Communication method and communication apparatus

Abstract

The present application relates to the technical field of wireless communications. Disclosed are a communication method and a communication apparatus. The method comprises: a network device obtaining channel characteristic information of J users, wherein J is a positive integer; determining information of K user groups on the basis of the channel characteristic information of the J users, wherein the number of users in a kth user group among the K user groups is J'k, K and J'k are positive integers, and k is an integer from 1 to K; determining frequency-domain resources of the J users on the basis of performance indicator information and the information of the K user groups, wherein the performance indicator information is used for indicating a demand priority of communication and a demand priority of sensing; and determining a target pre-coded code on the basis of the frequency-domain resources of the J users and the information of the K user groups, wherein the target pre-coded code comprises a user-level pre-coded code and a user-group-level pre-coded code, and the frequency-domain resources of the J users and the target pre-coded code are used for communication between a network device and the J users. The method not only enables efficient integration of a communication function and a sensing function, but also achieves a low implementation complexity.

Description

A communication method and a communication device

[0001] Cross-references to related applications

[0002] This application claims priority to Chinese Patent Application No. 202510084439.5, filed on January 17, 2025, entitled "A Communication Method and Communication Device", the entire contents of which are incorporated herein by reference. Technical Field

[0003] This application relates to the field of wireless communication technology, and in particular to a communication method and a communication device. Background Technology

[0004] Integrated sensing and communication (ISAC), as one of the important candidate technologies for future mobile communications, can fully share the spatial, temporal, and frequency resources of wireless communication and radar sensing, achieving coexistence, mutual assistance, and shared benefits. Common multiple access methods in ISAC include orthogonal multiple access (OMA) and non-orthogonal multiple access (NOMA). OMA allocates a single radio resource to a single user, eliminating interference between different users, but resulting in lower spectral efficiency. NOMA can allocate the same resource to multiple users, leading to interference between different users, but with higher spectral efficiency.

[0005] In ISAC systems, the communication and sensing functions have different requirements and compete for limited resources. Therefore, a balanced approach is needed to address the performance challenges of both. However, current ISAC implementations have certain limitations. For example, OMA-ISAC technology can suppress mutual interference between communication and sensing functions, but it suffers from poor adaptability and low spectrum utilization in dynamic environments. Furthermore, the high correlation between communication and sensing channels leads to significant performance degradation in OMA-ISAC. NOMA-ISAC technology can significantly improve the resource utilization efficiency of wireless systems, achieving efficient resource sharing between sensing and communication through flexible resource allocation, and suppressing mutual interference between the two functions through interference management strategies. However, its design complexity is high, requiring complex interference cancellation.

[0006] Therefore, how to improve the performance of the integrated communication and sensing system with lower complexity has become an urgent problem to be solved. Summary of the Invention

[0007] This application provides a communication method and a communication device for improving the performance of a communication-sensing integrated system with lower complexity.

[0008] In a first aspect, embodiments of this application provide a communication method. This method can be executed by a network device, or by a component in the communication device (e.g., a processor, chip, or chip system), or it can be a logic module or software capable of implementing all or part of the functions of the communication device; this application does not limit this. For example, in the method provided in the first aspect, the network device obtains channel characteristic information of J users; J is a positive integer; then, the network device determines information of K user groups based on the channel characteristic information of the J users; the number of users in the kth user group among the K user groups is J′. k ;K and J′ k It is a positive integer. k takes an integer from 1 to K; next, the network device determines the frequency domain resources of J users based on the performance index information and the information of K user groups; the performance index information is used to indicate the priority of communication needs and the priority of perception needs; the network device then determines the target precoding based on the frequency domain resources of J users and the information of K user groups; the target precoding consists of user-level precoding and user group-level precoding, and the frequency domain resources of J users and the target precoding are used for communication between the network device and J users.

[0009] In this application, after the network device obtains the channel characteristic information of J users, it can divide the J users into K user groups based on the channel characteristic information, determine the information of the K user groups, and then flexibly allocate resources to the J users according to the priority of communication needs, the priority of sensing needs, and the information of the K user groups. This allows for a trade-off between sensing performance (e.g., sensing accuracy) and communication performance. Furthermore, the target precoding in this embodiment consists of user-level precoding and user group-level precoding. User group-level precoding can be used to eliminate interference between user groups, while user-level precoding can be used to improve the communication performance of users within a user group (e.g., maximizing speed). Therefore, this scheme can support communication for a large number of users and can achieve efficient integration of communication and sensing functions with low complexity, thus improving the performance of the integrated communication and sensing system.

[0010] In conjunction with the first aspect, in one possible implementation, the network device determines the information of K user groups based on the channel characteristic information of J users. This includes: determining the number of user groups K based on the channel data in the channel characteristic information of the J users; and performing clustering processing using a clustering algorithm based on the channel data of the J users to divide the J users into K user groups and obtain the information of the K user groups. This implementation method allows for the division of J users into K user groups and the acquisition of information for the K user groups, facilitating subsequent effective resource allocation.

[0011] In conjunction with the first aspect, in one possible implementation, K and J′ k When the integer value is greater than 1, the channel characteristics of users in different user groups within the K user groups exhibit low correlation, while the channel characteristics of different users within the same user group within the K user groups exhibit high correlation. This implementation divides J users into K user groups, limiting the number of users in each group. The high correlation between the channels of different users within the same user group facilitates subsequent elimination of interference between users within the same group. Furthermore, ensuring low correlation or dissimilarity in the channels of users in different user groups reduces mutual interference between users in different user groups.

[0012] In conjunction with the first aspect, in one possible implementation, the method further includes: the network device obtaining N frequency domain resources to be allocated; N being a positive integer; the network device determining the frequency domain resources of J users based on performance index information and information of K user groups, including: determining the frequency domain resources of J users based on performance index information, information of K user groups, and N frequency domain resources.

[0013] In conjunction with the first aspect, in one possible implementation, the priority of communication needs is higher than the priority of perception needs; the network device determines the frequency domain resources for J users based on performance index information, information on K user groups, and N frequency domain resources, including: for J′ in the k-th user group k One user, determine J′ k For each of the N users, the channel gain across N frequency domain resources is calculated, and the d frequency domain resources with the largest channel gains are selected as the user's frequency domain resources; d is a positive integer less than N; where J′ k Any two users in a given user group have d distinct or partially identical frequency domain resources, and the number of users corresponding to each of the N frequency domain resources does not exceed a predetermined threshold. Through this implementation, for any user group J′... k For each user, based on the channel gain of each user across N frequency domain resources, the d frequency domain resources with the largest channel gain can be selected as the user's frequency domain resources, thereby helping to ensure the user's communication performance.

[0014] In conjunction with the first aspect, in one possible implementation, the priority of perception requirements is higher than that of communication requirements; the network device determines the frequency domain resources for J users based on performance index information, information of K user groups, and N frequency domain resources, including: first obtaining the perception weights of the N frequency domain resources; then, for J′ in the k-th user group... k A user, based on N frequency domain resources and J′ k Given the number d of frequency domain resources corresponding to each of the N users, determine q allocation methods; where each allocation method corresponds to d frequency domain resources out of N frequency domain resources; q is greater than or equal to J′. k The integer; then, based on the perception weights of the N frequency domain resources, determine the allocation priority of the q allocation methods; and then, based on the allocation priorities of the q allocation methods, select J′ with the highest allocation priority from the q allocation methods. k Allocation method; and according to J′ k The allocation method determines J′ k Frequency domain resources for each user.

[0015] This implementation method allows for the determination of the priorities of q different allocation methods based on the perceived weights of N frequency domain resources. Each allocation method corresponds to d frequency domain resources out of the N resources, and then the highest priority J′ is selected. k There are several allocation methods, and the highest priority J′ will be assigned to one of them. k The frequency domain resources corresponding to the different allocation methods are J′ k Frequency domain resources are allocated to each user, which effectively guarantees sensing performance.

[0016] In conjunction with the first aspect, in one possible implementation, the priority of communication requirements is the same as the priority of perception requirements; the network device determines the frequency domain resources for J users based on performance index information, information on K user groups, and N frequency domain resources, including:

[0017] For J′ in the k-th user group k One user, determine J′ k Channel gain for each of the N users across N frequency domain resources;

[0018] Based on the perceived weights of N frequency domain resources, determine the expected number of allocations for the N frequency domain resources;

[0019] According to J′ k The channel quality index of each user is used to identify users with poor channel quality.

[0020] For users with poor channel quality, the user's frequency domain resources are determined based on the user's channel gain across N frequency domain resources, the expected number of allocations for the N frequency domain resources, and a first allocation rule; wherein the first allocation rule includes one or more of the following:

[0021] Prioritize the desired number of allocations for the frequency domain resource with the highest perception weight, select the frequency domain resource with high channel gain from N frequency domain resources, or select the frequency domain resource with high channel gain from the remaining frequency domain resources other than the frequency domain resource with the highest perception weight from N frequency domain resources.

[0022] The channel quality index of the aforementioned user can be the root mean square of the sum of the channel gains of the user across N frequency domain resources.

[0023] This implementation method can effectively adjust the allocated resources for users with poor channel quality, which not only meets the needs of perception but also helps to ensure communication performance.

[0024] In conjunction with the first aspect, in one possible implementation, the method further includes: targeting J′ k For users other than those with poor channel quality, the network device selects d frequency domain resources with the largest channel gains from the N frequency domain resources based on the user's channel gain across N frequency domain resources; d is a positive integer less than N. Through this implementation, for any group J′ k For users other than those with poor channel quality, this helps ensure their communication performance.

[0025] For example, the perceptual weights of the above N frequency domain resources conform to the following formula:

[0026] Where, ρ n P represents the sensing weight of the nth frequency domain resource out of N frequency domain resources. n This represents the target effective sensing power of the nth frequency domain resource out of N frequency domain resources, where n is an integer from 1 to N, / is a division operation, and Σ is a summation operation.

[0027] In conjunction with the first aspect, in one possible implementation, the network device determines the target precoding based on the frequency domain resources of J users and the information of K user groups, including: adjusting the preset user-level precoding based on the frequency domain resources of J users to obtain user-level precoding; determining user group-level precoding based on the information of K user groups; and obtaining the target precoding based on the target user-level precoding and the user group-level precoding.

[0028] For example, target precoding can conform to the following formula:

[0029] Among them, w jk (n) represents the target precoding of the nth frequency domain resource of the jth user in the kth user group; v jk (n) represents the target user-level precoding of the nth frequency domain resource of the jth user in the kth user group. B k (n) represents the user group-level precoding corresponding to the nth frequency domain resource of the kth user group. M represents the number of transmitting antennas on the network device, and a represents the transmission degrees of freedom. ∈ is any symbol, and ∈ is the symbol belonging to.

[0030] In conjunction with the first aspect, in one possible implementation, the aforementioned v jk (n) Maximize the sum and rate, v, under preset constraints. jk (n) satisfies the following formula:

[0031] The preset constraints include one or more of the following constraints:

[0032] First constraint: Where, γ j,k r represents the transmission rate of the j-th user (or any user) in the k-th user group. min N represents the minimum transmission rate. j,k This represents the set of frequency domain resources occupied by the j-th user (or any user) in the k-th user group. Target user group-level precoding is used to eliminate user group-level interference. γ jk (n) satisfies the following formula:

[0033] Among them, h jk (n) represents the channel response of the j-th user in the k-th user group on the n-th frequency domain resource. This represents the interference within the k-th user group. Based on information from K user groups, It is represented as the average noise power within the k-th user group.

[0034] Second constraint: in, P represents the effective sensing power on the nth frequency domain resource. n This represents the preset power threshold for the nth frequency domain resource. Let a represent the covariance matrix of the integrated communication and sensing waveform transmitted on the nth frequency domain resource. n (·) represents the steering vector on the nth frequency domain resource, θ l Indicates the angle of the l-th diameter;

[0035] Third constraint: ∑ n ∑ k ∑ j ||w jk (n)‖ 2 ≤P t , where ∑ n ∑ k ∑ j ||w jk (n)‖ 2 For the total transmit power, P t This is the preset power threshold.

[0036] In conjunction with the first aspect, in one possible implementation, the aforementioned B k (n) satisfies the following formula: B k (n)=[u r+1,k (n),u r+2,k (n),…,u M,k (n)];

[0037] make For the preset block diagonalization precoding, B k (n) is The zero space, for Singular value decomposition yields U k (n) is The left singular vector, for The right singular vector, B k (n) is composed of and The system consists of the left singular vector U corresponding to singular values ​​of zero; M represents the number of transmit antennas of the network device, and r represents... The rank, i.e. the number of data streams.

[0038] Secondly, embodiments of this application also provide a communication device that can be used to perform the method of the first aspect.

[0039] In one possible implementation, the communication device may include modules or units corresponding to the methods / operations / steps / actions described in the first aspect. These modules or units may be hardware circuits, software, or a combination of hardware circuits and software. In another possible implementation, the communication device may include a processing unit (also called a processing module) and a communication unit (also called a communication module). The communication unit may be used to perform receiving and / or sending functions, and the processing unit may be used to perform the methods described in the first aspect or any of the possible implementations of the first aspect.

[0040] Thirdly, embodiments of this application provide a communication device, which includes a processor and an input / output interface (or communication interface); wherein the input / output interface (or communication interface) is used for inputting and / or outputting information; and the processor is used to implement the method provided by the first aspect or any of the possible implementations described above.

[0041] In one possible design, the communication device may further include a memory for storing a computer program that, when executed by the processor, causes the method provided by the first aspect or any of the possible implementations therein to be performed.

[0042] In one possible design, the communication device described in the third aspect can be a chip.

[0043] Fourthly, embodiments of this application provide a communication system including a network device for implementing the method provided in the first aspect or any of its possible implementations. Optionally, the communication system described in the fourth aspect further includes a terminal device.

[0044] Fifthly, embodiments of this application provide a computer storage medium storing a software program that, when read and executed by one or more processors, can implement the method provided in the first aspect or any of the possible implementations described above.

[0045] Sixthly, embodiments of this application provide a computer program product containing instructions that, when run on a computer, cause the method provided in the first aspect or any of its possible implementations to be executed.

[0046] In a seventh aspect, embodiments of this application provide a chip system including a processor for supporting network devices in implementing the functions involved in the first aspect above.

[0047] In one possible design, the chip system further includes a memory for storing necessary program instructions and data to be executed by the loading device. The chip system may consist of chips or may include chips and other discrete components.

[0048] It should be noted that the technical effects that can be achieved by any of the second to seventh aspects or any of the possible implementations of the second to seventh aspects can be referred to the description of the technical effects that can be achieved by any of the first aspects or any of the possible implementations of the first aspect; they will not be repeated here. Attached Figure Description

[0049] Figure 1 is a schematic diagram of a communication system applicable to an embodiment of this application;

[0050] Figure 2 is a schematic diagram of the architecture of a network device;

[0051] Figure 3 is a flowchart illustrating a communication method according to an embodiment of this application;

[0052] Figure 4 is a user clustering diagram provided in this application;

[0053] Figure 5 is a schematic diagram of the implementation process on the base station side provided in this application;

[0054] Figure 6 is a schematic diagram showing the comparison of simulation results provided in this application;

[0055] Figure 7 is a schematic diagram of a communication device provided in an embodiment of this application;

[0056] Figure 8 is a schematic diagram of another communication device provided in an embodiment of this application;

[0057] Figure 9 is a schematic diagram of a chip device provided in an embodiment of this application. Detailed Implementation

[0058] The technical solutions in the embodiments of this application will now be described with reference to the accompanying drawings. This application will focus on various aspects, embodiments, or features of a system that may include multiple devices, components, modules, etc. It should be understood and appreciated that each system may include additional devices, components, modules, etc., and / or may not include all the devices, components, modules, etc. discussed in conjunction with the accompanying drawings. Furthermore, combinations of these solutions may also be used.

[0059] The technical solutions of this application can be applied to various wireless communication systems, such as Universal Mobile Telecommunications System (UMTS), Wireless Local Area Network (WLAN), short-range wireless communication systems (such as sidelink, wireless fidelity, Wi-Fi, Bluetooth, etc.), wired networks, vehicle-to-everything (V2X) communication systems, device-to-device (D2D) communication systems, vehicle-to-everything (V2X) communication systems, integrated communication and sensing systems, 4th generation (4G) mobile communication systems (such as Long Term Evolution (LTE) systems), LTE Frequency Division Duplex (FDD) systems, LTE Time Division Duplex (TDD) systems, Worldwide Interoperability for Microwave Access (WiMAX) communication systems, 5th generation (5G) mobile communication systems (such as New Radio (NR) systems), Future Communications systems, or other similar communication systems, without limitation. This application describes the communication system shown in Figure 1 as an example. When applying the technical solution of this application to other communication systems, the devices, components, modules, etc. in the embodiment can be replaced with corresponding devices, components, modules in other communication systems without limitation.

[0060] Figure 1 is a schematic diagram of the architecture of the communication system applied in the embodiments of this application. As shown in Figure 1, the communication system includes an access network 100. Optionally, the communication system may also include a core network 200 and an Internet 300. The access network 100 may include at least one network device, such as 110a and 110b in Figure 1, and may also include at least one terminal device, such as 120a-120j in Figure 1. Specifically, 110a is a base station, 110b is a micro-station, 120a, 120e, 120f, and 120j are mobile phones, 120b is a car, 120c is a fuel dispenser, 120d is a home access point (HAP) deployed indoors or outdoors, 120g is a laptop computer, 120h is a printer, and 120i is a drone. The same terminal device or network device can provide different functions in different application scenarios. For example, the mobile phones in Figure 1 are 120a, 120e, 120f and 120j. Mobile phone 120a can access base station 110a, connect to car 120b, communicate directly with mobile phone 120e and access HAP. Car 120b can access HAP and communicate directly with mobile phone 120a. Mobile phone 120f can access micro-station 110b, connect to laptop 120g and printer 120h. Mobile phone 120j can control drone 120i.

[0061] (1) Network equipment

[0062] A network device is a network-side device with wireless transceiver capabilities. A network device can be a device in a radio access network (RAN) that provides wireless communication capabilities to terminal devices; it can be called an RAN device. The RAN can be an access network in the 3rd Generation Partnership Project (3GPP), such as 4G, 5G, or future networks. The RAN can also be an open RAN (O-RAN or ORAN), a cloud radio access network (CRAN), or a communication network combining two or more of these.

[0063] Network equipment 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 base station in a future mobile communication system, an access node, transmission node, transceiver node, relay equipment in a WiFi system, or a small or micro station with base station functions, etc.

[0064] Network equipment can also be modules or units that perform some of the functions of a base station. For example, it can be a central unit (CU), a distributed unit (DU), or a radio unit (RU). Here, the CU performs the functions of the radio resource control (RRC) and PDCP protocols of the base station, and can also perform the functions of the service data adaptation protocol (SDAP). The CU can be further divided into a CU control plane (CP) (i.e., CU-CP) and a CU user plane (UP) (i.e., CU-UP). The DU performs the functions of the RLC and MA layers of the base station, and can also perform some or all of the physical layer functions. For specific descriptions of the above protocol layers, please refer to the relevant 3GPP technical specifications. The CU and DU can be set up separately, or they can be included in the same network element, such as in the baseband unit (BBU). The RU can be included in radio frequency equipment or radio frequency units, such as in a remote radio unit (RRU), an active antenna unit (AAU), or a remote radio head (RRH). In different systems, CU, DU, or RU may have different names, but those skilled in the art will understand their meaning. For example, in an ORAN system, CU can also be called O-CU (open CU), DU can also be called O-DU, and RU can also be called O-RU. Any of the CU (or CU-CP, CU-UP), DU, and RU units in this application can be implemented through software modules, hardware modules, or a combination of software and hardware modules. RAN equipment can be a macro base station (as shown in Figure 1, 110a), a micro base station or an indoor station (as shown in Figure 1, 110b), or a relay node or master node, etc. The embodiments of this application do not limit the specific technology or equipment form used in the network equipment.

[0065] For example, communication between network devices and terminal devices follows a certain protocol layer structure, which may include the radio resource control (RRC) layer, the packet data convergence protocol (PDCP) layer, the radio link control (RLC) layer, the media access control (MAC) layer, and the physical layer (PHY) layer. For detailed descriptions of each of these protocol layers, please refer to the relevant technical specifications of the 3rd Generation Partnership Project (3GPP).

[0066] Figure 2 illustrates a schematic diagram of a network device architecture. As shown in Figure 2, the network device includes one or more functional modules for signal processing. Taking the physical layer function as an example, the network device can perform 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.

[0067] In Figure 2, CPRI stands for Common Public Radio Interface, used to connect the building base band unit (BBU) and radio remote unit (RRU) of a wireless base station. eCPRI stands for Enhanced Common Public Radio Interface. eCPRI Cat A to F are several categories divided to meet different needs. These categories differ in key performance indicators such as data transmission rate, latency, and functional support to accurately adapt to various service scenarios, from simple mobile Internet access to complex industrial control and high-bandwidth multimedia transmission.

[0068] (2) Terminal equipment

[0069] A terminal device is a user-side device with wireless transceiver capabilities. Terminal devices can also be called terminals, user equipment (UE), mobile stations, mobile terminals, etc. Terminal devices can be widely used in various scenarios, such as device-to-device (D2D), vehicle-to-everything (V2X) communication, machine-type communication (MTC), the Internet of Things (IoT), the Industrial Internet, virtual reality, augmented reality, industrial control, autonomous driving, telemedicine, smart grids, smart furniture, smart offices, smart wearables, smart transportation, and smart cities. Terminal devices can be mobile phones, tablets, computers with wireless transceiver capabilities, wearable devices, vehicles, drones, helicopters, airplanes, ships, robots, robotic arms, smart home devices, etc. In the embodiments of this application, the device used to implement the functions of the terminal device can be the terminal device itself, or it can be a device that supports the terminal device in implementing that function, such as a chip system or a combination of devices or components that can implement the functions of the terminal device. This device can be installed in the terminal device. The embodiments of this application do not limit the specific technology or specific device form used in the terminal device.

[0070] For example, the terminal device includes one or more functional modules for signal processing. For instance, the terminal device may perform one or more of the following functions: encoding, decoding, rate matching, rate dematching, scrambling, descrambling, modulation, demodulation, layer mapping, FFT, IFFT, IDFT, precoding, RE mapping, channel equalization, RE mapping, digital BF, adding CP, or removing CP, etc.

[0071] Network devices and terminal devices can be fixed in location or mobile. They can be deployed on land, including indoors or outdoors, handheld or vehicle-mounted; they can also be deployed on water; and they can also be deployed in the air on airplanes, balloons, and artificial satellites. The embodiments of this application do not limit the application scenarios of the network devices and terminal devices.

[0072] The roles of network devices and terminal devices can be relative. For example, the helicopter or drone 120i in Figure 1 can be configured as a mobile network device. For terminal devices 120j that access the wireless access network 100 via 120i, terminal device 120i is a network device; however, for network device 110a, 120i is a terminal device. That is, 110a and 120i communicate via a wireless air interface protocol. Of course, 110a and 120i can also communicate via a network device-to-network device interface protocol. In this case, relative to 110a, 120i is also a network device. Therefore, both network devices and terminal devices can be collectively referred to as communication devices. 110a and 110b in Figure 1 can be called communication devices with network device functions, and 120a-120j in Figure 1 can be called communication devices with terminal device functions.

[0073] Network devices and terminal devices, network devices and network devices, and terminal devices and terminal devices can communicate through licensed spectrum, unlicensed spectrum, or both licensed and unlicensed spectrum simultaneously; there are no specific limitations.

[0074] The network architecture and business scenarios described in this application are intended to more clearly illustrate 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 business scenarios, the technical solutions provided in the embodiments of this application are also applicable to similar technical problems.

[0075] The following explanations address the relevant terms used in the embodiments of this application. These explanations are intended to make the embodiments of this application easier to understand and should not be construed as strict limitations on the terms within the scope of protection claimed in this application.

[0076] (1) ISAC (or Integrated Sensing and Communication): ISAC refers to integrating two independent functions, wireless communication and wireless sensing, into the same system. As one of the important candidate technologies for future mobile communication, ISAC can fully share the spatial, temporal, and frequency resources of wireless communication and radar sensing, achieving coexistence, mutual assistance, and shared benefits between the two.

[0077] (2) Multiple Access Technology: Within the radio wave coverage area of ​​a wireless communication environment, how to establish wireless channel connections between users is a problem of multiple access (MA) technology. The method to solve the multiple access problem is called multiple access technology, also known as "multiple access connection" technology. Multiple access technology divides the signal dimension into different channels and allocates them to users, enabling multiple users to communicate using resources.

[0078] Based on whether user access is relevant, multiple access technologies can be divided into OMA and NOMA.

[0079] OMA: Under OMA, each user has exclusive access to a signal resource in a specific dimension. For example, the signal is divided into multiple parts according to frequency or time and then allocated to different users for communication. In this way, there is no interference between different users, but the spectral efficiency is relatively low.

[0080] The integrated orthogonal multiple access (OMA-ISAC) system includes: frequency division multiple access (FDMA), time division multiple access (TDMA), code division multiple access (CDMA), and spatial division multiple access (SDMA).

[0081] Among them, FDMA divides the channel according to the frequency domain, such as assigning different carrier frequencies to different users to share the same channel for communication. TDMA divides the channel according to the time domain (such as time slots), such as assigning different time slots to different users to share the same channel for communication. CDMA divides the channel according to the code sequence, such as assigning different coding sequences to different users to share the same channel for communication. SDMA divides the channel according to different antenna orientation information, such as dividing the antenna array into several antenna subarrays and assigning different angle antenna subarrays to different users. Each subarray transmits signals to only one user, so each user has its own independent communication channel, reducing mutual interference. This allows different users to transmit in parallel on the same frequency.

[0082] NOMA: In NOMA, multiple users share the same channel resources and cannot be distinguished by a single dimension. For example, the same frequency or time resources may be allocated to multiple different users for communication, which results in high spectral efficiency, but interference exists between different users.

[0083] Non-orthogonal multiple access (NOMA-ISAC) that integrates sensing and communication includes: sparse code multiple access (SCMA), power domain multiple access (PDMA), and rate splitting multiple access (RSMA).

[0084] SCMA can extend user information in both the time and frequency domains by using sparse coding, allowing information from different users to be superimposed. Specifically, SCMA codewords are sparse in the frequency domain, allowing multiple users to share the same resource elements. Each user has specific non-zero element positions, and the sparsity of these positions determines the efficiency of information transmission. Key features of the SCMA system include factor graph matrices and mapping matrices, which describe the structure and non-zero positions of user codewords. In the SCMA system, the encoded bits of the data stream can be directly mapped to codewords in a codebook constructed based on a multidimensional constellation. SCMA codewords are sparse, meaning that only a few of their entries are non-zero, while the rest are zero. All SCMA codewords corresponding to an SCMA layer have unique positions for non-zero entries, known as the sparse pattern.

[0085] PDMA is a technique in wireless communication that distinguishes different user signals by adjusting transmission power. RSMA achieves non-orthogonal transmission by splitting user messages into non-general and private parts at the transmitting end, which can optimize interference management and multiple access strategies.

[0086] In the embodiments of this application, "at least one" refers to one or more, and "more than one" refers to two or more. "And / or" describes the relationship between related objects, indicating that three relationships can exist. For example, A and / or B can represent: A alone, A and B simultaneously, or B alone, where A and B can be singular or plural. The character " / " generally indicates that the preceding and following related objects are in an "or" relationship. "At least one of the following" or similar expressions refer to any combination of these items, including any combination of single or plural items. For example, at least one of a, b, or c can represent: a, b, c, a and b, a and c, b and c, or a and b and c, where a, b, and c can be single or multiple.

[0087] (3) Precoding technology: Base stations and other network devices can process the signal to be transmitted using a precoding matrix that matches the channel state, given the known channel state. This ensures the precoded signal is compatible with the channel, reducing the complexity of eliminating inter-channel interference for the receiving device. Therefore, by precoding the signal to be transmitted, the quality of the received signal is improved, and this quality can be characterized by parameters such as signal-to-interference-plus-noise ratio (SINR). Thus, by employing precoding technology, transmitting devices and multiple receiving devices can transmit on the same time-frequency resources, achieving multiple-user multiple-input multiple-output (MU-MIMO). It should be understood that the descriptions of precoding technology in this document are merely illustrative for ease of understanding and are not intended to limit the scope of protection of the embodiments of this application. In specific implementations, the transmitting device can also perform precoding in other ways. For example, when channel information (e.g., the channel matrix) is unknown, a pre-set precoding matrix or a weighted processing method can be used for precoding.

[0088] (4) Frequency domain resources: Represents resources in the frequency domain.

[0089] In this embodiment, N frequency domain resources can be N frequency domain resource units. For example, frequency domain resource units include, but are not limited to: sub-band, subcarrier, resource block (RB), resource block group (RBG), or precoding resource block group (PRG), etc.; N is a positive integer.

[0090] (5) Reference signal (RS) and precoded reference signal: The reference signal can also be called a pilot, reference sequence, etc. In the embodiments of this application, the reference signal can be a reference signal used for channel measurement. For example, the reference signal can be a channel state information reference signal (CSI-RS) used for downlink channel measurement, or a sounding reference signal (SRS) used for uplink channel measurement.

[0091] It should be understood that the reference signals listed above are merely examples and should not be construed as limiting this application in any way. This application does not preclude the possibility of defining other reference signals in future protocols to achieve the same or similar functions. The precoded reference signal can be a reference signal obtained by precoding a reference signal. Specifically, precoding can include beamforming and / or phase rotation. Beamforming can be implemented, for example, by precoding the downlink reference signal based on one or more angle vectors, and phase rotation can be implemented, for example, by precoding the downlink reference signal with one or more time delay vectors.

[0092] Furthermore, unless otherwise stated, the ordinal numbers such as "first," "second," or "1," "2," etc. (except when indicating numerical values) mentioned in the embodiments of this application are used to distinguish multiple objects and are not used to limit the size, content, order, timing, priority, or importance of the multiple objects. For example, "first information" and "second information" are only used to distinguish different information, not to indicate a difference in the size, priority, or importance of these two pieces of information. Similarly, "cluster 1" and "cluster 2" are only used to distinguish different clusters, not to indicate a difference in the size, priority, or importance of these two clusters.

[0093] In the embodiments of this application, the terms "exemplary," "for example," etc., are used to indicate examples, illustrations, or descriptions. Any embodiment or design scheme described as an "example" in this application should not be construed as being more preferred or advantageous than other embodiments or design schemes. Specifically, the use of the term "example" is intended to present concepts in a concrete manner. In the embodiments of this application, "of," "relevant," and "corresponding" may sometimes be used interchangeably, and it should be noted that their intended meanings are consistent unless their distinction is emphasized.

[0094] The terms "comprising" and "having," and any variations thereof, used in the following description of embodiments of this application are intended to cover non-exclusive inclusion. For example, a process, method, system, product, or device that includes a series of steps or units is not limited to the listed steps or units, but may optionally include other steps or units not listed, or may optionally include other steps or units inherent to these processes, methods, products, or devices. Furthermore, the term "for indicating" used in the description of embodiments of this application can include both direct and indirect indication. When describing an indication message for indicating A, it may include whether the indication message directly indicates A or indirectly indicates A, but does not necessarily mean that the indication message carries A.

[0095] In this application, "send" and "receive" refer to the direction of information / data / 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. Furthermore, "send" can also be understood as the "output" of a chip interface, and "receive" can be understood as the "input" of a chip interface. In other words, "send" or "receive" can occur between nodes / devices, such as a base station and a terminal transmitting or receiving data via an air interface. "Send" or "receive" can also occur within a device, such as between components, modules, chips, software modules, or hardware modules within the device via a bus, wiring, or interface.

[0096] It should be understood that the names of the messages (or information, etc.) in the following processes in this application are merely examples. As communication technology evolves, the names of the messages (or information, etc.) in the following processes may change. However, no matter how the names change, as long as their meaning is the same as the function or meaning of the messages (or information, etc.) in this application, they all fall within the protection scope of this application.

[0097] The following describes the application scenarios and technical problems involved in the embodiments of this application. It should be noted that the application scenarios are intended to make the embodiments of this application easier to understand and should not be regarded as a limitation on the scope of protection claimed by this application.

[0098] In ISAC systems, the communication and sensing functions have different requirements and compete for limited resources. Therefore, a balanced solution needs to be determined to address the performance challenges of both. However, current ISAC implementations have certain limitations. For example, OMA-ISAC technology can suppress mutual interference between communication and sensing functions, but it suffers from poor adaptability and low spectrum utilization in dynamic environments. Furthermore, the high correlation between communication and sensing channels leads to significant performance loss in OMA-ISAC. NOMA-ISAC technology can significantly improve the resource utilization efficiency of wireless systems, achieving efficient resource sharing between sensing and communication through flexible resource allocation, and suppressing mutual interference between the two functions through interference management strategies. However, its design complexity is high, requiring complex interference cancellation. Table 1 illustrates the advantages and disadvantages of several commonly used ISAC schemes. Using SDMA as an example of OMA, Table 1 lists the optimization objectives, sensing objectives, communication indicators, and corresponding advantages and disadvantages for both SDMA and NOMA with and without dedicated sensing beamforms. In Table 1, "√" indicates the use of dedicated sensing beamforms, and "×" indicates the use without dedicated sensing beamforms.

[0099] Table 1

[0100] As mentioned above, the SDMA scheme has low resource utilization and, due to its limited spatial division capability, is difficult to apply in high-density scenarios where users and targets are at similar angles. The PDMA scheme requires significant differences in channel conditions, necessitates power allocation, and requires complex interference cancellation at the receiver. Therefore, improving the performance of the integrated communication and sensing system with lower complexity is one of the urgent problems to be solved.

[0101] To address the aforementioned problems, this application provides corresponding solutions.

[0102] Figure 3 illustrates a communication method provided in an embodiment of this application. This method can be executed by a network device, a component of the network device (e.g., a processor, chip, or chip system), or a device compatible with the network device. This application does not limit the specific structure and number of the executing entities of the method provided in the embodiments of this application, as long as communication can be performed 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. The following description uses a network device as an example. The order of steps in the following processes is merely an example. In actual applications, the execution order of steps in each process can be adjusted, and some or all steps can be executed adaptively. Referring to Figure 3, the process of the method in the embodiment of this application includes the following steps:

[0103] S301: The network device obtains channel characteristic information of J users; J is a positive integer.

[0104] For example, a network device can be an access network device, etc.

[0105] In one possible implementation, the user's channel characteristic information can be channel state information (CSI).

[0106] For example, taking one user as an example, the network device can send a reference signal to the user, the user receives the reference signal and measures the downlink CSI, and the user reports the downlink CSI to the network device.

[0107] S302: The network device determines the information of K user groups based on the channel characteristic information of J users.

[0108] Among the K user groups, the number of users in the k-th user group is J′. k ;K and J′ k It is a positive integer. k takes an integer from 1 to K.

[0109] In one possible implementation, when the network device executes S302, it includes: determining the number K of user groups based on the channel data in the channel feature information of J users; and performing clustering processing using a clustering algorithm based on the channel data of J users to divide the J users into K user groups and obtain the information of the K user groups.

[0110] For example, the clustering algorithm described above could be the K-means clustering algorithm.

[0111] In one possible implementation, K and J′ k When taking an integer greater than 1, the channel characteristics of users in different user groups within the K user groups have low correlation, while the channel characteristics of users in the same user group within the K user groups have high correlation.

[0112] For example, user group 1 includes user 1 and user 2, and user group 2 includes user 3 and user 4. The channel characteristics of user 1 and user 2 are similar, the channel characteristics of user 3 and user 4 are similar, while the channel characteristics of user 1 and user 3 (which could also be user 4) are significantly different, and the channel characteristics of user 2 and user 3 (which could also be user 4) are significantly different.

[0113] This implementation method ensures that the channel characteristics of different users within the same user group are similar, which facilitates the subsequent unified elimination of user interference within the user group. Meanwhile, the channel characteristics of users in different user groups are very different, which can reduce interference between different user groups.

[0114] In one possible implementation, for the aforementioned K user groups, users within a group can use Sparse Code Division Multiple Access (SCMA) to transmit with network devices. Users between groups can use Space Division Multiple Access (SDMA) to transmit with network devices.

[0115] S303: The network device determines the frequency domain resources for J users based on performance index information and information from K user groups.

[0116] Among them, performance metrics information is used to indicate the priority of communication needs and the priority of perception needs.

[0117] In one possible implementation, the method of this application embodiment further includes: the network device obtaining N frequency domain resources to be allocated; N is a positive integer; then the network device determines the frequency domain resources of J users based on performance index information and information of K user groups, including: the network device determining the frequency domain resources of J users based on performance index information, information of K user groups and N frequency domain resources.

[0118] Based on the above implementation, the following three allocation strategies are included, but not limited to, when executing S303:

[0119] Allocation Strategy 1: Prioritizing communication needs over perception needs, one possible implementation involves the network device determining the frequency domain resources for J users based on performance metrics, information from K user groups, and N frequency domain resources. This includes the following:

[0120] For J′ in the k-th user group k One user, determine J′ k The channel gain of each user in N frequency domain resources is calculated, and the d frequency domain resources with the largest channel gains are selected as the user's frequency domain resources; d is a positive integer less than N.

[0121] Among them, J′ k Any two users in the N frequency domain resources correspond to different or partially the same frequency domain resources, and the number of users corresponding to each frequency domain resource in the N frequency domain resources does not exceed a predetermined threshold.

[0122] Allocation Strategy 2: Given that the priority of sensing needs is higher than that of communication needs, one possible implementation involves the network device determining the frequency domain resources for J users based on performance metrics, information from K user groups, and N frequency domain resources. This includes the following steps:

[0123] Obtain the perception weights of N frequency domain resources;

[0124] For J′ in the k-th user group k A user, based on N frequency domain resources and J′k Given the number d of frequency domain resources corresponding to each of the N users, determine q allocation methods; where each allocation method corresponds to d frequency domain resources out of N frequency domain resources; q is greater than or equal to J′. k Integers;

[0125] Based on the perceived weights of N frequency domain resources, determine the allocation priority of q allocation methods;

[0126] Based on the allocation priorities of the q allocation methods, select J′ with the highest allocation priority from among the q allocation methods. k Allocation method; and according to J′ k The allocation method determines J′ k Frequency domain resources for each user.

[0127] Allocation Strategy 3: Communication demand priority and perception demand priority are the same; in one possible implementation, the network device determines the frequency domain resources for J users based on performance index information, information of K user groups, and N frequency domain resources, including the following steps:

[0128] For J′ in the k-th user group k One user, determine J′ k Channel gain for each of the N users across N frequency domain resources;

[0129] Based on the perceived weights of N frequency domain resources, determine the expected number of allocations for the N frequency domain resources;

[0130] According to J′ k The channel quality index of each user is used to identify users with poor channel quality.

[0131] For example, a user with poor channel quality can refer to: from the front to the back direction, according to J′ k The channel quality index of each user, from high to low, is assigned to J′. k Sort the users, and the sorted J′ k Among the users, those listed earlier in the order have better channel quality, while those listed later have worse channel quality. From the sorted J′... k Among the users, select one or more users with the worst channel quality at the very end, or randomly select one or more users with the worst channel quality from the remaining users. Alternatively, according to J′ k The channel quality index of each user is used to select one or more users whose channel quality index is lower than a preset threshold as users with poor channel quality.

[0132] Furthermore, for users with poor channel quality, the frequency domain resources of the user are determined based on the user's channel gain on N frequency domain resources, the expected number of allocations of N frequency domain resources, and the first allocation rule.

[0133] The first allocation rule includes one or more of the following:

[0134] (1) Prioritize satisfying the expected number of allocations for the frequency domain resource with the highest perception weight;

[0135] (2) Select the frequency domain resource with high channel gain from N frequency domain resources;

[0136] (3) Select the frequency domain resource with high channel gain from the N frequency domain resources except for the frequency domain resource with the highest perception weight.

[0137] In one possible implementation, the channel quality metric for the aforementioned user is the root mean square of the sum of the user's channel gains across N frequency domain resources.

[0138] Based on allocation strategy 3, in one possible implementation, the method of this application embodiment further includes: targeting the aforementioned J′ k For users other than those with poor channel quality, the network device selects d frequency domain resources with the largest channel gain from the N frequency domain resources as the user's frequency domain resources, based on the user's channel gain on N frequency domain resources; d is a positive integer less than N.

[0139] In one possible implementation, the perceptual weights of the N frequency domain resources in allocation strategy 2 and allocation strategy 3 above can conform to the following formula:

[0140] Where, ρ n P represents the sensing weight of the nth frequency domain resource out of N frequency domain resources. n This represents the target effective sensing power of the nth frequency domain resource out of N frequency domain resources, where n is an integer from 1 to N, / is a division operation, and Σ is a summation operation.

[0141] S304: The network device determines the target precoding based on the frequency domain resources of J users and the information of K user groups.

[0142] The target precoding consists of user-level precoding and user group-level precoding. The frequency domain resources of J users and the target precoding are used for communication between the network device and J users.

[0143] In one possible implementation, the network device determines the target precoding based on the frequency domain resources of J users and the information of K user groups, including: adjusting the preset user-level precoding based on the frequency domain resources of J users to obtain user-level precoding; determining user group-level precoding based on the information of K user groups; and obtaining the target precoding based on the target user-level precoding and user group-level precoding.

[0144] In one possible implementation, the target precoding conforms to the following formula:

[0145] Among them, w jk (n) represents the target precoding of the nth frequency domain resource of the jth user in the kth user group; v jk (n) represents the target user-level precoding of the nth frequency domain resource of the jth user in the kth user group. B k (n) represents the user group-level precoding corresponding to the nth frequency domain resource of the kth user group. M represents the number of transmitting antennas on the network device, and a represents the transmission degrees of freedom. ∈ is any symbol, and ∈ is the symbol belonging to.

[0146] Among them, v jk (n) Maximize the sum and rate, v, under preset constraints. jk (n) satisfies the following formula:

[0147] The preset constraints include one or more of the following constraints:

[0148] First constraint: Where, γ j,k r represents the transmission rate of any user. min N represents the minimum transmission rate. j,k This represents the set of frequency domain resources occupied by any user. Target user group-level precoding is used to eliminate user group-level interference. γ jk (n) satisfies the following formula:

[0149] Among them, h jk (n) represents the channel response of the j-th user in the k-th user group on the n-th frequency domain resource. This represents the interference within the k-th user group. Based on information from K user groups, This is expressed as the average noise power within the k-th user group;

[0150] Second constraint: in, P represents the effective sensing power on the nth frequency domain resource. n This represents the preset power threshold for the nth frequency domain resource. Let a represent the covariance matrix of the integrated communication and sensing waveform transmitted on the nth frequency domain resource. n (·) represents the steering vector on the nth frequency domain resource, θ l Indicates the angle of the l-th diameter;

[0151] Third constraint: ∑ n ∑ k ∑ j ||w jk (n)‖ 2 ≤P t , where ∑ n ∑ k ∑ j ||w jk (n)‖ 2 For the total transmit power, P t This is the preset power threshold.

[0152] In the above, B k (n) satisfies the following formula: B k (n)=[u r+1,k (n),u r+2,k (n),…,u M,k (n)];

[0153] make For the preset block diagonalization precoding, B k (n) is The zero space, for Singular value decomposition yields U k (n) is The left singular vector, for The right singular vector, B k (n) is composed of and The system consists of the left singular vector U corresponding to singular values ​​of zero; M represents the number of transmit antennas of the network device, and r represents... The rank, i.e. the number of data streams.

[0154] In the scheme of this application embodiment, after the network device obtains the channel characteristic information of J users, it can divide the J users into K user groups based on the channel characteristic information of the J users. Then, according to the priority of communication needs, the priority of sensing needs, and the information of the K user groups, resources can be flexibly allocated to the J users, thereby achieving a trade-off between sensing performance (e.g., sensing accuracy) and communication performance. Moreover, the target precoding in this application embodiment consists of user-level precoding and user group-level precoding. User group-level precoding can be used to eliminate interference between user groups, and user-level precoding can be used to improve the communication performance of users within a user group (e.g., maximizing speed). Therefore, this scheme can support the communication of a large number of users and can achieve efficient integration of communication and sensing functions with low complexity.

[0155] Based on the scheme shown in Figure 3 above, the following describes the scheme of the embodiments of this application in detail through several specific implementation methods.

[0156] Implementation Method 1:

[0157] In Implementation Method 1, taking a network device as a base station as an example, S302 (i.e., the network device determines the information of K user groups based on the channel characteristic information of J users) in the scheme shown in Figure 3 above will be described in detail. The process of Implementation Method 1 specifically includes the following steps:

[0158] Step 1: The base station obtains the channel state information of J users, where J is a positive integer.

[0159] Here, the channel state information for each user refers to the channel state information (CSI) between the user and the base station.

[0160] In one possible implementation, for any user, the base station uses the average value of the normalized channel vector on the sub-band as the data point corresponding to the user, based on the user's channel state information, to characterize the user's position in the frequency domain.

[0161] Step 2: The base station divides the J users into K clusters based on their channel state information (K clusters are an example of the K user groups in the scheme shown in Figure 3 above).

[0162] The number of users in the k-th cluster out of the K clusters is denoted as J′. k k takes any integer from 1 to K. The number of users in the K clusters can be the same, different, or some clusters can have the same number of users; there are no restrictions on this, and it is determined according to the actual partitioning. In addition, the K clusters do not overlap, that is, there are no identical users in different clusters within the K clusters. This can also be understood as each of the J users being assigned to a cluster. Users within each of the K clusters have high channel correlation, while users between clusters have significant channel differences.

[0163] For example, a higher correlation value indicates more similar channel characteristics. The first cluster includes 5 users, and the channel correlation value of these 5 users is greater than or equal to a preset correlation threshold. The channel correlation value between users in the first cluster and users in the second cluster is less than the preset correlation threshold.

[0164] In one possible implementation, when the base station performs step two, it can use the K-means clustering algorithm to analyze the data points corresponding to the J users in order to minimize the sum of squares of the Euclidean distances between the data points and their nearest cluster centers.

[0165] For example, minimizing the sum of squares of the Euclidean distances between a data point and its nearest cluster center conforms to the following equation (1).

[0166] c k d represents the reference channel vector corresponding to the center position of the k-th cluster. j The channel vector representing user j, a jk This represents the distance of data point j from the cluster center k, where j is an integer from 1 to J.

[0167] Based on equation (1) above, the base station can iteratively solve the problem by decoupling the cluster centers and selection variables to obtain the user clustering results. As shown in Figure 4, the K-means clustering algorithm is used to cluster the data points corresponding to J users, resulting in K clusters, namely cluster 1, cluster 2, ..., cluster K. jk =1 indicates that data point j is closest to cluster center k, a jk =0 indicates that data point j is the farthest from cluster center k.

[0168] In one possible implementation, for the aforementioned K clusters, users within a cluster use Sparse Code Division Multiple Access (SCMA) to transmit with the base station. Users between clusters use Spatial Division Multiple Access (SDMA) to transmit with the base station.

[0169] In Implementation Method 1, the base station can divide J users into K non-overlapping clusters based on the users' channel state information. The channel correlation of users within each cluster is high, while the channel differences between users in different clusters are large, which facilitates effective resource allocation in the future.

[0170] Implementation Method Two:

[0171] In the second implementation method, taking a network device as a base station as an example, the S303 (that is, the network device determines the frequency domain resources of J users based on performance index information and information of K user groups) in the scheme shown in Figure 3 will be described in detail.

[0172] In Implementation Method 2, taking N frequency domain resources to be allocated as N sub-bands as an example, based on the user clustering result A in Implementation Method 1, the corresponding sub-band is allocated to each user within each cluster. The process of Implementation Method 2 specifically includes the following steps:

[0173] Step 1: The base station constructs an evaluation table for user-subband performance based on the channel gain and sensing priority of the N subbands.

[0174] Subband performance includes communication performance and sensing performance. The following section uses J′ in the k-th cluster as an example. k The process of constructing a user-subband performance evaluation table is illustrated using one user as an example, where k is any integer from 1 to K.

[0175] (1) Regarding communication performance, the calculations are as follows:

[0176] First, regarding J′ k For any user among the N users, denoted as user j, calculate the channel gain of user j across the N subbands.

[0177] For example, the channel gain of user j in any subband n is expressed as:

[0178] Then, the root mean square of the channel gain of user j across N subbands is used as the average channel quality index of user j.

[0179] For example, the root mean square (RMS) of the channel gain of user j across N subbands conforms to the following equation (2).

[0180] Based on the above, according to J′ k Construct a user-subband communication performance evaluation table based on the average channel quality index of each user and the channel gain of each user in N subbands.

[0181] For example, as shown in Table 2, J′ k Users are sorted in descending order based on their average channel quality index value. Used to represent J′ k For each user, the channel quality decreases from strong to weak, from left to right. S1, S2, ..., S5 represent 5 sub-bands (or subcarriers). The column corresponding to H1 shows the channel gain of user 1 in each of the 5 sub-bands, the column corresponding to H2 shows the channel gain of user 2 in each of the 5 sub-bands, and so on recursively. The corresponding column is user J′ k Channel gain in each of the five subbands.

[0182] Table 2

[0183] Table 2 above is a user-subband communication performance evaluation table for one cluster. For other clusters in the K clusters, the user-subband communication performance evaluation table can be constructed by referring to Table 2 above, which will not be described in detail here.

[0184] (2) Regarding the perception performance, the calculation is as follows:

[0185] In one possible implementation, the contribution ratio of the target effective sensing power of each of the N sub-bands is used as the sensing weight or sensing priority of the corresponding sub-band. For example, the contribution ratio ρ of the target effective sensing power of sub-band n... n It conforms to the following formula (3):

[0186] Where n takes any integer from 1 to N.

[0187] For example, as shown in Table 3 below, a perception performance evaluation table for N sub-bands is constructed based on the perception priorities of the N sub-bands. In Table 3, W S The values ​​represent the perception weights (or perception priorities) of subbands. ρ1 represents the perception weights (or perception priorities) of subband 1, ρ2 represents the perception weights (or perception priorities) of subband 2, and so on. ρ5 represents the perception weights (or perception priorities) of subband 5.

[0188] Table 3

[0189] Based on the above calculations of communication and sensing performance, according to J′ k Average channel quality metrics and J′ for each user k Construct a user-subband communication perception performance evaluation table based on the channel gain of each user across N subbands and the perception priority of the N subbands for each user.

[0190] For example, by combining Tables 2 and 3 above, we obtain the user-subband communication awareness performance evaluation table, as shown in Table 4 below.

[0191] Table 4

[0192] Table 4 above is a user-subband communication awareness performance evaluation table for one cluster. For other clusters in the K clusters, the user-subband communication awareness performance evaluation table can be constructed with reference to the above, which will not be described in detail here.

[0193] In this application, Tables 2, 3, and 4 are merely examples of one implementation method. In actual applications, Tables 2, 3, and 4 may contain more or less content, which will not be detailed here.

[0194] Step 2: Based on the user-subband performance evaluation table, the base station can perform SCMA subband allocation for users in each of the K clusters.

[0195] The following uses J′ in the k-th cluster as an example. k Using one user as an example, this demonstrates how to perform a user-subband performance evaluation based on a user-subband performance table. k Each user performs SCMA subband allocation, where k is any integer from 1 to K.

[0196] For the N sub-bands to be assigned, assume J′ k Each of the users occupies d c Sub-band, and J′ k Each user has a different usage method, i.e., J′ kIf the subbands occupied by each user are not exactly the same, then the subband allocation method shall not exceed [a certain number]. In addition, to control interference, each subband is set to be at most d. f Each user occupies a portion of the bandwidth. Based on this, the base station uses the user-subband performance evaluation table to determine the J′ bandwidth. k When assigning SCMA subbands to individual users, the following allocation strategies are available:

[0197] Allocation Strategy 1: Prioritize communication performance.

[0198] For J′ k For each of the N users, based on the user's channel gain across the N subbands, select the d corresponding to the largest channel gain. c He has a belt.

[0199] For example, the initialization allocation matrix Referring to Table 2 above, for J′ k For each user in the given list, select the largest d from the corresponding column. c element ||h nj ‖, making F n,j =1, and the following constraints need to be satisfied:

[0200] Constraint 1: That is, let J′ k Each of the users occupies d c Individual belt;

[0201] Constraint 2: That is, each of the N subbands can be at most d f One user occupies;

[0202] Constraint 3: That is, let J′ k Any two users among the users will have different usage methods.

[0203] Allocation Strategy 2: Prioritize perception performance.

[0204] For the k-th cluster, where J′ k Each of the users occupies d c Sub-band, and J′ k Each user has a different usage method, i.e., J′ k If the subbands occupied by each user are not exactly the same, then the subband allocation method shall not exceed [a certain number]. Based on this, first, according to the perceptual weights {ρ1,ρ2,…,ρ...} of the N sub-bands shown in Table 2... N}, quantify the priority of the q-seed allocation method respectively; then, select the J′ with the highest priority. kSeed band allocation method, and then according to J′ k Seed band allocation method, J′ k Each user is assigned a corresponding sub-band. If there is no limit on the maximum number of users (d) that can occupy each of the N sub-bands... f Then J′ k Each user can prioritize selecting the sub-band with the highest perception weight.

[0205] For example, there are 5 subbands, and the perceptual weights of the 5 subbands are {ρ1,ρ2,…,ρ5}. Assume J′ k =5, and each of the 5 users occupies 2 sub-bands. Therefore, the 10 possible allocation methods for the 5 sub-bands are as follows:

[0206] Allocation method 1: Subband 1 and Subband 2, the priority of allocation method 1 is w1 = ρ1 + ρ2;

[0207] Allocation method 2: Sub-band 1 and sub-band 3, the priority of allocation method 2 is w2 = ρ1 + ρ3;

[0208] Allocation method 3: Sub-band 1 and sub-band 4, the priority of allocation method 3 is w3 = ρ1 + ρ4;

[0209] Allocation method 4: Sub-band 1 and sub-band 5, the priority of allocation method 4 is w4 = ρ1 + ρ5;

[0210] Allocation method 5: Subband 2 and subband 3, priority of allocation method 5 w5 = ρ2 + ρ3;

[0211] Allocation method 6: Subband 2 and subband 4, the priority of allocation method 6 is w6 = ρ2 + ρ4;

[0212] Allocation method 7: Sub-band 2 and sub-band 5, the priority of allocation method 7 is w7 = ρ2 + ρ5;

[0213] Allocation method 8: Sub-band 3 and sub-band 4, the priority of allocation method 8 is w8 = ρ3 + ρ4;

[0214] Allocation method 9: Sub-band 3 and sub-band 5, priority of allocation method 9 w9 = ρ3 + ρ5;

[0215] Allocation method 10: Sub-band 4 and sub-band 5, priority w of allocation method 10 10 =ρ4+ρ5.

[0216] Based on the priority of the 10 allocation methods mentioned above, the 5 allocation methods with the highest priority are selected. For example, if the priority of the 10 allocation methods is sorted from high to low, the first 5 are w1, w2, w5, w6, and w8. Then, according to allocation method 1, allocation method 2, allocation method 5, allocation method 6, and allocation method 8, the corresponding sub-bands are allocated to the 5 users. For example, sub-band 1 and sub-band 2 corresponding to allocation method 1 are assigned to user 1, sub-band 1 and sub-band 3 corresponding to allocation method 2 are assigned to user 2, sub-band 2 and sub-band 3 corresponding to allocation method 5 are assigned to user 3, sub-band 2 and sub-band 4 corresponding to allocation method 6 are assigned to user 4, and sub-band 3 and sub-band 4 corresponding to allocation method 8 are assigned to user 5.

[0217] Allocation Strategy 3: A trade-off between communication and sensing performance.

[0218] 1) Prioritize communication performance, and assign it to J′. k Each of the users is initially assigned d. c Each sub-band. The specific implementation can be referenced in allocation strategy 1 above, and will not be repeated here.

[0219] 2) Based on the perceptual weights {ρ1,ρ2,…,ρ} of the N sub-bands N The expected number of assignments for each of the N subbands is calculated as follows: d c ×J′ k ×[ρ1,ρ2,…,ρ N ];

[0220] 3) According to J′ k Channel quality metrics for each user, determining J′ k The user {j′} with the poorest channel quality among the users is identified, and the initially allocated subband corresponding to the user {j′} with the poorest channel quality is adjusted.

[0221] For J′ k For users {j′} with poor channel quality among N users, assuming that subband m has the highest perception weight among the N subbands, then the expected number of allocations for subband m should be prioritized (let F). j′,m =1), then select d from the remaining available sub-bands. c -1 corresponds to a subband with higher channel gain.

[0222] For example, with N=5, J′ k =5,d c =2,d f Taking 4 as an example, the user-subband communication sensing performance evaluation table is shown in Table 5 below. The specific allocation strategy for comprehensive communication and sensing performance is as follows:

[0223] As shown in Table 5, S1 represents subband 1, S2 represents subband 2, S3 represents subband 3, S4 represents subband 4, and S5 represents subband 5. The channel quality for the five users gradually deteriorates from left to right. Based on the communication priority criterion, the initial subband allocation results for the five users are determined as follows: User 1 (H1) is allocated subband 1 and subband 5, User 2 (H2) is allocated subband 2 and subband 5, User 3 (H3) is allocated subband 3 and subband 5, User 4 (H4) is allocated subband 4 and subband 5, and User 5 (H5) is allocated subband 1 and subband 2. Therefore, the number of times the five subbands were initially allocated is 2, 2, 1, 1, and 4, respectively.

[0224] Table 5

[0225] The initial sub-band mapping matrix F assigned to the above 5 users is represented as follows:

[0226] Based on the perception weights of the five subbands shown in Table 5, the expected number of allocations for the five subbands are determined to be 2, 2, 1, 3, 2, respectively. Among them, subband 4 has the highest expected number of allocations, but according to the above statistics, subband 4 has been allocated only once so far.

[0227] Based on the above, the subbands allocated to users 3 and 5, who have poor channel quality, are selected for adjustment so that the allocation frequency of subband 4 reaches the desired frequency of 3. In one possible implementation, subbands 3 and 5 corresponding to user 3 are adjusted, resulting in subbands 3 and 4 for user 3; and subbands 1 and 2 corresponding to user 5 are adjusted, resulting in subbands 1 and 4 for user 5. After adjusting the subbands for users 3 and 5, the subband mapping matrix for the five users is represented by F′ as follows:

[0228] For each user within one of the K clusters, the steps described above can be used to assign a corresponding sub-band to each user within the cluster; these steps will not be detailed here.

[0229] Furthermore, based on the user clustering result A and the sub-band allocation result F of different clusters in the K clusters, the resource allocation for all users is determined, and the resource allocation within the same resource block is ensured to be non-orthogonal in order to effectively reduce interference.

[0230] For example, J=12, K=2, N=5, ensuring that the number of users in each cluster does not exceed 8. Assume 12 users are divided into two clusters, cluster 1 and cluster 2. Cluster 1 contains 7 users, and cluster 2 contains 5 users. The clustering results are shown in Table 6 below. In Table 6, the first row corresponds to the identifiers of the 12 users. If a user belongs to cluster 1, a 1 is used; otherwise, a 0 is used. Similarly, for the second row, if a user belongs to cluster 2, a 1 is used; otherwise, a 0 is used.

[0231] Table 6

[0232] Each of the 12 users occupies 2 subbands. The subband mapping matrix for the 7 users in cluster 1 is as follows: F1. The subband mapping matrix for the 5 users in cluster 2 is as follows: F2.

[0233] Based on the subband mapping matrices F1 and F2, the subband allocation result D for the 12 users can be obtained, and D conforms to the following formula (4):

[0234] Among them, S k S represents the selection matrix of cluster k; k (i,j) = 1 if and only if A(i,k) = 1 and the user is located at the j-th position in cluster k.

[0235] Referring to the user clustering results shown in Table 6 above, it can be seen that the selection matrix of cluster 1 is represented as [1,0,1,1,0,0,1,0,1,1,0,1], and the selection matrix of cluster 2 is represented as [0,1,0,0,1,1,0,1,0,0,1,0].

[0236] Based on the subband mapping matrix F1 of cluster 1 and the selection matrix of cluster 1, and the subband mapping matrix F2 of cluster 2 and the selection matrix of cluster 2, the subband allocation result is calculated by the above formula (4), and the subband allocation result is represented by the following matrix D.

[0237] In Implementation Method Two, based on user clustering result A and the performance indicators / requirements of communication and sensing in different sub-bands, a corresponding user-sub-band performance evaluation table is constructed. This table can be pre-determined through negotiation or determined by the base station and can be indicated to users by the base station. The base station can flexibly select a communication-first allocation strategy, a sensing-first allocation strategy, or a compromise allocation strategy based on the priority of communication and sensing performance indicators or requirements, to allocate corresponding sub-band resources to users. This not only guarantees sensing performance (e.g., sensing accuracy) / sensing requirements or communication performance but also achieves a trade-off between sensing and communication performance, i.e., satisfying the performance indicators / requirements of both communication and sensing as much as possible simultaneously.

[0238] Implementation Method 3:

[0239] In the third implementation method, taking a network device as a base station as an example, the S304 (that is, the network device determines the target precoding based on the frequency domain resources of J users and the information of K user groups) in the scheme shown in Figure 3 will be described in detail.

[0240] In Implementation Method 3, based on the subband allocation results D of the users in the K clusters obtained in Implementation Method 2 and the subband mapping matrix of the users within each of the K clusters, a precoding for communication awareness is designed (an example of target precoding in the scheme shown in Figure 3 above). The precoding for communication awareness is obtained using cluster-level precoding (an example of user group-level precoding in the scheme shown in Figure 3 above) and user-level precoding (an example of user-level precoding in the scheme shown in Figure 3 above).

[0241] For example, the precoding matrix in the embodiments of this application can conform to the following formula (5):

[0242] Among them, B k (n) represents the cluster-level precoding matrix of the k-th cluster, v jk (n) represents the user-level precoding matrix of the j-th user in the k-th cluster.

[0243] The design of cluster-level precoding and user-level precoding is described in detail below.

[0244] 1. Cluster-level precoding:

[0245] In this embodiment, cluster-level precoding is designed based on user clustering result A. Where M represents the number of transmit antennas of the base station (an example of the network equipment in the scheme shown in Figure 3 above), and a is the degree of freedom of transmission.

[0246] For example, block diagonalization precoding is used to project the transmitted signal onto the null space of the interference channel, i.e. This eliminates inter-cluster interference. Singular value decomposition, i.e. null space B k (n) due to The left singular vectors corresponding to singular values ​​of zero are formed, as shown in equation (6): B k (n)=[u r+1,k (n),u r+2,k (n),…,u M,k (n)]; (6)

[0247] Where r represents The rank of a is Mr.

[0248] 2. User-level precoding:

[0249] By utilizing the subband allocation matrix D corresponding to the K clusters and the subband mapping matrix of users within each cluster (e.g., the subband allocation matrices F1 and F2 corresponding to the two clusters mentioned above), the user-level precoding currently used by the base station is optimized. To maximize the system and rate under the constraints of perception accuracy and total power, as shown in equation (7):

[0250] For example, the sensing accuracy constraints and total power constraints include the following:

[0251] Constraint (1):

[0252] Where, γ j,k r represents the transmission rate of the j-th user (or any user) in the k-th cluster. min N represents the minimum transmission rate. j,k This represents the set of frequency domain resources occupied by the j-th user (or any user) in the k-th cluster. The above cluster-level precoding can be used to eliminate cluster-level interference, γ jk (n) can satisfy the following equation (8):

[0253] Among them, h jk (n) represents the channel response of the j-th user in the k-th cluster on the n-th frequency domain resource. This represents the interference within the k-th cluster. Based on information from K clusters, It is represented as the average noise power within the k-th cluster.

[0254] Constraint (2):

[0255] in, P represents the effective sensing power on the nth frequency domain resource. n This represents the preset power threshold for the nth frequency domain resource. Let a represent the covariance matrix of the integrated communication and sensing waveform transmitted on the nth frequency domain resource. n (·) represents the steering vector on the nth frequency domain resource, θ l This represents the angle of the l-th diameter.

[0256] Constraint (3): ∑ n ∑ k ∑ j ||w jk (n)‖2 ≤P t ;

[0257] Where, ∑ n ∑ k ∑ j ||w jk (n)‖ 2 P represents the total transmit power. t This represents the preset power threshold.

[0258] In Implementation Method 3, a two-stage communication-aware precoding strategy is designed based on the subband allocation results D of the users in the K clusters and the subband mapping matrix of the users in each of the K clusters. This strategy can maximize the system and rate constrained by the effective sensing power and total transmit power, and can also eliminate inter-cluster interference.

[0259] For example, Figure 5 shows an implementation flow example of the SCMA-ISAC scheme shown in the embodiments of this application applied to the base station side. Referring to Figure 5, the flow executed by the base station includes the following:

[0260] Step 1: Obtain the CSI of J users and the perception priority of N sub-bands, etc.

[0261] Step 2: Perform user clustering based on the CSI of J users to obtain user clustering result A, i.e., K clusters. Next, this can be executed in two separate steps:

[0262] In the first step: Step 3.1: Construct a user-subband performance evaluation table. Specifically, the base station constructs a user-subband performance evaluation table based on the CSI of J users, the user clustering result A, and the subband perception priority.

[0263] Step 3.2, initial subband allocation. Specifically, the base station initially allocates subbands to J users based on the user-subband performance evaluation table, using a communication-first strategy.

[0264] Step 3.3: Determine whether to optimize / adjust the allocated subbands.

[0265] If yes, proceed to step 3.4, whereby the base station optimizes / adjusts the allocated subbands based on sensing requirements. If no, proceed to step 3.5, whereby SCMA coding is performed. Specifically, the base station performs SCMA coding based on the initially allocated subbands and the user clustering result A.

[0266] After executing step 3.4, the base station executes step 3.5, which involves performing SCMA encoding. Specifically, the base station performs SCMA encoding based on the adjusted subband and user clustering result A. After step 3.5, step 3.6 is executed, which involves sending the ISAC waveform signal, and the user receives the ISAC waveform signal accordingly. After the base station sends the ISAC waveform signal to the user, step 3.7 is executed, which involves obtaining the data obtained by the downlink user recovering the received ISAC waveform signal; step 3.8: processing the target echo signal to obtain the corresponding data.

[0267] Step 3.9: Optimize / adjust the currently used user-level precoding. Specifically, by using the data obtained from the downlink user recovering the received ISAC waveform signal and the data obtained from the base station processing the target echo signal, the user-level precoding currently used by the base station is optimized or adjusted to obtain the optimized or adjusted user-level precoding.

[0268] In the other path: Step 4: The base station determines the cluster-level precoding. Specifically, the base station determines the cluster-level precoding based on the CSI of J users, the user clustering result A, and the sub-band sensing priority.

[0269] In the aforementioned K clusters, users within a cluster use SCMA to transmit with the base station, while users between clusters use SDMA to transmit with the base station.

[0270] Furthermore, based on cluster-level and user-level precoding, a communication-aware precoding is obtained. Finally, the communication-aware precoding is used to communicate with J users.

[0271] For example, based on the simulation parameter configuration shown in Table 7, Figure 6 shows a comparison of the system and rate of OMA-ISAC and the SCMA-ISAC proposed in this application. The SCMA-ISAC scheme proposed in this application includes three SCMA subband resource allocation schemes corresponding to communication priority (corresponding to allocation strategy 1 above), perception priority (corresponding to allocation strategy 2 above), and a trade-off between communication and perception (corresponding to allocation strategy 3 above). As shown in Figure 6, for the OMA-ISAC scheme, each user is allocated only one subband, that is, the maximum number of users in each cluster is equal to the number of subbands. Through the system and rate of the SCMA subband resource allocation schemes corresponding to the three cases of communication priority, perception priority, and communication and perception trade-off shown in Figure 6, it can be seen that the communication priority SCMA subband resource allocation scheme (corresponding to allocation strategy 1 above) in this application can achieve better achievability and rate under the same conditions, and the achievability and rate of the SCMA scheme in this application are significantly better than those of the OMA scheme, that is, the performance gain is more than 50%.

[0272] Table 7

[0273] It should be understood that the above embodiments may change as the technical solutions evolve, and this application is not limited to the contents shown in the above embodiments.

[0274] It should be noted that different embodiments or some steps (e.g., any one or more steps) in different embodiments of this application can be combined with each other to form new embodiments. Furthermore, this application does not limit the inclusion of any one or more steps in different embodiments as including optional steps in a certain embodiment, mandatory steps in a certain embodiment, or both optional and mandatory steps in a certain embodiment.

[0275] It should be noted that, unless otherwise specified or there is a logical conflict, the terminology and / or descriptions between different implementation methods are consistent and can be referenced from each other.

[0276] It should be noted that the order of the steps in the embodiments of this application is determined by the logic of the scheme, and this application does not limit it.

[0277] It should be noted that the order in which different conditions are judged in the embodiments of this application is not limited by this application.

[0278] It should be noted that the terms "after" and "time" in this application do not strictly limit the specific point in time.

[0279] It should be noted that the nouns and terms used in this application are merely examples and may be other names, which are not limited in this application.

[0280] In the embodiments provided above, the methods provided by the embodiments of this application have been described from the perspective of interaction between various devices. To implement the functions of the methods provided in the embodiments or implementations of this application, the network device may include hardware structures and / or software modules, implementing the above functions in the form of hardware structures, software modules, or a combination of hardware structures and software modules. Whether a particular function is executed in the form of hardware structures, software modules, or a combination of hardware structures and software modules depends on the specific application and design constraints of the technical solution.

[0281] The module division in this embodiment is illustrative and represents only one logical functional division; in actual implementation, other division methods may be used. Furthermore, the functional modules in the various embodiments or implementations of this application can be integrated into a single processor, exist as separate physical entities, or be integrated into a single module. The integrated modules described above can be implemented in hardware or as software functional modules.

[0282] Similar to the above concept, as shown in FIG7, this application embodiment also provides a communication device 700 for implementing the functions of the network device in the above method. For example, the communication device 700 can be a software module or a chip system. In this application embodiment, the chip system can be composed of chips or can include chips and other discrete devices. The communication device 700 may include: a communication unit 701 and a processing unit 702.

[0283] In this embodiment, the communication unit 701, also known as the transceiver unit, may include a sending unit and / or a receiving unit, respectively used to perform the sending and receiving steps of the network device in the above method embodiments. The processing unit 702 may be used to read instructions and / or data from the storage module so that the communication device 700 implements the aforementioned method embodiments.

[0284] For example, the communication device 700 may also include a storage unit 703, which is equivalent to a storage module and can be used to store instructions and / or data.

[0285] The communication device provided in the embodiments of this application is described in detail below with reference to Figures 7 and 8. It should be understood that the description of the device embodiments corresponds to the description of the method embodiments. Therefore, the contents not described in detail can be implemented as shown in Figure 3 above, and will not be repeated here for the sake of brevity.

[0286] The communication unit 701 can also be called a transceiver, transceiver, or transceiver device. The processing unit 702 can also be called a processor, processing board, processing module, or processing device. Optionally, the device in the communication unit 701 used to implement the receiving function can be considered as a receiving unit, and the device in the communication unit 701 used to implement the transmitting function can be considered as a transmitting unit; that is, the communication unit 701 includes a receiving unit and a transmitting unit. The communication unit can sometimes also be called a transceiver, transceiver circuit, or transceiver unit. The receiving unit can sometimes be called a receiver, receiver, or receiving circuit. The transmitting unit can sometimes be called a transmitter, transmitter, or transmitting circuit.

[0287] When the communication device 700 is applied to the network device in the process shown in Figure 3 of the above embodiment:

[0288] Communication unit 701 is used to obtain channel characteristic information of J users; J is a positive integer;

[0289] The processing unit 702 is configured to determine the information of K user groups based on the channel characteristic information of the J users; the number of users in the k-th user group among the K user groups is J′. k ;K and J′ k It is a positive integer. k takes an integer from 1 to K; the processing unit 702 is further configured to determine the frequency domain resources of the J users based on performance index information and the information of the K user groups; the performance index information is used to indicate the priority of communication needs and the priority of perception needs; and to determine the target precoding based on the frequency domain resources of the J users and the information of the K user groups; wherein the target precoding consists of user-level precoding and user group-level precoding, and the frequency domain resources of the J users and the target precoding are used for communication between the network device and the J users.

[0290] The above is just an example. The processing unit 702 and the communication unit 701 can also perform other functions. For a more detailed description, please refer to the relevant description in the method embodiment shown in Figure 3. It will not be repeated here.

[0291] Figure 8 shows a communication device 800 provided in an embodiment of this application. The communication device shown in Figure 8 can be a hardware circuit implementation of the communication device shown in Figure 7. This communication device 800 can be applied to the flowcharts shown above to perform the functions of the first or second communication device in the above method embodiments. For ease of explanation, Figure 8 only shows the main components of the communication device.

[0292] As shown in Figure 8, the communication device 800 includes a communication interface 801 and a processor 802. The communication interface 801 and the processor 802 are coupled to each other. It is understood that the communication interface 801 can be a transceiver or an input / output interface, or an interface circuit such as a transceiver circuit. Optionally, the communication device 800 may further include a memory 803 for storing instructions executed by the processor 802, or storing input data required by the processor 802 to execute instructions, or storing data generated after the processor 802 executes instructions.

[0293] When the communication device 800 is used to implement the method shown in FIG3 above, the communication interface 801 is used to implement the function of the communication unit 701 above, and the processor 802 is used to implement the function of the processing unit 702 above.

[0294] This embodiment does not limit the specific connection medium between the communication interface 801, processor 802, and memory 803. In Figure 8, the memory 803, processor 802, and communication interface 801 are connected via a communication bus 804, which is represented by a thick line. The connection methods between other components are merely illustrative and not intended to be limiting. The communication bus 804 can be divided into address bus, data bus, control bus, etc. For ease of illustration, only one thick line is used in Figure 8, but this does not indicate that there is only one bus or one type of bus.

[0295] When the aforementioned communication device is a chip, Figure 9 shows a simplified schematic diagram of the chip's device structure. The chip 900 includes an interface circuit 901 and one or more processors 902. Optionally, the chip 900 may also include a bus. Wherein:

[0296] The processor 902 may be an integrated circuit chip with signal processing capabilities. In implementation, each step of the method for determining the service node information described above can be completed through integrated logic circuits in the hardware of the processor 902 or through software instructions. The processor 902 may be a general-purpose processor, a digital signal processor (DSP), an application-specific integrated circuit (ASIC), a field-programmable gate array (FPGA), or other programmable logic devices, discrete gate or transistor logic devices, or discrete hardware components. It can implement or execute the methods and steps disclosed in the embodiments of this application. The general-purpose processor may be a microprocessor or any conventional processor.

[0297] The interface circuit 901 can be used to send or receive data, instructions or information. The processor 902 can use the data, instructions or other information received by the interface circuit 901 to process the data, instructions or other information, and can send the processed information out through the interface circuit 901.

[0298] Optionally, chip 900 also includes memory 903, which may include read-only memory and random access memory, and provides operation instructions and data to the processor. A portion of memory 903 may also include non-volatile random access memory (NVRAM).

[0299] Optionally, the memory stores executable software modules or data structures, and the processor can execute corresponding operations by calling the operation instructions stored in the memory (which may be stored in the operating system).

[0300] Optionally, the chip can be used in the network device involved in the embodiments of this application. Optionally, the interface circuit 901 can be used to output the execution result of the processor 902. For the communication methods provided by one or more embodiments of this application, please refer to the foregoing embodiments, which will not be repeated here.

[0301] It should be noted that the functions of the interface circuit 901 and the processor 902 can be implemented through hardware design, software design, or a combination of hardware and software; no restrictions are imposed here.

[0302] This application also provides a computer-readable storage medium storing computer instructions for implementing the methods executed by a network device in the above-described method embodiments.

[0303] For example, when the computer program is executed by a computer, it enables the computer to implement the method executed by the network device in the above method embodiments.

[0304] This application also provides a computer program product containing instructions that, when executed by a computer, cause the computer to implement the method executed by the network device in the above method embodiments.

[0305] This application embodiment also provides a chip, including a processor, for calling computer programs or computer instructions stored in the memory, so that the processor executes the communication method of the implementation shown in FIG3 above.

[0306] In one possible implementation, the input of the chip corresponds to the receiving operation in the implementation shown in Figure 3 above, and the output of the chip corresponds to the sending operation in the implementation shown in Figure 3 above.

[0307] Optionally, the processor is coupled to the memory via an interface.

[0308] Optionally, the chip also includes a memory that stores computer programs or computer instructions.

[0309] The processor mentioned above can be a general-purpose central processing unit, a microprocessor, an application-specific integrated circuit (ASIC), or one or more integrated circuits used to control the execution of a program through a communication method for the implementation shown in Figure 3. The memory mentioned above can be read-only memory (ROM) or other types of static storage devices capable of storing static information and instructions, such as random access memory (RAM).

[0310] It should be noted that, for the sake of convenience and brevity, the explanations and beneficial effects of the relevant content in any of the communication devices provided above can be referred to the corresponding service node information determination method embodiments provided above, and will not be repeated here.

[0311] The module division in this embodiment is illustrative and represents only one logical functional division. In actual implementation, other division methods may be used. Furthermore, the functional modules in each embodiment of this application can be integrated into a single processor, exist as separate physical entities, or be integrated into a single module. The integrated modules described above can be implemented in hardware or as software functional modules.

[0312] Through the above description of the embodiments, those skilled in the art will clearly understand that the embodiments of this application can be implemented in hardware, firmware, or a combination thereof. When implemented in software, the above functions can be stored in a computer-readable medium or transmitted as one or more instructions or code on a computer-readable medium. Computer-readable media include computer storage media and communication media, wherein communication media include any medium that facilitates the transfer of a computer program from one place to another. Storage media can be any available medium accessible to a computer. For example, but not limited to, computer-readable media can include RAM, ROM, electrically erasable programmable read-only memory (EEPROM), compact disc read-only memory (CD-ROM) or other optical disc storage, magnetic disk storage media, or other magnetic storage devices, or any other medium capable of carrying or storing desired program code in the form of instructions or data structures and accessible to a computer. Furthermore, any connection can suitably be a computer-readable medium. For example, if the software is transmitted from a website, server, or other remote source using coaxial cable, fiber optic cable, twisted pair, digital subscriber line (DSL), or wireless technologies such as infrared, radio, and microwave, then coaxial cable, fiber optic cable, twisted pair, DSL, or wireless technologies such as infrared, radio, and microwave are included in the definition of the medium. As used in embodiments of this application, disks and discs include compact discs (CDs), laser discs, optical discs, digital video discs (DVDs), floppy disks, and Blu-ray discs, wherein disks typically magnetically copy data, while discs optically copy data using lasers. The combinations above should also be included within the scope of protection for computer-readable media.

[0313] In summary, the above descriptions are merely embodiments of this application and are not intended to limit the scope of protection of this application. Any modifications, equivalent substitutions, improvements, etc., made based on the disclosure of this application should be included within the scope of protection of this application.

Claims

1. A communication method, characterized in that, include: Obtain channel characteristic information for J users; J is a positive integer; Based on the channel characteristic information of the J users, information for K user groups is determined; the number of users in the k-th user group among the K user groups is J′. k ;K and J′ k It is a positive integer. k takes an integer from 1 to K; Based on the performance index information and the information of the K user groups, determine the frequency domain resources of the J users; The performance metrics information is used to indicate the priority of communication needs and the priority of perception needs; The target precoding is determined based on the frequency domain resources of the J users and the information of the K user groups; The target precoding consists of user-level precoding and user group-level precoding. The frequency domain resources of the J users and the target precoding are used for communication between the network device and the J users.

2. The method according to claim 1, characterized in that, The step of determining the information of the K user groups based on the channel characteristic information of the J users includes: Based on the channel data in the channel characteristic information of the J users, determine the number K of the user groups; Based on the channel data of the J users, a clustering algorithm is used to perform clustering processing, dividing the J users into the K user groups and obtaining the information of the K user groups.

3. The method according to claim 1 or 2, characterized in that, K and J' k When the integer value is greater than 1, the channel characteristics of users in different user groups within the K user groups have low correlation, and the channel characteristics of users in the same user group within the K user groups have high correlation.

4. The method according to any one of claims 1-3, characterized in that, The method further includes: Obtain N frequency domain resources to be allocated; N is a positive integer; The step of determining the frequency domain resources of the J users based on performance index information and the information of the K user groups includes: Based on the performance index information, the information of the K user groups, and the N frequency domain resources, determine the frequency domain resources of the J users.

5. The method according to claim 4, characterized in that, The priority of the communication requirement is higher than the priority of the perception requirement; The step of determining the frequency domain resources of the J users based on the performance index information, the information of the K user groups, and the N frequency domain resources includes: For the J′ in the kth user group k One user, determine the J′ k Each of the N users has the channel gain over the N frequency domain resources, and selects the d frequency domain resources with the largest channel gain from the N frequency domain resources as the frequency domain resources of the user; d is a positive integer less than N. Wherein, the J′ k Any two users among the N users correspond to d frequency domain resources that are different or partially the same, and the number of users corresponding to each frequency domain resource among the N frequency domain resources does not exceed a predetermined threshold.

6. The method according to claim 4, characterized in that, The priority of the sensing requirement is higher than the priority of the communication requirement; The step of determining the frequency domain resources of the J users based on the performance index information, the information of the K user groups, and the N frequency domain resources includes: Obtain the perception weights of the N frequency domain resources; For the J′ in the kth user group k A user, based on the N frequency domain resources and the J′ k The number of frequency domain resources corresponding to each of the N users is d, and q allocation methods are determined; where each allocation method corresponds to d frequency domain resources out of the N frequency domain resources; q is greater than or equal to J′. k Integers; Based on the perception weights of the N frequency domain resources, the allocation priority of the q allocation methods is determined; Based on the allocation priority of the q allocation methods, select J′ with the highest allocation priority from the q allocation methods. k Allocation method; and according to the J′ k The allocation method determines the J′ k Frequency domain resources for each user.

7. The method according to claim 4, characterized in that, The priority of the communication requirement is the same as the priority of the sensing requirement; The step of determining the frequency domain resources of the J users based on the performance index information, the information of the K user groups, and the N frequency domain resources includes: For the J′ in the kth user group k One user, determine the J′ k Channel gain for each of the N users on the N frequency domain resources; Based on the perceived weights of the N frequency domain resources, determine the expected number of allocations for the N frequency domain resources; According to the J′ k The channel quality index of each user is used to identify users with poor channel quality. For users with poor channel quality, the frequency domain resources of the user are determined based on the user's channel gain on the N frequency domain resources, the expected number of allocations of the N frequency domain resources, and the first allocation rule. The first allocation rule includes one or more of the following: Prioritize the desired number of allocations for the frequency domain resource with the highest perception weight; Select the frequency domain resource with high channel gain from the N frequency domain resources; or... Select the frequency domain resource with high channel gain from the N frequency domain resources, excluding the frequency domain resource with the highest perception weight.

8. The method according to claim 7, characterized in that, The channel quality metric is the root mean square of the sum of the channel gains of the user across the N frequency domain resources.

9. The method according to claim 7 or 8, characterized in that, The method further includes: Regarding the J′ k For users other than those with poor channel quality, based on the channel gain of each user on the N frequency domain resources, d frequency domain resources with large channel gains are selected as the frequency domain resources of each user; d is a positive integer less than N.

10. The method according to claim 6 or 7, characterized in that, The sensing weights of the N frequency domain resources conform to the following formula: Where, ρ n P represents the sensing weight of the nth frequency domain resource among the N frequency domain resources. n This represents the target effective sensing power of the nth frequency domain resource among the N frequency domain resources, where n is an integer from 1 to N, / is a division operation, and Σ is a summation operation.

11. The method according to any one of claims 1-10, characterized in that, The step of determining the target precoding based on the frequency domain resources of the J users and the information of the K user groups includes: Based on the frequency domain resources of the J users, the preset user-level precoding is adjusted to obtain the user-level precoding; Based on the information of the K user groups, the user group-level precoding is determined; The target precoding is obtained based on the target user-level precoding and the user group-level precoding.

12. The method according to claim 11, characterized in that, The target precoding conforms to the following formula: Among them, w jk (n) represents the target precoding of the nth frequency domain resource of the jth user in the kth user group; v jk (n) represents the target user-level precoding of the nth frequency domain resource of the jth user in the kth user group. B k (n) represents the user group-level precoding corresponding to the nth frequency domain resource of the kth user group. M represents the number of transmitting antennas of the network device, and a is the transmission degree of freedom. ∈ is any symbol, and ∈ is the symbol belonging to.

13. The method according to claim 12, characterized in that, The v jk (n) Maximize the sum and rate under preset constraints, where v jk (n) satisfies the following formula: The preset constraints include one or more of the following constraints: First constraint: Where, γ j,k r represents the transmission rate of any user. min N represents the minimum transmission rate. j,k This represents the set of frequency domain resources occupied by any user. The target user group-level precoding is used to eliminate user group-level interference. jk (n) satisfies the following formula: Among them, h jk (n) represents the channel response of the j-th user in the k-th user group on the n-th frequency domain resource. This represents the interference within the k-th user group. Based on the information of the K user groups, it is determined that... It is expressed as the average noise power within the k-th user group; Second constraint: in, P represents the effective sensing power on the nth frequency domain resource. n This represents the preset power threshold for the nth frequency domain resource. Let a represent the covariance matrix of the integrated communication and sensing waveform transmitted on the nth frequency domain resource. n (·) represents the steering vector on the nth frequency domain resource, θ l Indicates the angle of the l-th diameter; Third constraint: ∑ n ∑ k ∑ j ||w jk (n)‖ 2 ≤P t , where ∑ n ∑ k ∑ j ||w jk (n)‖ 2 For the total transmit power, P t This is the preset power threshold.

14. The method according to claim 12, characterized in that, The B k (n) satisfies the following formula: B k (n)=[u r+1,k (n),u r+2,k (n),…,u M,k (n)]; make For the preset block diagonalization precoding, B k (n) is The zero space, for Singular value decomposition yields U k (n) is The left singular vector, for The right singular vector, B k (n) is composed of and The network consists of left singular vectors U corresponding to singular values ​​of zero; M represents the number of transmit antennas of the network device, and r represents... The rank, i.e. the number of data streams.

15. A communication device, characterized in that, It includes units or modules for performing the method as described in any one of claims 1-14.

16. A communication device, characterized in that, It includes a processor and an input / output interface, the input / output interface being used for inputting and / or outputting information, and the processor being used to perform the method as described in any one of claims 1-14.

17. The communication device according to claim 16, characterized in that, It also includes a memory for storing a computer program, which, when executed by the processor, performs the method as described in any one of claims 1-14.

18. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a computer-readable program or instructions that, when executed on a communication device, cause the method described in any one of claims 1-14 to be performed.

19. A computer program product, characterized in that, The computer program product includes a computer program or instructions that, when run on a computer, cause the method as described in any one of claims 1-14 to be performed.

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