Atoms represent signals that enable 2 M When a signal represented by an atom is processed by a device (e.g., a first communication device and / or a second communication device), the device performs conjugation operations instead of matrix inversion. Since matrix inversion is relatively complex, using conjugation operations instead reduces the complexity of the signal processing.

[0161] Among them, 2 M The signal represented by the atom consists of a real part of the signal and 2. M -1 is an imaginary part signal, where M is an integer greater than or equal to 2, meaning that in this application, the signal is represented as a real part and 2. M -1 imaginary part.

[0162] By way of example and not limitation, the first communication device in this application obtains information via 2 M Signals represented by atom numbers can be:

[0163] The first communication device generates the signal, which is transmitted via 2M Atom representation; or,

[0164] The first communication device receives the signal, which is transmitted via 2 M Metadata representation. For example, the first communication device receives this signal from the management device.

[0165] Optionally, 2 M Atoms can also be called hypercomplex numbers, such as quaternions, octonions, or hexadecimals. It should be understood that this application does not impose any limitations on the specific form of hypercomplex numbers, as long as they possess the algebraic property of using conjugate operations to replace matrix inversion. For example, hypercomplex numbers can also be 32-element numbers, etc., which will not be listed here.

[0166] For example, the value of M is 2, 2 M The quaternion is a quaternion, meaning the signal can be represented using quaternions. For example, the signal can be represented as s = s1 + s2j = s 1r +s 1i i+s 2r j+s 2i k, where s1 and s2 represent complex signals, s 1r and s 1i This represents the real and imaginary parts of the complex signal s1. 2r and s 2i This represents the real and imaginary parts of the complex signal s2. 1r The real part of the quaternion signal s is represented by s. 1i s 2r and s 2i This represents the imaginary part of the quaternion signal s, where i, j, and k are the imaginary units.

[0167] For example, M can take the values ​​3 and 2. M The octonions are octonions, meaning that signals can also be represented using octonions. For example, a signal can be represented as s = s1 + s2j + s3l + s4p = s 1r +s 1i i+s 2r j+s 2i k+s 3r l+s 3i m+s 4r p+s 4i q, where s1, s2, s3, and s4 represent complex signals, s 1r and s 1i This represents the real and imaginary parts of the complex signal s1. 2r and s 2i This represents the real and imaginary parts of the complex signal s2. 3r and s 3i This represents the real and imaginary parts of the complex signal s3.4r and s 4i This represents the real and imaginary parts of the complex signal s4. 1r The real part of the quaternion signal s is represented by s. 1i s 2r s 2i s 3r s 3i s 4r and s 4i All of these represent the imaginary part of the quaternion signal s, where i, j, k, l, m, p, and q are the imaginary units.

[0168] For example, the signal can be transmitted via 2 M In atom representation, M can take the value of an integer greater than 3. For example, signals can also be represented using hexadecimals, which will not be discussed further here.

[0169] It should be understood that this application does not limit the specific form of the signal to be transmitted acquired by the first communication device through the hypercomplex number. The hypercomplex number only needs to have the algebraic property of replacing matrix inversion operation with conjugate operation as described above. For example, the hypercomplex number in this application can be any hypercomplex number other than quaternion, octernion or hexadecimal, and will not be listed here.

[0170] As an example, not a limitation, let's take quaternions as an example to illustrate how to determine if a quaternion possesses the aforementioned algebraic property of replacing matrix inversion with conjugate operations. This can be seen from the description of quaternions in the basic concepts above:

[0171] A quaternion can be represented as: q = q1 + q2i + q3j + q4k. The inverse of a quaternion is the number that multiplies by the quaternion to get 1. The inverse of a quaternion is represented as q. -1 Furthermore, the conjugate of a quaternion is defined as: q * =q1-q2i-q3j-q4k, and Since the modulus of a quaternion is defined as: thereby therefore, Thus we can obtain Therefore, the inverse of a quaternion can be determined based on the conjugate and modulus of the quaternion, without the need to directly perform the inverse operation on the quaternion.

[0172] It should be noted that in this application, the value of M is an integer greater than or equal to 2, indicating that the signal is represented by a quaternion or a hypercomplex number exceeding a quaternion (such as an octonion, a hexadecimal, etc.). If the value of M is 1, it can be understood that the signal is represented by a complex number (or binary number). This application will not elaborate on the case where the signal is represented by a complex number.

[0173] Furthermore, after the first communication device receives the signal, it can send the signal to the second communication device. Therefore, the communication method shown in Figure 4 can also include:

[0174] S420, the first communication device sends a signal to the second communication device, and correspondingly, the second communication device receives the signal from the first communication device.

[0175] Specifically, the first communication device can transmit signals to the second communication device via at least one antenna group. Each antenna group includes 2... M-1 One antenna.

[0176] For example, the second communication device receives signals from the first communication device through at least one antenna group, wherein each antenna group includes 2 M-1 One antenna.

[0177] It should be noted that the number of antennas used by the first communication device to transmit signals and the number of antennas used by the second communication device to receive signals can be equal or unequal. For example, the first communication device can transmit signals to the second communication device using four antennas, and the second communication device can receive signals using two antennas. The first and second communication devices can transmit signals using a number of antennas greater than or equal to two.

[0178] Optionally, the 2 M-1 Each antenna corresponds to a different spatial dimension. This is an example, not a limitation, of the two antennas used in this application. M-1 Each antenna can correspond to a different spatial dimension, which can be: 2 M-1 Each antenna corresponds to a different polarization direction. It should be understood that in this application, 2... M-1 Each antenna corresponds to a different spatial dimension, and it can also be a traditional MIMO device's 2 M-1 One antenna, and the 2 M-1 Each antenna corresponds to a different spatial dimension, which will not be elaborated here.

[0179] It should be noted that 2 M-1 The signals physically transmitted on an antenna are real signals, while complex signals are carried by the in-phase and quadrature components of the real signals transmitted on the antenna.

[0180] For example, the signal mentioned above is denoted as s,2 M-1 The signal transmitted on each antenna is either the signal s or the processed signal s, such as 2. M-1 Let the signal transmitted from each antenna be denoted as x. qv In this application, signal s can be understood as a modulation symbol, and x... qv It can be the same as or different from s, for example, x qv It can be the processed signal of s. The x qvIt can also be represented using quaternions, and 2 M-1 The in-direction component of the signal physically transmitted by one of the antennas (denoted as antenna #1) carries the signal x. qv The real part of the signal, and the other 2 M-1 The orthogonal components of the physically transmitted signal on antenna #1 of the antennas, and 2 M-1 The in-phase and quadrature components of the physically transmitted signals on the antennas other than antenna #1 carry the signal x. qv The imaginary part of the signal; for example, 2 M-1 Let x be the physically transmitted signal from each antenna. qv The x qv It can also be represented using quaternions, and 2 M-1 The orthogonal component of the signal physically transmitted by one of the antennas (denoted as antenna #1) carries the signal x. qv The real part of the signal, and the other 2 M-1 The signal x physically transmitted on antenna #1 of the antennas qv The same-direction components, and 2 M-1 The in-phase and quadrature components of the physically transmitted signals on the antennas other than antenna #1 carry the signal x. qv The imaginary part of the signal.

[0181] As one possible implementation, the signal is represented by a quaternion, with M set to 2. The first communication device can then transmit a signal to the second communication device via at least one antenna group. Each antenna group includes two antennas, each corresponding to a different spatial dimension. For example, the two antennas may have different polarization directions. For instance, one antenna may be horizontally polarized, while the other is vertically polarized. Alternatively, one antenna may be left-elliptical polarized, while the other is right-elliptical polarized, and so on.

[0182] For example, in this implementation, the signal includes a real part signal and three imaginary parts signals. Each antenna group in at least one antenna group includes a first antenna and a second antenna. The real part signal is carried by the in-phase component of the continuous signal transmitted on the first antenna, and the three imaginary parts signal are carried by the quadrature component of the continuous signal transmitted on the first antenna, and by the in-phase component and quadrature component of the continuous signal transmitted on the second antenna, respectively. Alternatively, the real part signal is carried by the quadrature component of the continuous signal transmitted on the first antenna, and the three imaginary parts signal are carried by the in-phase component of the continuous signal transmitted on the first antenna, and by the in-phase component and quadrature component of the continuous signal transmitted on the second antenna, respectively.

[0183] As can be seen from the above, signals can be represented by quaternions, thereby dividing the number of antennas in the communication system into multiple antenna groups. Each antenna group includes two antennas, which are used to transmit one real part and three imaginary parts of the signal represented by the quaternion, respectively. For an antenna group, the signal represented by the quaternion can be transmitted through two antennas in one time slot. Compared with the signal represented by complex numbers, the signal transmission time can be reduced, thereby improving the signal transmission efficiency.

[0184] For example, in this implementation, if the number of transmitting antennas equals the number of receiving antennas and the number of transmitting antennas is 2, then the first communication device and the second communication device can be understood as communication devices in a 2×2 MIMO system. That is, the first communication device can send signals to the second communication device through an antenna group, which includes the two transmitting antennas.

[0185] For example, in this implementation, if the number of transmitting antennas is equal to the number of receiving antennas, and the number of transmitting antennas is 4, then the first communication device and the second communication device can be understood as communication devices in a 4×4 MIMO system. That is, the first communication device can send signals to the second communication device through each of the two antenna groups, and each antenna group includes the two transmitting antennas.

[0186] For example, in this implementation, if the number of transmitting antennas equals the number of receiving antennas, and the number of transmitting antennas is N, where N can be an even number greater than or equal to 2, then the first communication device and the second communication device can be understood as communication devices in an N×N dimensional MIMO system, that is, the first communication device can... Each of the antenna groups transmits signals to the second communication device, and each antenna group includes the two transmitting antennas.

[0187] It should be understood that the above-described possible forms of antenna groups are merely illustrative examples to indicate the possible forms of antenna groups on which the first communication device transmits signals when quaternions represent signals, and do not constitute any limitation on the scope of protection of this application. For example, the number of transmitting antennas and the number of receiving antennas may be different, and will not be illustrated in detail here.

[0188] As another possible implementation, the signal is represented by an octonion, with M set to 3. In this case, the first communication device can transmit a signal to the second communication device via at least one antenna group. Each antenna group includes four antennas, each corresponding to a different spatial dimension. For example, the four antennas may have different polarization directions.

[0189] For example, in this implementation, the signal includes a real part signal and seven imaginary parts signals. Each antenna group in at least one antenna group includes a first antenna, a second antenna, a third antenna, and a fourth antenna. The real part signal is carried by the in-phase component of the continuous signal transmitted on the first antenna, and the seven imaginary parts signal are carried by the quadrature component of the continuous signal transmitted on the first antenna, as well as the in-phase and quadrature components of the continuous signal transmitted on the second, third, and fourth antennas, respectively. Alternatively, the real part signal is carried by the quadrature component of the continuous signal transmitted on the first antenna, and the seven imaginary parts signal are carried by the in-phase component of the continuous signal transmitted on the first antenna, as well as the in-phase and quadrature components of the continuous signal transmitted on the second, third, and fourth antennas, respectively.

[0190] As can be seen from the above, signals can be represented by octonions, thereby dividing the number of antennas in the communication system into multiple antenna groups. Each antenna group includes four antennas, which are used to transmit one real part and three imaginary parts of the signal represented by the octonion. For an antenna group, the signal represented by the octonion can be transmitted through four antennas in one time slot. Compared with the signal represented by complex numbers, the signal transmission time can be reduced, thereby improving the signal transmission efficiency.

[0191] For example, in this implementation, if the number of transmitting antennas equals the number of receiving antennas, and the number of transmitting antennas is 4, then the first communication device and the second communication device can be understood as communication devices in a 4×4 MIMO system. That is, the first communication device can send signals to the second communication device through an antenna group, each of which includes the four transmitting antennas.

[0192] For example, in this implementation, if the number of transmitting antennas equals the number of receiving antennas, and the number of transmitting antennas is N, where N can be a multiple of 4, then the first communication device and the second communication device can be understood as communication devices in an N×N dimensional MIMO system. That is, the first communication device can... Each of the four antenna groups transmits signals to the second communication device.

[0193] It should be understood that the above-described possible forms of antenna groups are merely illustrative examples to indicate the possible forms of antenna groups on which the first communication device transmits signals when octonions represent signals, and do not constitute any limitation on the scope of protection of this application. For example, the number of transmitting antennas and the number of receiving antennas may be different, and will not be illustrated in detail here.

[0194] Furthermore, it should be understood that the above-mentioned signal transmission method, where the signal is represented by a quaternion or octet, is merely an example and does not constitute any limitation on the scope of protection of this application. The signal can also be represented by other hypercomplex numbers, for example, the signal can be represented by 2... M Atom representation: In an N×N dimensional MIMO system, the communication device, i.e., the first communication device, can... Each antenna group transmits signals to the second communication device. M-1 One transmitting antenna.

[0195] For example, in step S420, the first communication device sending a signal to the second communication device can be: the first communication device carries the signal on a channel and sends the signal after passing through the channel to the second communication device through at least one antenna group. As can be seen from the above, in this application, the signal passes through 2... M Atom representation, the channel can also be represented by 2 M The element representation indicates that the channel consists of a real part channel and 2 M -1 imaginary part of the channel.

[0196] As one possible implementation, the channel can be represented by a quaternion, such as M, which takes the value of 2.

[0197] In this implementation, the channel can be represented as h qv = h1 + h2i + h3j + h4k, where h1 represents a real part channel, h2, h3, h4 represent three imaginary part channels, and i, j, k are imaginary units. Optionally, h1, h2, h3, h4 follow independent and identically distributed real Gaussian random variables.

[0198] Referring to the complex representation of the channel, in this implementation, the channel can be represented as h. qv =h q1 +h q2 j. Optionally, h q1 and h q2 Let h1 and h2 be complex numbers that follow a Rayleigh distribution, where h1 and h2 represent h. q1 The real and imaginary parts, h3 and h4 represent h q2 The real and imaginary parts.

[0199] As one possible implementation, the channel can be represented by an octonion, for example, M can be 3.

[0200] In this implementation, the channel can be represented as h qv= h1 + h2i + h3j + h4k + h5l + h6m + h7p + h8q, where h1 represents a real part channel, and h2, h3, h4, h5, h6, h7, h8 represent seven imaginary part channels, where i, j, k, l, m, p, and q are imaginary units. Optionally, h1, h2, h3, h4, h5, h6, h7, h8 follow independent and identically distributed real Gaussian random variables.

[0201] Referring to the complex representation of the channel, in this implementation, the channel can be represented as h. qv =h q1 +h q2 j+h q3 l+h q4 p. Optionally, h q1 h q2 h q3 and h q4 Let h1 and h2 be complex numbers that follow a Rayleigh distribution, where h1 and h2 represent h. q1 The real and imaginary parts, h3 and h4 represent h q2 The real and imaginary parts, h5 and h6 represent h q3 The real and imaginary parts, h7 and h8 represent h q4 The real and imaginary parts.

[0202] It should be understood that the above-described channel representation using quaternions or octernions is merely an example and does not constitute any limitation on the scope of protection of this application. In this application, the channel can be represented by 2... M In atom representation, M can take the value of an integer greater than 3. For example, a channel can also be represented by a hexadecimal, which will not be elaborated here.

[0203] Furthermore, since the second communication device in this application can process the received signal, the method flow shown in FIG4 may further include:

[0204] S430, the second communication device processes signals.

[0205] Specifically, during the signal processing process of the second communication device in this application, because the signal passes through 2 M Atom representation, and 2 M Atoms possess the algebraic property of allowing conjugation operations to replace matrix inversion operations. Therefore, the second communication device can perform conjugation operations instead of matrix inversion operations during signal processing. Since matrix inversion operations are relatively complex, using conjugation operations instead of matrix inversion operations can reduce the complexity of the signal processing process.

[0206] For example, in step S420 above, the second communication device receiving the signal from the first communication device can be understood as: the second communication device receiving the received signal corresponding to the signal, which can be represented as: y qv =h qv x qv +n qv (2-1)

[0207] In equation (2-1) above, y qv n represents the received signal received by the second communication device. qv h represents noise. qv The channel that carries the signal, x qv Indicates 2 M-1 Signals transmitted from each antenna.

[0208] Alternatively, considering precoding and transmit power normalization, the received signal can be represented as: y qv =β qv h qv p qv x qv +n qv =β qv x qv +n qv (2-2)

[0209] In equation (2-2) above, y qv n represents the received signal received by the second communication device. qv h represents noise. qv The channel that carries the signal, x qv Indicates 2 M-1 The signal transmitted on each antenna, β qv p represents the transmit power normalization factor. qv This indicates the precoding corresponding to the signal.

[0210] It should be understood that precoding in this application refers to steps performed by the transmitting device, such as the first communication device performing a precoding process.

[0211] For ease of description, the following explanation uses the example of representing signals and channels using quaternions. If octonions or hexadecimals are used, the explanation will not be repeated. M Quaternions represent signals and channels. The signal processing method is similar to that when signals and channels are represented by quaternions, which will not be elaborated on below.

[0212] For example, if the signal and channel are represented by quaternions, the received signal received by the second communication device can also be represented by quaternions, and the noise can also be represented by quaternions. For example, the channel can be represented by a quaternion as: h qv =h1+h2i+h3j+h4k=(h1+h2i)+(h3+h4i)j (2-3)

[0213] In equation (2-3) above, (h1+h2i) can be denoted as h (1) (h3+h4i) can be written as h (2) h (1) The element corresponding to the main diagonal of the channel, h (2) The elements corresponding to the off-diagonal elements of the channel. h qv This represents the channel scalar represented by a quaternion.

[0214] x qv Represented using quaternions: x qv =(x1+x2i)+(x3+x4i)j (2-4)

[0215] In equation (2-4) above, (x1+x2i) can be denoted as x (1) (x³ + x⁴i) can be written as x (2) x (1) Let x represent the complex signal corresponding to one of the two transmitting antennas. (2) This represents the complex signal corresponding to the other of the two transmitting antennas. qv This represents a signal scalar represented by a quaternion.

[0216] n qv Represented by quaternions: n qv =(n1+n2i)+(n3+n4i)j (2-5)

[0217] In equation (2-5) above, (n1+n2i) can be denoted as n (1) (n3+n4i) can be written as n (2) n (1) n represents the noise corresponding to one of the two receiving antennas. (2) This represents the noise corresponding to the other of the two receiving antennas. qv This represents a noise scalar represented by a quaternion.

[0218] As an example, and not a limitation, the process of a signal passing through a channel can be modeled as quaternions s and h. qv The product of can be expressed as: sh qv =(s 1r +s1i i+s 2r j+s 2i k)(h1+h2i+h3j+h4k) =(s 1r h1-s 1i h2-s 2r h3-s 2i h4)+(s 1r h2+s 1i h1+s 2r h4-s 2i h3)i +(s 1r h3-s 1i h4+s 2r h1+s 2i h2)j+(s 1r h4+s 1i h3-s 2r h2+s 2i h1)k (2-6)

[0219] Furthermore, as mentioned above, the signal can also be represented as s = s1 + s2j, where s1 and s2 represent complex signals. In this representation, the signal can be represented as a vector s = [s1 s2]. Moreover, referring to the complex-represented channel, the quaternion-represented signal can be represented as h. qv =h q1 +h q2 j, h q1 and h q2 Complex numbers that follow a Rayleigh distribution.

[0220] It should be understood that in the above equation (2-6), s can be interpreted as the modulation symbol, and x qv It can be the same as or different from s, for example, x qv It can be the processed signal of s.

[0221] As shown in Figure 5, for a 2×2 MIMO channel, it can be achieved through h (1) and (h) (1) ) * -h represents the elements on the main diagonal of the complex channel. (2) and (h) (2) ) * Let h represent the off-diagonal elements of the complex channel, and h (1) ,(h (1) ) * ,-h (2) ,(h (2) ) * All are complex numbers distributed by Rayleigh, and the channel can also be represented by a matrix as:

[0222] Therefore, the product of vector s and channel matrix H can also be expressed as:

[0223] In equation (2-8) above, (s1h (1) +s2(h (1) ) * j) can be denoted as A1, (s1h) (1) +s2(h (1) ) * j) can be denoted as A2.

[0224] From equation (2-8) above, we know that sH is the quaternion A1 = s1h on the main diagonal of the channel. (1) +s2(h (1) ) * j and the off-diagonal quaternion of the channel A2 = s1h (1) +s2(h (1) ) * The sum of j.

[0225] For example, a 2×2 MIMO system can be extended to an N×N MIMO system. In an N×N MIMO system, the channel can... The dimensional matrix is ​​represented as: H qv =A + iB + jC + kD (2-9)

[0226] In equation (2-9) above, H qv Let W1 represent the channel matrix, where W1 = [(A+iB)+(C+iD)(A-iB)]. -1 (C-iD)] -1 W2 = (A - iB) -1 (C-iD)W1, where the elements in matrices W1 and W2 are all complex numbers, and the elements in matrices A, B, C, and D are all real numbers.

[0227] In this implementation, the quaternion MIMO channel matrix inversion can be achieved based on the Frobenius inversion (FI). For example, H... qv inverse matrix

[0228] For example, as shown in Figure 6, the first and second communication devices can be communication equipment in a 4×4 MIMO system. This 4×4 MIMO channel is represented as a quaternion 2×2 MIMO channel as follows:

[0229] Among them, the matrix in equation (2-10) above Substituting these values ​​into the formulas for W1 and W2 yields matrices W1 and W2, which in turn leads to... Furthermore, equation (2-10) above represents one channel model. As shown in Figure 6, the channel between the transmitting and receiving antennas can also be represented in other ways. For example, the channel between the first transmitting antenna and the four receiving antennas shown in Figure 6 can be represented as follows: The channel between the fourth transmitting antenna and the four receiving antennas can be represented as follows: It should be understood that the channel is expressed through the parameters shown in Figure 6 and the matrix H in equation (2-10) above. qv The ways of expressing the channel are equivalent, that is, the channel expressed by the parameters shown in Figure 6 can be represented by A+iB+jC+kD.

[0230] It should be understood that the above-described channel behavior is merely an example and does not constitute any limitation on the scope of protection of this application.

[0231] In the communication method shown in Figure 4, the signal acquired by the first communication device can be represented by a hypercomplex number, for example, the signal is represented by 2... M The element M is an integer greater than or equal to 2, meaning that the signal can be represented by a hypercomplex number such as a quaternion, octon, or hexadecimal. Since the hypercomplex number has the algebraic property of using conjugate operations to replace matrix inversion operations, this technical solution can reduce the signal processing complexity to a certain extent compared to the scheme of representing the signal by complex numbers.

[0232] Furthermore, as introduced in the basic concepts above, in wireless communication, modulation, waveforms, channels, and multi-antenna transmission can all be represented using complex numbers. For example, in a MIMO system, the linear precoding process can be represented using complex numbers; similarly, the linear channel equalization process can be represented using complex numbers; and Alamouti coding can be represented using complex numbers in a MIMO system.

[0233] The communication method shown in Figure 4 proposes a hypercomplex representation of signals or channels. It should be understood that hypercomplex representations can also be used for modulation, waveforms, or multi-antenna transmission. The following sections will illustrate, with specific examples, how hypercomplex representations are used in MIMO systems for linear precoding, linear channel equalization, and Alamouti coding.

[0234] Example 1: Alamouti encoding based on quaternions.

[0235] As shown in Figure 3, in a complex MIMO system, Alamouti encoding can be represented as:

[0236] As shown in Equation (3-1), in a complex MIMO system, the channel is represented by a matrix, which is a two-row by two-column matrix. This indicates that Alamouti coding requires two time slots to be transmitted on two antennas. However, as shown in Equation (2-3), the channel is represented by a quaternion, and Alamouti coding can be transmitted on two antennas with different spatial dimensions through a single time slot. Therefore, compared to a complex MIMO system, Alamouti coding in a quaternion MIMO system can approximately save half the time, thus improving the efficiency of Alamouti coding.

[0237] To facilitate understanding, Figure 7 illustrates the difference between complex-based Alamouti coding and quaternion-based Alamouti coding. As shown in Figure 7, the bit error rates (BER) of complex-based and quaternion-based Alamouti coding are essentially the same. However, as mentioned above, the channel is represented by quaternions, allowing Alamouti coding to be transmitted in a single time slot across two antennas with different spatial dimensions. Therefore, for the same BER, quaternion-based Alamouti coding can improve spectral efficiency. The cross-polarization discrimination shown in Figure 7 indicates the degree of polarization, while the cross-polarization discrimination and the "new" cross-polarization discrimination represent two different polarization modes, such as horizontal-vertical polarization and elliptic polarization.

[0238] Example 2: Quaternion-based uplink multi-user (MU) MIMO channel equalization method.

[0239] For example, in a complex-representation-based MIMO system, zero-forcing channel equalization in complex MIMO requires solving for the inverse matrix. For instance, in a 2×2 MIMO system, zero-forcing channel equalization in complex MIMO requires solving for the inverse of the 2×2 channel matrix. As shown in equation (3-2):

[0240] In MIMO systems based on quaternion representation, since quaternions possess the algebraic property of using conjugate operations to replace matrix inversion operations, the quaternion MIMO zero-forcing channel equalization representation for quaternion MIMO systems is as follows:

[0241] Among them, in the above formula (3-3) This represents the signal obtained after zero-forcing channel equalization. h qv The conjugate of |h qv | indicates h qv The model, y qv This refers to the received signal. This represents the signal scalar obtained after zero-forcing channel equalization, expressed in quaternion form.

[0242] As can be seen from equation (3-3) above, in a quaternion-represented MIMO system, zero-forcing channel equalization in quaternion MIMO is achieved by replacing matrix inversion with conjugation. This reduces the complexity of zero-forcing channel equalization.

[0243] Furthermore, the 2×2 MIMO system can be extended to an N×N MIMO system. As shown in equation (2-9), in an N×N MIMO system, the channel can... 3D matrix representation, and in N×N MIMO systems The quaternion-based MIMO channel matrix can be inverted using the Frobenius inverse, reducing the complexity of MIMO zero-forcing channel equalization. The Frobenius inverse implementation of quaternion-based zero-forcing channel equalization can be expressed as:

[0244] Among them, in the above formula (3-4) This represents the signal obtained after zero-forcing channel equalization. H represents qv The inverse matrix, y qv This refers to the received signal. This represents the signal vector obtained after zero-forcing channel equalization.

[0245] It should be understood that the signal obtained after quaternion zero-forcing channel equalization in an N×N MIMO system It can also be understood as a zero-forcing channel equalization vector.

[0246] As one possible implementation, in an N×N MIMO system, signals from a portion of the users can be transmitted in a fixed manner.

[0247] To facilitate understanding, the following example illustrates how zero-forcing channel equalization is represented in a 4×4 MIMO system if the signals of the first two users are transmitted in a fixed manner.

[0248] For example, for a 4×4 uplink MU-MIMO system (4 single-antenna users, 4 antennas at the base station, i.e., 4 transmit antennas and 4 receive antennas), the transmission model can be expressed as equation (3-5):

[0249] From equation (3-5) above, we can see that y represents the received signal, H represents the channel matrix, x represents the transmitted signal, and n represents noise.

[0250] If the signals of the first two users are transmitted in a fixed manner (e.g., x1 and x2), the MU-MIMO system can be represented as a 2×1 dimensional quadrupole MIMO channel matrix as shown in equation (3-6):

[0251] In scenarios where the number of transmit antennas and receive antennas differs, uplink MU-MIMO channel equalization can be achieved using the channel matrix h in equation (3-6). qv The pseudo-inverse is determined. Specifically, in equation (3-6) above, matrix h... qv The steps to solve for the pseudoinverse include:

[0252] Step 1: Calculation

[0253] Step 2: Calculation in Representation matrix Frobenius inverse;

[0254] Step 3: Calculation

[0255] In this implementation, the quadrupole MIMO zero-forcing channel equalization can be expressed as:

[0256] As another possible implementation, the quaternion-based uplink MU-MIMO channel equalization method provided in this application also supports rank adaptation.

[0257] For example, if rank adaptation is adopted, for MU-MIMO uplink transmission, the quaternion MIMO channel H corresponding to the l-th user... qv,l The singular value decomposition is represented as:

[0258] In equation (3-7) above, H qv,l Σ represents the channel of the l-th user. l Indicates channel H qv,l The singular value matrix, U l Indicates channel H qv,l The left singular matrix, V l Indicates channel H qv,l The right singular matrix is ​​given, where L represents the number of users and l represents the user index, where l is a positive integer less than or equal to L. In this application, the l-th user can be a user with index l, such as L users numbered from 1 to L; or, the l-th user can be a user with index l-1, such as L users numbered from 0 to L-1; or, the index of the l-th user can be in other forms, which will not be illustrated here.

[0259] A quaternion MU-MIMO channel can be represented as: In this implementation, the quadrupole MIMO zero-forcing channel equalization can be expressed as:

[0260] Among them, in the above formula (3-8) This represents the signal obtained after zero-forcing channel equalization. H represents qv The inverse matrix, y qv This indicates the received signal. H represents qv The conjugate transpose of . This represents the signal vector obtained after zero-forcing channel equalization.

[0261] It should be understood that the minimum mean square error channel equalization process also requires matrix inversion. Therefore, the computational complexity of the quaternion-based uplink MU-MIMO equalization process is lower than that of the complex number-based channel equalization process, which will not be elaborated here.

[0262] To facilitate understanding, Figure 8 illustrates the differences between complex-based uplink MU-MIMO equalization and quaternion-based uplink MU-MIMO equalization. As shown in Figure 8, quaternion-based uplink MU-MIMO equalization outperforms complex-based uplink MU-MIMO equalization. Quaternion-based uplink MU-MIMO equalization improves transmission reliability, reduces computational complexity, and supports rank adaptation.

[0263] Example 3: A downlink MU-MIMO precoding method based on quaternions.

[0264] As shown in Equation (3-2) above, for complex MIMO zero-forcing precoding, it is necessary to solve for the inverse of the 2×2 matrix and normalize the transmit power.

[0265] As shown in equation (2-9) above, in complex MIMO systems, for complex MIMO zero-forcing channel equalization or zero-forcing precoding, it is necessary to solve for the inverse of the channel matrix.

[0266] In MIMO systems based on quaternion representation, since quaternions possess the algebraic property of using conjugate operations to replace matrix inversion operations, the quaternion MIMO zero-forcing precoding representation for quaternion MIMO systems is as follows:

[0267] In equation (3-9) above, p qv Indicates zero-forcing precoding, h qv The conjugate of |h qv | indicates h qv The model. p qv This represents the zero-forcing precoding scalar in quaternion representation.

[0268] Transmit power normalization factor N t Indicates the number of transmitting antennas. The transmitted signal is represented as... As can be seen, quaternion conjugation replaces matrix inversion, reducing the complexity of zero-forcing precoding.

[0269] Extending the 2×2 MIMO system to an N×N MIMO system, a Frobenius inverse implementation of the quaternion MIMO channel matrix inversion is proposed, reducing the complexity of MIMO zero-forcing precoding. Downlink MU-MIMO transmission can be modeled as: y qv =β qv H qv P qv x qv +n qv =β qv x qv +n qv (3-10)

[0270] In equation (3-10) above, y qv Indicates the received signal, β qv H represents the transmit power normalization factor. qv express 4D quaternion channel, P qv Let x represent the precoding matrix. qv Indicates sending a signal, n qv This represents noise. Where H... qv P qv The value is Given an identity matrix I, it can be seen from equation (3-10) that downlink MU-MIMO transmission can be modeled as: y qv =β qv x qv +n qv P qv This represents the zero-forcing precoding matrix.

[0271] As can be seen from the description of the channel matrix in an N×N MIMO system above, for 4D Quaternion Channel H qv =A + iB + jC + kD, the corresponding inverse matrix It can be represented as Therefore, referring to the description in equation (2-9) above and the relationship between the channel matrix and the precoding matrix, it can be seen that for the precoding matrix, quaternion zero-forcing precoding can be implemented by performing the Frobenius inverse on the channel matrix. For example, the precoding matrix can be represented as:

[0272] In equation (3-11) above, P qvRepresents the zero-forcing precoding matrix. H represents qv The inverse matrix.

[0273] Transmit power normalization factor N t This indicates the number of transmitting antennas. The received signal is represented as:

[0274] To facilitate understanding, the following example illustrates the flow of the quaternion-based downlink MU-MIMO precoding method in this application.

[0275] For example, a complex 8×8 MIMO channel can be represented as a quaternion 4×4 MIMO channel as follows:

[0276] Among them, the matrix in equation (3-13) above Substitute matrices A, B, C, and D into W1 = [(A + iB) + (C + iD)(A - iB)] -1 (C-iD)] -1 W2 = (A - iB) -1 (C-iD)W1 yields matrices W1 and W2, which in turn lead to...

[0277] As one possible implementation, the quaternion-based downlink MU-MIMO precoding method provided in this application also supports rank adaptation. For example, if rank adaptation is used, the quaternion received signal for MU-MIMO downlink transmission can be represented as: y qv =β qv H qv P qv x qv +n qv (3-14)

[0278] The l-th user quaternion MIMO channel H qv,l The singular value decomposition is represented as:

[0279] In equation (3-15) above, H qv,l Σ represents the channel of the l-th user. l Indicates channel H qv,l The singular value matrix, U l Indicates channel H qv,l The left singular matrix, V l Indicates channel H qvlThe right singular matrix is ​​given by , where L represents the number of users, l represents the user index, and l is a positive integer less than or equal to L. A quaternion MU-MIMO channel can be represented as... In this implementation, quadruplet MIMO zero-forcing precoding can be represented as: P qv =[p qv,1 ,…,p qv,l ,…,p qv,L ], p qv,l =U l (:,1:r l (3-16)

[0280] In equation (3-16) above, p qv,l U represents the zero-forcing precoding of the l-th user. l (:,1:r l ) represents matrix U l The front r l column, r l Represents the quaternion channel H qv,l The rank (the transport layer number of the l-th user). p qv,l Represents matrix U l The front r l Column, transmit power normalization factor P qv p represents the zero-forcing precoding matrix. qv,l This represents the zero-forcing precoding matrix for the l-th user.

[0281] It should be understood that the minimum mean square error precoding process also requires matrix inversion. Therefore, the computational complexity of the quaternion-based uplink MU-MIMO precoding process is lower than that of the complex number-based precoding process, which will not be elaborated here.

[0282] To facilitate understanding, Figure 9 illustrates the differences between complex-based and quaternion-based downlink MU-MIMO precoding. As shown in Figure 9, quaternion-based downlink MU-MIMO precoding outperforms complex-based downlink MU-MIMO precoding. Quaternion-based downlink MU-MIMO precoding improves transmission reliability, reduces computational complexity, and supports rank adaptation.

[0283] It should be understood that the sequence number of each process does not imply the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of this application.

[0284] It should also be understood that, in the various embodiments of this application, unless otherwise specified or in case of logical conflict, the terms and / or descriptions between different embodiments are consistent and can be referenced by each other, and the technical features in different embodiments can be combined to form new embodiments according to their inherent logical relationships.

[0285] It should also be understood that in some of the above embodiments, the examples are mainly based on devices in existing network architectures (such as the first communication device, the second communication device, etc.). It should be understood that the specific form of the device is not limited in the embodiments of this application. For example, any device that can achieve the same function in the future is applicable to the embodiments of this application.

[0286] It is understood that in the above-described method embodiments, the methods and operations implemented by devices (such as the first communication device, the second communication device, etc.) can also be implemented by components of the devices (such as chips or circuits).

[0287] The communication method provided by the embodiments of this application has been described in detail above with reference to Figure 4. The above communication method is mainly described from the perspective of the interaction between a first communication device and a second communication device. It is understood that, in order to achieve the above functions, the first communication device and the second communication device include hardware structures and / or software modules corresponding to the execution of each function.

[0288] Those skilled in the art will recognize that, based on the units and algorithm steps described in conjunction with the embodiments disclosed herein, this application can be implemented in hardware or a combination of hardware and computer software. Whether a function is implemented in hardware or by computer software driving hardware depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of this application.

[0289] The communication device provided in this application is described in detail below with reference to Figures 10 to 12. It should be understood that the description of the device embodiments corresponds to the description of the method embodiments. Therefore, for details not described in detail, please refer to the method embodiments above; for brevity, some details are not repeated.

[0290] This application embodiment can divide the transmitting or receiving device into functional modules according to the above method examples. For example, each function can be divided into its own functional modules, or two or more functions can be integrated into one processing module. The integrated module can be implemented in hardware or as a software functional module. It should be noted that the module division in this application embodiment is illustrative and only represents one logical functional division. In actual implementation, there may be other division methods. The following description uses the division of functional modules according to each function as an example.

[0291] Figure 10 is a schematic block diagram of a communication device 10 provided in an embodiment of this application. The device 10 includes a transceiver module 11 and a processing module 12. The transceiver module 11 can implement corresponding communication functions, and the processing module 12 is used for data processing. In other words, the transceiver module 11 is used to perform operations related to receiving and sending, while the processing module 12 is used to perform other operations besides receiving and sending. The transceiver module 11 can also be referred to as a communication interface or a communication unit.

[0292] In one possible implementation, the device 10 may further include a storage module 13, which can be used to store instructions and / or data. The processing module 12 can read the instructions and / or data in the storage module to enable the device to perform the actions of the device in the aforementioned method embodiments.

[0293] In one design, the device 10 may correspond to the first communication device in the above method embodiments, or to a component of the first communication device (such as a chip).

[0294] The device 10 can implement the steps or processes corresponding to those performed by the first communication device in the above method embodiment. The transceiver module 11 can be used to perform the transceiver-related operations of the first communication device in the above method embodiment, and the processing module 12 can be used to perform the processing-related operations of the first communication device in the above method embodiment.

[0295] In one possible implementation, processing module 12 is used to obtain data via 2 M The signal is represented by an atom, the signal comprising a real part and 2. M -1 imaginary part signal. Transceiver module 11, for transmitting the signal through at least one antenna group, each antenna group including 2 M-1 There are 1 antenna, where M is an integer greater than or equal to 2.

[0296] When the device 10 is used to execute the method in FIG4, the transceiver module 11 can be used to execute the steps of sending and receiving information in the method, such as step S420; the processing module 12 can be used to execute the processing steps in the method, such as step S410.

[0297] It should be understood that the specific process of each unit performing the above-mentioned corresponding steps has been described in detail in the above method embodiments, and will not be repeated here for the sake of brevity.

[0298] In another design, the device 10 may correspond to the second communication device in the above method embodiment, or to a component of the second communication device (such as a chip).

[0299] The device 10 can implement the steps or processes corresponding to those performed by the second communication device in the above method embodiments. The transceiver module 11 can be used to perform transceiver-related operations of the second communication device in the above method embodiments, and the processing module 12 can be used to perform processing-related operations of the second communication device in the above method embodiments.

[0300] In one possible implementation, the transceiver module 11 is configured to receive signals via at least one antenna group, each of which includes 2 antennas. M-1 One antenna. Processing module 12, used to process the signal, the signal passing through 2... M The atom representation, the signal comprising a real part signal and 2 M -1 is an imaginary part signal, where M is an integer greater than or equal to 2.

[0301] When the device 10 is used to execute the method in FIG4, the transceiver module 11 can be used to execute the steps of sending and receiving information in the method, such as step S420; the processing module 12 can be used to execute the processing steps in the method, such as step S430.

[0302] It should be understood that the specific process of each unit performing the above-mentioned corresponding steps has been described in detail in the above method embodiments, and will not be repeated here for the sake of brevity.

[0303] It should also be understood that the device 10 here is embodied in the form of a functional module. The term "module" here can refer to an application-specific integrated circuit (ASIC), electronic circuitry, a processor (e.g., a shared processor, a proprietary processor, or a group processor, etc.) and memory for executing one or more software or firmware programs, integrated logic circuitry, and / or other suitable components supporting the described functions. In an alternative example, those skilled in the art will understand that device 10 may be specifically a first communication device in the above embodiments, used to execute the various processes and / or steps corresponding to the first communication device in the above method embodiments; or, device 10 may be specifically a second communication device in the above embodiments, used to execute the various processes and / or steps corresponding to the second communication device in the above method embodiments.

[0304] The apparatus 10 of each of the above-described schemes has the function of implementing the corresponding steps performed by the devices (such as the first communication device and the second communication device) in the above-described methods. This function can be implemented by hardware or by hardware executing corresponding software. The hardware or software includes one or more modules corresponding to the above-described functions; for example, the transceiver module can be replaced by a transceiver (for example, the transmitting unit in the transceiver module can be replaced by a transmitter, and the receiving unit in the transceiver module can be replaced by a receiver), and other units, such as processing modules, can be replaced by processors, which respectively execute the transceiver operations and related processing operations in each method embodiment.

[0305] In addition, the transceiver module 11 can also be a transceiver circuit (for example, it may include a receiving circuit and a transmitting circuit), and the processing module can be a processing circuit.

[0306] Figure 11 is a schematic diagram of another communication device 20 provided in an embodiment of this application. The device 20 includes a processor 21, which is used to execute computer programs or instructions stored in a memory 22, or to read data / signaling stored in the memory 22, to perform the methods in the above-described method embodiments. In one possible implementation, the processor 21 may be one or more.

[0307] As shown in Figure 11, one possible implementation of the device 20 includes a memory 22 for storing computer programs or instructions and / or data. The memory 22 may be integrated with the processor 21 or it may be separate. In another possible implementation, there may be one or more memories 22.

[0308] As shown in Figure 11, one possible implementation of the device 20 includes a transceiver 23 for receiving and / or transmitting signals. For example, a processor 21 controls the transceiver 23 to receive and / or transmit signals.

[0309] As one approach, the device 20 is used to implement the operations performed by the first communication device and the second communication device in the various method embodiments described above.

[0310] It should be understood that the processor mentioned in the embodiments of this application can be a central processing unit (CPU), or other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. A general-purpose processor can be a microprocessor or any conventional processor.

[0311] It should also be understood that the memory mentioned in the embodiments of this application can be volatile memory and / or non-volatile memory. Non-volatile memory can be read-only memory (ROM), programmable read-only memory (PROM), erasable programmable read-only memory (EPROM), electrically erasable programmable read-only memory (EEPROM), or flash memory. Volatile memory can be random access memory (RAM). For example, RAM can be used as an external cache. By way of example and not limitation, RAM includes the following forms: static random access memory (SRAM), dynamic random access memory (DRAM), synchronous dynamic random access memory (SDRAM), double data rate synchronous dynamic random access memory (DDR SDRAM), enhanced synchronous dynamic random access memory (ESDRAM), synchronous linked dynamic random access memory (SLDRAM), and direct rambus RAM (DR RAM).

[0312] It should be noted that when the processor is a general-purpose processor, DSP, ASIC, FPGA, or other programmable logic device, discrete gate or transistor logic device, or discrete hardware component, the memory (storage module) can be integrated into the processor.

[0313] It should also be noted that the memory described herein is intended to include, but is not limited to, these and any other suitable types of memory.

[0314] Figure 12 is a schematic diagram of a chip system 30 provided in an embodiment of this application. The chip system 30 (or may also be called a processing system) includes logic circuitry 31 and an input / output interface 32.

[0315] The logic circuit 31 can be a processing circuit in the chip system 30. The logic circuit 31 can be coupled to a memory unit, calling instructions from the memory unit, enabling the chip system 30 to implement the methods and functions of the embodiments of this application. The input / output interface 32 can be an input / output circuit in the chip system 30, outputting processed information from the chip system 30, or inputting data or signaling information to be processed into the chip system 30 for processing.

[0316] As one approach, the chip system 30 is used to implement the operations performed by the first communication device and the second communication device in the various method embodiments described above.

[0317] For example, logic circuit 31 is used to implement the processing-related operations performed by the first communication device and the second communication device in the above method embodiment; input / output interface 32 is used to implement the sending and / or receiving-related operations performed by the first communication device and the second communication device in the above method embodiment.

[0318] This application also provides a computer-readable storage medium storing computer instructions for implementing the methods executed by the first communication device and the second communication device in the above-described method embodiments.

[0319] For example, when the computer program is executed by the computer, it enables the computer to implement the methods executed by the first communication device and the second communication device in the various embodiments of the above methods.

[0320] This application also provides a computer program product comprising instructions that, when executed by a computer, implement the methods performed by the first communication device and the second communication device in the above-described method embodiments.

[0321] This application also provides a communication system, including the aforementioned first communication device and second communication device.

[0322] The explanations and beneficial effects of the relevant contents in any of the devices provided above can be found in the corresponding method embodiments provided above, and will not be repeated here.

[0323] Those skilled in the art will recognize that the units and algorithm steps of the various examples described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of this application.

[0324] Those skilled in the art will understand that, for the sake of convenience and brevity, the specific working processes of the systems, devices, and units described above can be referred to the corresponding processes in the foregoing method embodiments, and will not be repeated here.

[0325] In the several embodiments provided in this application, it should be understood that the disclosed systems, apparatuses, and methods can be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative; for instance, the division of units 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 apparatuses or units may be electrical, mechanical, or other forms.

[0326] The units described 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.

[0327] In addition, the functional units in the various embodiments of this application can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit.

[0328] If the aforementioned functions are implemented as software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, or a portion of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of this application. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0329] The above description is merely a specific embodiment of this application, but the scope of protection of this application is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in this application should be included within the scope of protection of this application. Therefore, the scope of protection of this application should be determined by the scope of the claims.

Claims

1. A communication method, characterized in that, include: Get through 2 M The signal is represented by an atom, the signal comprising a real part and 2. M -1 imaginary part signal; The signal is transmitted through at least one antenna group, each antenna group comprising 2 M-1 One antenna, Where M is an integer greater than or equal to 2.

2. A communication method, characterized in that, include: Signals are received through at least one antenna group, each antenna group comprising 2 M-1 One antenna; Process the signal, the signal through 2 M The atom representation, the signal comprising a real part signal and 2 M -1 is an imaginary part signal, where M is an integer greater than or equal to 2.

3. The method according to claim 1 or 2, characterized in that, When M is 2, the signal includes one real part and three imaginary parts, and each of the at least one antenna group includes a first antenna and a second antenna. Wherein, the real number part signal is carried by the in-phase component of the continuous signal transmitted on the first antenna, and the three imaginary number part signals are carried by the quadrature component of the continuous signal transmitted on the first antenna, and the in-phase component and quadrature component of the continuous signal transmitted on the second antenna, respectively; or, the real number part signal is carried by the quadrature component of the continuous signal transmitted on the first antenna, and the three imaginary number part signals are carried by the in-phase component of the continuous signal transmitted on the first antenna, and the in-phase component and quadrature component of the continuous signal transmitted on the second antenna, respectively.

4. The method according to any one of claims 1 to 3, characterized in that, The signal is carried in a channel, and the channel passes through the 2 M The channel is represented by a number symbol, comprising a real part channel and 2. M -1 imaginary part of the channel.

5. The method according to any one of claims 1 to 4, characterized in that, The received signal corresponding to the signal is represented as follows: y qv = h qv x qv + n qv ; or, y qv = β qv h qv p qv x qv + n qv = β qv x qv + n qv Among them, y qv Indicates the received signal, n qv h represents noise. qv x represents the channel carrying the signal. qv Indicates the 2 M-1 The signal transmitted on each antenna, β qv p represents the transmit power normalization factor. qv This indicates the precoding corresponding to the signal.

6. The method according to claim 5, characterized in that, When the number of transmitting antennas equals the number of receiving antennas, and the number of transmitting antennas is 2, The channel is represented by a quaternion as: h qv =h1+h2i+h3j+h4k=(h1+h2i)+(h3+h4i)j, The x qv Represented by quaternions: x qv =(x1+x2i)+(x3+x4i)j, The n qv Represented by quaternions: n qv =(n1+n2i)+(n3+n4i)j, Where h1 represents a real part channel, h2, h3, h4 represent three imaginary part channels, x1+x2i represents the complex signal corresponding to one of the two transmit antennas, x3+x4i represents the complex signal corresponding to the other of the two transmit antennas, n1+n2i represents the noise corresponding to one of the two receive antennas, and n3+n4i represents the noise corresponding to the other of the two receive antennas.

7. The method according to claim 6, characterized in that, The zero-forcing channel equalization corresponding to the signal is represented as follows: in, This represents the signal obtained after zero-forcing channel equalization. h qv The conjugate of |h qv | indicates h qv The model.

8. The method according to claim 6, characterized in that, The p qv Indicates zero-forcing precoding: in, h qv The conjugate of |h qv | indicates h qv The model, the p qv The conjugate of N t This indicates the number of transmitting antennas.

9. The method according to claim 5, characterized in that, When the number of transmit antennas equals the number of receive antennas, and the number of transmit antennas is N, where N is an integer greater than 2, the channel passes through... The dimensional matrix is ​​represented as: H qv =A + iB + jC + kD, Among them, H qv inverse matrix W1=[(A+iB)+(C+iD)(A-iB) -1 (C-iD)] -1 W2 = (A - iB) -1 (C-iD)W1, where the elements in matrices W1 and W2 are all complex numbers, and the elements in matrices A, B, C, and D are all real numbers.

10. The method according to claim 9, characterized in that, The zero-forcing channel equalization corresponding to the signal is represented as follows: or, in, This represents the signal obtained after zero-forcing channel equalization. H represents qv The inverse matrix, y qv This indicates the received signal. H represents qv The conjugate transpose of .

11. The method according to claim 9, characterized in that, The P qv Indicates zero-forcing precoding: or, p qv,l =U l (:,1:r l ) Where, p qv,l This represents the zero-forcing precoding for the l-th user. H represents qv The inverse matrix of U, where L represents the number of users, l represents the user index, and l is a positive integer less than or equal to L. l (:,1:r l ) represents matrix U l The front r l The column, the r l H represents the channel of the l-th user. qv,l The rank, the N t This indicates the number of transmit antennas, and Tr(·) represents the trace of the matrix. P represents qv The conjugate transpose of the channel H of the l-th user qv,l The singular value decomposition is represented as: Where, Σ l H represents qv,l The singular value matrix, U l H represents qv,l The left singular matrix, V l H represents qv,l The right singular matrix.

12. A communication device, characterized in that, The device includes: Processing unit, used to obtain via 2 M The signal is represented by an atom, the signal comprising a real part and 2. M -1 imaginary part signal; Transceiver unit for transmitting the signal via at least one antenna group, each antenna group comprising 2 M-1 One antenna, Where M is an integer greater than or equal to 2.

13. A communication device, characterized in that, The device includes: Transceiver unit for receiving signals via at least one antenna group, each antenna group comprising 2 M-1 One antenna; A processing unit is configured to process the signal, the signal being transmitted through 2... M The atom representation, the signal comprising a real part signal and 2 M -1 imaginary part signal, Where M is an integer greater than or equal to 2.

14. A communication device, characterized in that, include: A processor is configured to execute a computer program stored in a memory to cause the apparatus to perform the method as claimed in any one of claims 1 to 3 to 11; or to cause the apparatus to perform the method as claimed in any one of claims 2 to 11.

15. A computer program product, characterized in that, The computer program product includes instructions for performing the method as described in any one of claims 1 to 11.

16. A computer-readable storage medium, characterized in that, include: The computer-readable storage medium stores a computer program; when the computer program is run on a computer, it causes the computer to perform the method as described in any one of claims 1 to 11.

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