Communication method and communication apparatus

Abstract

The present application provides a communication method and a communication apparatus. The method comprises: determining M frequency points, the M frequency points being determined from among Q frequency points on the basis of a first pattern, the first pattern being determined from among a plurality of preconfigured candidate sensing signal patterns on the basis of a sensing requirement parameter, column correlation of an observation matrix corresponding to each of the plurality of candidate sensing signal patterns reaching or approaching the lower bound of the Welch theory, the sensing requirement parameter comprising signal sparsity, and Q and M being integers greater than 1; and sending or receiving a sensing signal on the M frequency points. By means of the method, a clear sparse sensing signal pattern can be provided, so that column correlation of an observation matrix corresponding to the sparse sensing signal pattern is minimized, thereby reducing frequency domain resources occupied by the sensing signal, reducing the computing complexity, achieving efficient allocation of the frequency domain resources, and improving communication performance.

Description

Communication methods and communication devices

[0001] This application claims priority to Chinese Patent Application No. 202410925280.0, filed on July 10, 2024, entitled "Communication Method and Communication Apparatus", the entire contents of which are incorporated herein by reference. Technical Field

[0002] This application relates to the field of communications, and more specifically, to communication methods and communication apparatus. Background Technology

[0003] Wireless sensing technology analyzes changes in wireless signals during propagation to obtain the characteristics of the signal propagation space, thereby enabling scene perception. Taking radar as an example, its basic principle is that the transmitter emits a specific waveform signal, which is transmitted to the receiver through a wireless channel. By analyzing the transmitted and received signals, the characteristics of the wireless channel are obtained, thus achieving wireless sensing.

[0004] Wireless communication can be used to send and receive information between two ends. Its basic principle is that the transmitter transmits a specific waveform signal, which is received by the receiver after passing through the wireless channel. The receiver then processes the signal and demodulates the signal transmitted by the transmitter.

[0005] From the perspective of transmitting, receiving, and transmitting signals, wireless communication and wireless sensing are remarkably similar. Therefore, combining wireless communication and wireless sensing allows for simultaneous communication between the transmitting and receiving ends while simultaneously sensing the surrounding environment. Specifically, sensing signals can be transmitted in the frequency domain, which can be used to carry information exchanged between the transmitting and receiving ends, as well as to sense objects in the surrounding environment.

[0006] In sensing applications, to ensure ranging accuracy, a larger ranging range requires a higher density of sensing signals in the frequency domain. However, a higher density of sensing signals consumes more frequency domain resources, impacting communication performance. Therefore, sparse sensing signals can be used for sensing measurements.

[0007] However, determining the optimal sparse sensing signal pattern and the sparse frequency domain resources used for sensing is an urgent problem to be solved. Summary of the Invention

[0008] This application provides a communication method and a communication device that can determine sparse frequency domain resources for transmitting sensing signals.

[0009] Firstly, a communication method is provided. This method can be executed by a transmitting device or a chip or circuit configured in the transmitting device, or it can be executed by a receiving device or a chip or circuit configured in the receiving device. This application does not limit the execution method; without affecting the understanding of the context, this application will describe the method as being executed by either a transmitting device or a receiving device. The transmitting device can be a network device or a terminal device, and this application does not limit the type of device. The receiving device can be a network device or a terminal device, and this application does not limit the type of device either.

[0010] The method includes: determining M frequency points, wherein the M frequency points are determined from Q frequency points according to a first pattern, wherein the first pattern is determined from a plurality of pre-configured candidate sensing signal patterns according to sensing requirement parameters, wherein the column correlation of the observation matrix corresponding to each candidate sensing signal pattern reaches or approaches the lower bound of the Welch theory, and the sensing requirement parameters include signal sparsity, where Q and M are integers greater than 1; and transmitting or receiving sensing signals on the M frequency points.

[0011] The correlation between any two columns in the observation matrix corresponds to the interference between the two ranging targets, and the maximum number of ranging targets that can be distinguished based on Q frequency points is Q.

[0012] Based on the above scheme, frequency domain resources for sensing can be determined based on the sparse sensing signal pattern provided in this application. Since the column correlation of the observation matrix corresponding to the sparse sensing signal pattern provided in this application reaches or approaches the lower bound of Welch theory, that is, the column correlation of the observation matrix is ​​minimized, thereby minimizing the maximum value of interference between Q ranging targets.

[0013] In one possible implementation, the value of M is determined based on the signal sparsity.

[0014] Based on the above scheme, the number of frequency points used for sensing can be determined by signal sparsity.

[0015] In one possible implementation, the first pattern indicates K frequency points out of N frequency points, and the first pattern is one of the plurality of candidate sensing signal patterns.

[0016] Optionally, the M frequency points are determined from the Q frequency points according to a first pattern, including: the first pattern is determined according to a second pattern, the second pattern is determined according to the first pattern, and the second pattern indicates the M frequency points among the Q frequency points.

[0017] Based on the above scheme, the first pattern is selected from multiple pre-configured candidate sensing signal patterns, thereby minimizing the correlation of the observation matrix columns corresponding to the sparse sensing signal pattern, achieving efficient allocation of frequency domain resources, and improving communication performance.

[0018] In one possible implementation, the sensing requirement parameters may also include one or more of the following parameters: minimum bandwidth, ranging resolution, and maximum unambiguous ranging distance.

[0019] Based on the above scheme, candidate sensing signal patterns that meet the requirements can be flexibly selected according to sensing needs, thereby achieving efficient allocation of frequency domain resources and improving communication performance.

[0020] In one possible implementation, the first pattern corresponds to N frequency points, and the first pattern includes K first indices, which are indices representing the order of the N frequency points arranged in ascending order.

[0021] In one possible implementation, the first pattern includes a first index of the frequency point with the smallest frequency among the K frequency points and K-1 differences, wherein the differences are the absolute values ​​of the differences between two adjacent first indices among the K first indices.

[0022] In one possible implementation, the first pattern includes a first index of the frequency point with the highest frequency among the K frequency points and K-1 differences, wherein the differences are the absolute values ​​of the differences between two adjacent first indices among the K first indices.

[0023] In one possible implementation, the first pattern includes a first index (referred to as index 1) of the frequency point with the smallest or largest frequency among the K frequency points and K-1 differences, wherein the K-1 differences are the absolute values ​​of the differences between the K-1 first indices other than index 1 and index 1.

[0024] In one possible implementation, the first pattern is a bitmap corresponding to the N frequency points, where each bit in the bitmap indicates whether one of the N frequency points is used for sensing.

[0025] In one possible implementation, the first pattern includes an index of multiple frequency point combinations and an index of at least one frequency point in each of the multiple frequency point combinations.

[0026] In one possible implementation, the method further includes: determining the first pattern from the plurality of candidate sensing signal patterns based on the sensing requirement parameters.

[0027] In one possible implementation, the sensing requirement parameters further include minimum bandwidth or ranging resolution, and the method further includes: determining the frequency granularity of the Q frequency points based on the sensing requirement parameters, subcarrier spacing, and the first pattern, wherein determining the M frequency points includes: determining the M frequency points based on the first pattern and the frequency granularity of the Q frequency points.

[0028] Based on the above scheme, efficient allocation of frequency domain resources can be achieved while ensuring ranging resolution.

[0029] In one possible implementation, the sensing requirement parameter further includes the maximum unambiguous ranging distance, and the method further includes: determining the frequency granularity of the Q frequency points based on the sensing requirement parameter and the subcarrier spacing; determining the M frequency points includes: determining the M frequency points based on the first pattern and the frequency granularity of the Q frequency points.

[0030] Based on the above scheme, efficient allocation of frequency domain resources can be achieved while ensuring the maximum unambiguous ranging distance.

[0031] In one possible implementation, the sensing requirement parameters further include ranging resolution and unambiguous ranging distance; or, the sensing requirement parameters further include minimum bandwidth and unambiguous ranging distance. Determining the first pattern from the plurality of candidate sensing signal patterns based on the sensing requirement parameters includes: determining the value of Q based on the sensing requirement parameters and the subcarrier spacing; determining the first pattern based on the value of Q, wherein the first pattern is one of the plurality of candidate sensing signal patterns, and the absolute value of the difference between N and Q corresponding to the first pattern is less than or equal to the absolute value of the difference between N and Q corresponding to other patterns in the plurality of candidate sensing signal patterns.

[0032] The step of determining the value of Q based on the sensing requirement parameters and the subcarrier spacing includes: determining the frequency granularity of the Q frequency points and the bandwidth used for sensing based on the sensing requirement parameters and the subcarrier spacing; determining the value of Q based on the frequency granularity of the Q frequency points and the bandwidth used for sensing; and determining the M frequency points includes: determining the M frequency points based on the first pattern and the frequency granularity of the Q frequency points.

[0033] Based on the above scheme, efficient allocation of frequency domain resources can be achieved while ensuring ranging resolution and maximum unambiguous ranging distance.

[0034] In one possible implementation, before determining the M frequency points, the method further includes: receiving a second index; determining the frequency granularity of the first pattern and the Q frequency points based on the second index; the determination of the M frequency points includes: determining the M frequency points based on the frequency granularity of the first pattern and the Q frequency points.

[0035] Based on the above scheme, the transmitting or receiving device can receive the index corresponding to the pattern and determine the sensing signal based on the pre-configured mapping relationship between the index and the pattern, thus saving signaling resources.

[0036] In one possible implementation, before determining the M frequency points, the method further includes: receiving information about the M frequency points.

[0037] Based on the above scheme, the transmitting or receiving device can receive information about the sensing frequency points sent by the peer or the network side, and then perform sensing and ranging through the determined frequency points.

[0038] In one possible implementation, after determining the M frequency points, the method further includes: sending information about the M frequency points.

[0039] Based on the above scheme, the transmitting or receiving device can send the frequency point information to the peer device after determining the frequency point used for sensing.

[0040] In one possible implementation, the first pattern is the pattern that is closest to the signal sparsity among the patterns that satisfy the sensing requirement parameters, or the first pattern is the pattern that occupies the least frequency domain resources among the patterns that satisfy the sensing requirement parameters.

[0041] Based on the above scheme, the pattern with the least frequency domain resource consumption is determined as the first pattern, thereby saving a portion of frequency domain resources, which can be used for other purposes, thus improving resource utilization.

[0042] Secondly, a communication method is provided, which can be executed by a network device, or by a chip or circuit configured in the network device, without limitation herein. It should be understood that the description of the beneficial effects in the second aspect can refer to the beneficial effects of the relevant implementations in the first aspect.

[0043] The method includes: determining M frequency points, wherein the M frequency points are determined from Q frequency points according to a first pattern, wherein the first pattern is determined from a plurality of pre-configured candidate sensing signal patterns according to sensing requirement parameters, wherein the column correlation of the observation matrix corresponding to each candidate sensing signal pattern reaches or approaches the lower bound of Welch theory, and the sensing requirement parameters include signal sparsity, where Q and M are integers greater than 1; and transmitting information from the M frequency points.

[0044] In one possible implementation, the value of M is determined based on the signal sparsity.

[0045] Based on the above scheme, the number of frequency points used for sensing can be determined by signal sparsity.

[0046] In one possible implementation, the first pattern indicates K frequency points out of N frequency points, and the first pattern is one of the plurality of candidate sensing signal patterns.

[0047] In one possible implementation, the sensing requirement parameters may also include one or more of the following parameters: minimum bandwidth, ranging resolution, and maximum unambiguous ranging distance.

[0048] In one possible implementation, the first pattern corresponds to N frequency points, and the first pattern includes K first indices, which are indices representing the order of the N frequency points arranged in ascending order.

[0049] In one possible implementation, the first pattern includes a first index of the frequency point with the smallest frequency among the K frequency points and K-1 differences, wherein the differences are the absolute values ​​of the differences between two adjacent first indices among the K first indices.

[0050] In one possible implementation, the first pattern includes a first index of the frequency point with the highest frequency among the K frequency points and K-1 differences, wherein the differences are the absolute values ​​of the differences between two adjacent first indices among the K first indices.

[0051] In one possible implementation, the first pattern includes a first index (referred to as index 1) of the frequency point with the smallest or largest frequency among the K frequency points and K-1 differences, wherein the K-1 differences are the absolute values ​​of the differences between the K-1 first indices other than index 1 and index 1.

[0052] In one possible implementation, the first pattern is a bitmap corresponding to the N frequency points, where each bit in the bitmap indicates whether one of the N frequency points is used for sensing.

[0053] In one possible implementation, the first pattern includes an index of multiple frequency point combinations and an index of at least one frequency point in each of the multiple frequency point combinations.

[0054] In one possible implementation, the method further includes: determining the first pattern from the plurality of candidate sensing signal patterns based on the sensing requirement parameters.

[0055] In one possible implementation, the sensing requirement parameters further include minimum bandwidth or ranging resolution, and the method further includes: determining the frequency granularity of the Q frequency points based on the sensing requirement parameters, subcarrier spacing, and the first pattern, wherein determining the M frequency points includes: determining the M frequency points based on the first pattern and the frequency granularity of the Q frequency points.

[0056] In one possible implementation, the sensing requirement parameter further includes the maximum unambiguous ranging distance, and the method further includes: determining the frequency granularity of the Q frequency points based on the sensing requirement parameter and the subcarrier spacing; determining the M frequency points includes: determining the M frequency points based on the first pattern and the frequency granularity of the Q frequency points.

[0057] In one possible implementation, the sensing requirement parameters further include ranging resolution and unambiguous ranging distance; or, the sensing requirement parameters further include minimum bandwidth and unambiguous ranging distance. Determining the first pattern from the plurality of candidate sensing signal patterns based on the sensing requirement parameters includes: determining the value of Q based on the sensing requirement parameters and the subcarrier spacing; determining the first pattern based on the value of Q, wherein the first pattern is one of the plurality of candidate sensing signal patterns, and the absolute value of the difference between N and Q corresponding to the first pattern is less than or equal to the absolute value of the difference between N and Q corresponding to other patterns in the plurality of candidate sensing signal patterns.

[0058] In one possible implementation, determining the value of Q based on the sensing requirement parameters and the subcarrier spacing includes: determining the frequency granularity of the Q frequency points and the bandwidth used for sensing based on the sensing requirement parameters and the subcarrier spacing; determining the value of Q based on the frequency granularity of the Q frequency points and the bandwidth used for sensing; and determining the M frequency points includes: determining the M frequency points based on the first pattern and the frequency granularity of the Q frequency points.

[0059] In one possible implementation, the first pattern is the pattern that is closest to the signal sparsity among the patterns that satisfy the sensing requirement parameters, or the first pattern is the pattern that occupies the least frequency domain resources among the patterns that satisfy the sensing requirement parameters.

[0060] Thirdly, a communication device is provided, which may be a transmitting end device or a receiving end device, or a module or unit (e.g., a chip, a chip system, or a circuit) in the transmitting end device or the receiving end device that corresponds to each of the methods, operations, steps, or actions described in the first aspect above, or a device that can be matched with a terminal.

[0061] In one possible implementation, the communication device includes a transceiver unit (or communication module) and a processing unit (or processing module) connected to the transceiver unit.

[0062] The transceiver unit can perform the receiving and transmitting processes in the first aspect described above, and the processing unit can perform other processes in the first aspect described above besides receiving and transmitting.

[0063] Fourthly, a communication device is provided, which may be a network device, or a module or unit (e.g., a chip, a chip system, or a circuit) in the network device that corresponds to each of the methods, operations, steps, or actions described in the second aspect above, or a device that can be used in conjunction with the network device.

[0064] In one possible implementation, the communication device includes a transceiver unit (or communication module) and a processing unit (or processing module) connected to the transceiver unit.

[0065] The transceiver unit can perform the receiving and sending processes in the second aspect described above, and the processing unit of the communication device can perform other processes in the second aspect described above besides receiving and sending.

[0066] Fifthly, a communication device is provided. This communication device can be either the receiving device or the transmitting device described above. The communication device includes a transceiver, a processor, and a memory. The processor controls the transceiver to transmit and receive signals, the memory stores a computer program, and the processor retrieves and runs the computer program from the memory, causing the communication device to perform the method in any possible implementation of the first or second aspect described above.

[0067] Optionally, there may be one or more processors and one or more memories.

[0068] Alternatively, the memory can be integrated with the processor, or the memory can be set up separately from the processor.

[0069] Optionally, the communication device may also include a transmitter and a receiver.

[0070] Sixthly, a communication system is provided. The communication system includes a sensing device side and / or a network device side, wherein the sensing device side is used to execute the method in any possible implementation of the first aspect described above, and the network device side is used to execute the method in any possible implementation of the second aspect described above.

[0071] For example, the sensing device side can be a terminal device or a network device, or a chip or circuit in the terminal device or network device, or a functional module in the terminal device or network device that can call and execute a program.

[0072] For example, the network device side can be a network device, or a chip or circuit in the network device, or a CU or DU in the network device, or a functional module in the network device that can call and execute a program.

[0073] In a seventh aspect, a computer-readable storage medium is provided. This computer-readable storage medium stores computer program code or instructions that, when executed, cause the method in any of the possible implementations of the first or second aspect to be implemented.

[0074] Eighthly, a chip or chip system is provided. The chip or chip system includes at least one processor coupled to a memory for storing a computer program that, when executed, causes the methods in any of the possible implementations of the first or second aspect to be implemented.

[0075] For example, the chip may include input circuitry or interface for transmitting information or data, and output circuitry or interface for receiving information or data.

[0076] Ninthly, a computer program product is provided. The computer program product includes: computer program code or instructions that, when executed, cause the method in any possible implementation of the first or second aspect to be implemented.

[0077] In a tenth aspect, a computer program is provided. When the computer program is run, it causes the method in any of the possible implementations of the first or second aspect to be implemented.

[0078] It should be understood that the beneficial effects of the third to tenth aspects mentioned above can be referred to the first or second aspects mentioned above and any possible implementation thereof, which will not be elaborated here. Attached Figure Description

[0079] Figure 1 is a schematic diagram of a communication system provided in an embodiment of this application;

[0080] Figure 2 is a schematic diagram of a communication scenario provided in an embodiment of this application;

[0081] Figure 3 is a schematic diagram of a communication scenario provided in an embodiment of this application;

[0082] Figure 4 is a schematic diagram of a communication scenario provided in an embodiment of this application;

[0083] Figure 5 is a schematic diagram of a communication scenario provided in an embodiment of this application;

[0084] Figure 6 is a schematic diagram of a communication scenario provided in an embodiment of this application;

[0085] Figure 7 is a schematic diagram of a communication scenario provided in an embodiment of this application;

[0086] Figure 8 is a schematic diagram of a communication scenario provided in an embodiment of this application;

[0087] Figure 9 is a flowchart of a communication method provided in an embodiment of this application;

[0088] Figure 10 is a flowchart of a communication method provided in an embodiment of this application;

[0089] Figure 11 is a flowchart of a communication method provided in an embodiment of this application;

[0090] Figure 12 is a schematic block diagram of the communication device 10 provided in an embodiment of this application;

[0091] Figure 13 is a schematic diagram of another communication device 20 provided in an embodiment of this application;

[0092] Figure 14 is a schematic diagram of a chip system 30 provided in an embodiment of this application. Detailed Implementation

[0093] To facilitate understanding of the embodiments of this application, the following points are provided.

[0094] First, in this application, "for indicating" can include both direct and indirect indication. When describing an indication information as indicating A, it can include whether the indication information directly indicates A or indirectly indicates A, but does not necessarily mean that the indication information includes A.

[0095] The information indicated by the instruction information is called the instruction-to-be-instructed information. In the specific implementation, there are many ways to instruct the instruction-to-be-instructed information. The instruction-to-be-instructed information can be sent as a whole, or it can be divided into multiple sub-information messages and sent separately. Furthermore, the sending period and / or timing of these sub-information messages can be the same or different. This application does not limit the specific sending method. The sending period and / or timing of these sub-information messages can be predefined, for example, according to a protocol, or configured by the transmitting device by sending configuration information to the receiving device.

[0096] Second, in this application, "at least one" refers to one or more, and "more than one" refers to two or more. Furthermore, in the embodiments of this application, "first," "second," and various numerical designations (e.g., "#1," "#2," etc.) are merely for descriptive convenience and are not intended to limit the scope of the embodiments of this application. The sequence numbers of the processes below do not imply an order of execution; the execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of this application. It should be understood that the objects described in this way can be interchanged where appropriate to describe solutions other than those in the embodiments of this application. In addition, in the embodiments of this application, terms such as "510," "520," etc., are merely identifiers for descriptive convenience and do not limit the order of execution steps.

[0097] Third, in this application, the words "exemplary" or "for example" are used to indicate that something is an example, illustration, or illustration. Any embodiment or design that is described as "exemplary" or "for example" in this application should not be construed as being more preferred or advantageous than other embodiments or designs. Specifically, the use of the words "exemplary" or "for example" is intended to present the relevant concepts in a specific manner.

[0098] Fourth, in the embodiments of this application, "under the circumstances", "when", and "if" can sometimes be used interchangeably. It should be noted that when the distinction is not emphasized, their intended meanings are consistent.

[0099] Fifth, the term "and / or" in the embodiments of this application is merely a description of the relationship between related objects, indicating that three relationships can exist. For example, A and / or B can represent: A existing alone, A and B existing simultaneously, and B existing alone. In addition, the character " / " in this document generally indicates that the related objects before and after it have an "or" relationship.

[0100] Sixth, the various message names or device names involved in the embodiments of this application are merely examples and do not constitute any limitation on the scope of protection of this application. For example, messages may have different names, as long as they can achieve the corresponding functions.

[0101] Seventh, the terms "message", "information", or "information element (IE)" can be used interchangeably in this article. There are no restrictions on the names of messages or information, as long as they can achieve the corresponding functions.

[0102] In this application, "send" and "receive" indicate the direction of signal transmission. For example, "send information to XX" can be understood as the destination of the information being XX, and "send information" can include direct transmission or indirect transmission through other units or modules. "Receive information from YY" can be understood as the source of the information being YY, and "receive information" can include direct reception from YY or indirect reception from YY through other units or modules. Besides air interface transmission or reception signals implemented at the system level, such as network devices or terminal devices, "send" can also be understood as the "output" of a chip interface, and "receive" can also be understood as the "input" of a chip interface. For example, a modem or system-on-a-chip (SoC) chip or system-in-package (SIP) chip transmits or receives signals. "Send" or "receive" can also be performed through device components, for example, by using buses, traces, or interfaces to transmit or receive signals through several parts, modules, or chips of a device.

[0103] The technical solutions in this application will now be described with reference to the accompanying drawings.

[0104] The technical solutions of this application can be applied to satellite communication systems, high altitude platform station (HAPS) communication, and non-terrestrial network (NTN) systems such as unmanned aerial vehicles (UAVs), including integrated communication and navigation (ICAN) systems, GNSS, and ultra-dense low-Earth orbit satellite communication systems. Satellite communication systems can be integrated with traditional mobile communication systems. For example, the mobile communication system can be a fourth-generation (4G) communication system (e.g., Long Term Evolution (LTE) system), a worldwide interoperability for microwave access (WiMAX) communication system, a fifth-generation (5G) communication system (e.g., new radio (NR) system), and future mobile communication systems.

[0105] Figure 1 is a schematic diagram of a communication system applicable to this application. As shown in Figure 1, the communication system 100 includes at least one network device, such as network device 111, network device 112, and network device 113 shown in Figure 1. The wireless communication system may also include at least one terminal device, such as terminal device 121, terminal device 122, terminal device 123, terminal device 124, terminal device 125, terminal device 126, and terminal device 127 shown in Figure 1.

[0106] For example, network devices and terminal devices can communicate with each other, including but not limited to: multi-site transmission, enhanced mobile broadband (eMBB) transmission, etc., wherein network devices 112 and 113 as shown in FIG1 can transmit with terminal device 124 through multi-site transmission, and network device 112 as shown in FIG1 can transmit with terminal devices 121, 122 and 123 through eMBB transmission.

[0107] For example, network devices can also communicate with each other, including but not limited to: backhaul. As shown in FIG1, network device 111 and network device 112 can communicate through backhaul, and network device 111 and network device 113 can also communicate through backhaul. In this case, network device 112 and network device 113 can act as relay nodes in the system.

[0108] For example, terminal devices can also communicate with each other, including but not limited to device-to-device (D2D) transmission. For example, terminal device 122 and terminal device 125 can communicate with each other via D2D transmission as shown in FIG1.

[0109] 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. Network devices can be cellular systems related to the 3rd Generation Partnership Project (3GPP), such as 5G mobile communication systems, or future-oriented evolution systems. Network devices can also be open radio access networks (O-RAN or ORAN), cloud radio access networks (CRAN), or wireless fidelity (WiFi) systems. For example, the network device can be a base station, an evolved NodeB (eNodeB), a next-generation NodeB (gNB) in a 5G mobile communication system, a 3GPP subsequent evolution base station, a transmission reception point (TRP), an access node, a wireless relay node, or a wireless backhaul node in a WiFi system. In communication systems employing different radio access technologies (RATs), the names of devices with base station capabilities may differ. For example, in an LTE system, it may be called an eNB or eNodeB, and in a 5G or NR system, it may be called a gNB. This application does not limit the specific name of the base station. The network equipment may include one or more co-located or non-co-located transmitting and receiving points. Furthermore, the network equipment may include at least one of the following: one or more central units (CUs), one or more distributed units (DUs), and one or more radio units (RUs).

[0110] In different systems, CU (or CU-CP and CU-UP), DU, or RU may have different names, but those skilled in the art will understand their meaning. For example, in an ORAN system, CU can also be called O-CU (open CU), DU can also be called O-DU (open DU), CU-CP can also be called O-CU-CP, CU-UP can also be called O-CU-UP, and RU can also be called O-RU. Any of the units among CU (or CU-CP, CU-UP), DU, and RU in this application can be implemented through software modules, hardware modules, or a combination of software and hardware modules. Exemplarily, the function of CU can be implemented by one entity or different entities. For example, the function of CU can be further divided, that is, the control plane and user plane can be separated and implemented through different entities, namely the control plane CU entity (i.e., the CU-CP entity) and the user plane CU entity (i.e., the CU-UP entity). The CU-CP entity and the CU-UP entity can be coupled with the DU to jointly complete the function of the access network device. For example, the CU (Complex Unit) is responsible for handling non-real-time protocols and services, implementing the functions of the radio resource control (RRC) and packet data convergence protocol (PDCP) layers. The DU (Digital Unit) is responsible for handling physical layer protocols and real-time services, implementing the functions of the radio link control (RLC), media access control (MAC), and physical (PHY) layers. This allows multiple network function entities to implement some of the functions of a radio access network device. These network function entities can be network elements in hardware devices, software functions running on dedicated hardware, or virtualized functions instantiated on a platform (e.g., a cloud platform). Network devices can also include active antenna units (AAUs). The AAU implements some physical layer processing functions, radio frequency processing, and related functions of the active antenna. Since RRC layer information ultimately becomes PHY layer information, or is derived from PHY layer information, in this architecture, higher-layer signaling, such as RRC layer signaling, can also be considered as being sent by the DU, or by the DU+AAU. It is understood that network devices can be one or more of the following: CU nodes, DU nodes, and AAU nodes. Furthermore, a CU can be classified as a network device in the RAN or as a network device in the core network (CN); this application does not impose any limitations on this.For example, in vehicle-to-everything (V2X) technology, the access network equipment can be a roadside unit (RSU). Multiple access network devices in the communication system can be base stations of the same type or different types. Base stations can communicate with terminal devices, or they can communicate with terminal devices through relay stations. In this embodiment, the device used to implement the network device function can be the network device itself, or a device that supports the network device in implementing that function, such as a chip system or a combination of devices or components that can implement the access network device function. This device can be installed in the network device. In this embodiment, the chip system can be composed of chips, or it can include chips and other discrete devices.

[0111] A terminal device is a user-side device with wireless transceiver capabilities. It can be a fixed device, mobile device, handheld device (e.g., mobile phone), wearable device, in-vehicle device, or a wireless device (e.g., communication module, modem, or chip system) built into the aforementioned devices. Terminal devices are used to connect people, objects, and machines, and can be widely used in various scenarios, such as: cellular communication, D2D communication, V2X communication, machine-to-machine / machine-type communications (M2M / MTC), the Internet of Things (IoT), virtual reality (VR), augmented reality (AR), industrial control, self-driving, remote medical care, smart grids, smart furniture, smart offices, smart wearables, smart transportation, smart cities, drones, robots, etc. For example, a terminal device can be a handheld terminal in cellular communication, a communication device in D2D, an IoT device in MTC, a surveillance camera in smart transportation and smart cities, or a communication device on a drone. Terminal equipment is sometimes referred to as user equipment (UE), user terminal, user device, user unit, user station, terminal, access terminal, access station, UE station, remote station, mobile device, or wireless communication device, etc. Terminal equipment can also be a terminal device in an IoT system. IoT is an important component of future information technology development. Its main technical characteristic is connecting objects to networks through communication technology, thereby realizing an intelligent network of human-machine interconnection and machine-to-machine interconnection. In the embodiments of this application, IoT technology can achieve massive connectivity, deep coverage, and terminal power saving through, for example, narrowband (NB) technology. In the embodiments of this application, the device used to implement the functions of the terminal equipment can be the terminal equipment itself, or it can be a device that supports the terminal equipment in implementing the functions, such as a chip system or a combination of devices or components that can implement the functions of the terminal equipment. This device can be installed in the terminal equipment. The terminal typically contains a communication module, circuit, or chip (such as a modem chip, also known as a baseband chip, or a system-on-chip (SoC) chip containing a modem core, or a system-in-package (SIP) chip) that performs the corresponding communication functions. The terminal can also be configured with program instructions for performing corresponding communication functions.

[0112] Network devices and terminal devices 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 satellites. This application does not limit the scenario in which the network devices and terminal devices are located.

[0113] For example, the communication system 100 may further include an application function (AF) network element, which is a control plane network function provided by the operator's network for providing application layer information; the communication system 100 may also include a session management function (SMF) network element, which is a control plane network function provided by the operator's network. In this embodiment, when the communication system 100 includes both AF and SMF network elements, the AF can send service-related information to the network device through the SMF.

[0114] Based on the above communication system, by way of example, the sensing and measurement method provided in this application embodiment can be applied to any of the communication scenarios shown in Figures 2 to 8 below:

[0115] As shown in Figure 2, network devices can act as transmitting and control devices, while terminal devices can act as receiving devices. The sensing signals emitted by the network devices can be received by the terminal devices after being reflected by a car (or other target objects such as bicycles, drones, etc.). After receiving the sensing signals, the terminal devices can perform signal processing at the processing node to obtain the sensing results, which may include information such as distance, speed, angle, and intensity.

[0116] The control device can be used to control the transmitting device to send sensing signals. The processing node can be located at the receiving device, or it can be the receiving device itself; there is no restriction.

[0117] As shown in Figure 3, the terminal device can act as the transmitting device, and the network device can act as the receiving device and control device. The sensing signal emitted by the terminal device can be received by the network device after being reflected by the car (or other targets such as bicycles, drones, etc.). After receiving the sensing signal, the network device can perform signal processing at the processing node to obtain the sensing result. The sensing result can include information such as distance, speed, angle, and intensity.

[0118] As shown in Figure 4, network device 1 can be used as a transmitting device and a control device, and network device 2 can be used as a receiving device. The sensing signal emitted by network device 1 can be received by network device 2 after being reflected by a car (or other targets such as bicycles, drones, etc.). After receiving the sensing signal, network device 2 can perform signal processing at the processing node to obtain the sensing result. The sensing result can include information such as distance, speed, angle, and intensity.

[0119] As shown in Figure 5, terminal device 1 can be used as a transmitting device and a control device, and terminal device 2 can be used as a receiving device. The sensing signal emitted by terminal device 1 can be received by terminal device 2 after being reflected by a car (or other targets such as bicycles, drones, etc.). After receiving the sensing signal, terminal device 2 can perform signal processing at the processing node to obtain the sensing result. The sensing result can include information such as distance, speed, angle, and intensity.

[0120] As shown in Figure 6, network device 1 can be used as a transmitting device, network device 2 can be used as a receiving device, and network device 3 can be used as a control device. The sensing signal emitted by network device 1 can be received by network device 2 after being reflected by a car (or other targets such as bicycles or drones). After receiving the sensing signal, network device 2 can perform signal processing at the processing node to obtain the sensing result. The sensing result can include information such as distance, speed, angle, and intensity.

[0121] As shown in Figure 7, the network device can act as a transmitter, receiver, and control device. The sensing signal emitted by the network device can be received by the network device after being reflected by a car (or other targets such as bicycles or drones). After receiving the sensing signal, the network device performs signal processing at the processing node to obtain the sensing result, which may include information such as distance, speed, angle, and intensity.

[0122] As shown in Figure 8, the terminal device can function as a transmitter, receiver, and controller. The sensing signal emitted by the terminal device is reflected by a car (or other targets such as bicycles or drones) and can be received by the terminal device. After receiving the sensing signal, the terminal device can perform signal processing at the processing node to obtain the sensing result, which may include information such as distance, speed, angle, and intensity.

[0123] Furthermore, while this application uses frequency points to represent frequency resources as an example to illustrate the sensing signal transmission method, frequency resources can also be represented by subcarriers. In this application embodiment, when frequency resources are represented by subcarriers, the frequency of any subcarrier can be represented by the frequency of the subcarrier at its starting position in the frequency domain. For example, if a subcarrier is a frequency band with frequencies from f1 to f2, then the frequency of that subcarrier is f1. Additionally, the frequency of any subcarrier can also be represented by the frequency of that subcarrier at other positions in the frequency domain besides its starting position, such as the frequency of the subcarrier at its ending position in the frequency domain; there are no limitations.

[0124] To facilitate understanding of the embodiments of this application, the basic concepts involved in this application will be explained first.

[0125] 1. Frequency baseline

[0126] The frequency baseline is obtained by subtracting one frequency from another, and the length of the frequency baseline is the absolute value between the two frequencies.

[0127] For two frequency points, the frequency baseline between them is obtained by subtracting the frequency of one frequency point from the frequency of the other. The length of the frequency baseline between the two frequency points is the absolute value of the frequency difference between them. In addition, the frequency baseline formed by multiple frequency points includes the frequency baseline between two different frequency points, as well as the frequency baseline between each frequency point and itself.

[0128] For example, for frequencies f i and f j For the two frequency points, the frequency baseline formed by the two frequency points includes: frequency baseline b ij =f i -f j Frequency baseline b ji =f j -f i Frequency baseline b ii =f i -f i =0 and frequency baseline b jj =f j -f j =0. Where b ij and b ji The lengths are the same, both being f. i and f j The absolute value of the difference between them, i.e., |b ij |=|b ji |=|f i -f j |

[0129] 2. Frequency baseline and ranging applications

[0130] Frequency baselines can be applied to ranging applications. In scenarios integrating wireless sensing and wireless communication, ranging can be achieved by transmitting sensing signals at specific frequencies. Specifically, ranging can be based on the relative phase relationship between sensing signals at different frequencies, and this relative phase relationship can be represented by a frequency baseline.

[0131] For example, the transmitter operates at frequencies f1, f2, ..., f N Sensing signals are transmitted at N frequency points. After a delay τ between the transmission and reception time, the receiving end receives the sensing signals. Compared with the sensing signals transmitted by the transmitting end, the phase of the sensing signal received by the receiving end changes at each frequency point. For example, the magnitude of the phase change of the sensing signal at the frequency point fi can be expressed as 2πf. iτ, i, are integers greater than or equal to 1 and less than or equal to N. It is evident that, for the same delay τ, the phase change of the sensed signal differs at different frequencies. In ranging applications, ranging can be performed based on the phase change difference of the sensed signal between different frequencies. For example, when the sensed signal is at frequency f... i The phase change at the frequency point is related to the phase change at frequency f. j The phase difference between the phase changes at the frequency points Both i and j are integers greater than or equal to 1 and less than or equal to N. Therefore, the phase difference can be represented using the frequency baseline.

[0132] 3. Ranging resolution

[0133] Ranging resolution refers to the minimum distance at which two identical objects can be distinguished. These two identical objects can be those that are identical in size, volume, material, etc. The smaller the ranging resolution value, the higher the ranging resolution and the higher the accuracy of the ranging. Ranging resolution based on a longer frequency baseline is higher than that based on a shorter frequency baseline; the length here refers to the relative length of the two frequency baselines. For example, at frequencies f1, f2, ..., f... N Sensing signals are transmitted at N frequency points, where f1, f2, ..., f N They are arranged in ascending order of frequency. Among these N frequency points, the frequency baseline with the shortest length includes frequency baseline b. 21 =f2-f1, frequency baseline b 21 Corresponding phase change difference The longest frequency baseline is frequency baseline b. N1 =f N -f1, the phase change difference corresponding to the frequency baseline bN1 Where τ is the delay, which is the absolute value of the difference between the time it takes for the receiver to receive the sensing signal and the time it takes for the transmitter to send the sensing signal. When the delay changes by Δτ, that is, when τ changes to τ+Δτ, The change is 2πb 21 (τ+Δτ), The change is 2πb N1 (τ+Δτ). It can be seen that, due to b N1 Greater than b 21 , The change is greater than The change indicates that a longer frequency baseline is more sensitive to changes in delay than a shorter frequency baseline, thus resulting in higher ranging resolution when ranging is performed based on a longer frequency baseline.

[0134] 6. Maximum unambiguous distance for ranging

[0135] The maximum unambiguous distance in ranging refers to the maximum value among the unambiguous distances in ranging, which refers to the range of distances that can be measured from perceived objects.

[0136] When the communication system shown in Figure 1 includes a first device and a second device, the sum of the distances between any point in the sensing area characterized by the unambiguous ranging distance and the first device, and the distance between any point in the sensing area and the second device, is less than the maximum unambiguous ranging distance. Conversely, the sum of the distances between any point on the edge of the sensing area and the first device, and the distance between any point in the sensing area and the second device, is equal to the maximum unambiguous ranging distance. Taking the scenario shown in Figure 2 as an example, and referring to Figure 3, the sensing area is an elliptical region formed by the base station and the mobile phone as foci. The shortest distance between the base station and the mobile phone is R1. The sum of the distances between any point on the ellipse and the base station, and the distance between any point in the ellipse and the mobile phone, is R2+R3. The unambiguous ranging distance is the range from R1 to R2+R3, and the maximum unambiguous ranging distance is R2+R3.

[0137] When the communication system shown in Figure 1 includes a first device but not a second device, and the function of the second device is performed by the first device, the distance from any point within the sensing area characterized by the unambiguous ranging distance to the first device multiplied by two is less than the maximum unambiguous ranging distance. Conversely, the distance from any point on the edge of the sensing area to the first device multiplied by two is equal to the maximum unambiguous ranging distance. Taking the scenario shown in Figure 2 as an example, and referring to Figure 3, the sensing area is a circular area with a radius of R centered on the base station. The unambiguous ranging distance ranges from 0 to 2R, and the maximum unambiguous ranging distance is 2R.

[0138] The maximum unambiguous ranging distance based on a shorter frequency baseline is greater than that based on a longer frequency baseline. Here, "length" refers to the relative length of the two frequency baselines. In ranging applications, when the phase difference between the sensed signal and two frequency points exceeds the range of 0 to 2π, ranging based on this phase difference will result in ambiguity. For example, if the detected phase is , the actual phase difference might be where k is an integer. It is evident that the uncertainty of the actual phase difference leads to ranging ambiguity. Therefore, to ensure unambiguous ranging, the phase difference must be less than 2π, i.e., 2πbτ < 2π. Furthermore, it must satisfy the condition where |b| is the length of the frequency baseline, and τ is the delay, i.e., the absolute value of the difference between the time the receiver receives the sensed signal and the time the transmitter sends the sensed signal. It is clear that the smaller |b| is, the larger τ is, and the greater the maximum unambiguous ranging distance. In other words, the maximum unambiguous ranging distance is greater when using a shorter frequency baseline.

[0139] For the sake of brevity, the maximum unambiguous distance of the ranging will be referred to as the unambiguous distance of the ranging in the following text.

[0140] 7. Observation matrix and column correlation of the observation matrix

[0141] In this paper, the observation matrix refers to the observation matrix corresponding to multiple frequency points, specifically:

[0142] Suppose there are N candidate frequency points in the frequency domain, and K frequency points can be selected from these N frequency points for sensing. The corresponding observation equation can be written in the following form: y = ΦFx = Ψx

[0143] in, Let y be a complex vector of dimension K*1, where each value in y represents the response received at each of the K frequency points. This represents the amplitude of the transmitted signal at different delays. Specifically, x can be represented as:

[0144] Where x1 represents the amplitude of the signal after the transmitted signal x0 passes through the target object 1, corresponding to the time delay τ1, ..., x N This represents the time delay τ of the transmitted signal x0 after it passes through the target object N. N The range.

[0145] In the above formula (1) This represents the Fourier transform matrix, where rows represent changes in the frequency dimension and columns represent changes in the time delay dimension. Specifically, matrix F can be represented in the following form:

[0146] Where Δf represents the interval between two adjacent frequency points.

[0147] In the above formula (1) This represents the frequency selection matrix, which selects K frequency points from N frequency points. Specifically, the matrix Φ can be written in the following form:

[0148] In this matrix, each row has only one element that is 1, and all other elements are 0. Each column has at most one element that is 1. If an element in the q-th column is 1, it means that the q-th frequency point has been selected for sensing. The K frequency points selected from the N frequency points can be numbered, i.e., the frequency points used for sensing can be represented as {f1, f2, ..., f...}. K}

[0149] In the above formula (1) The observation matrix can be represented in the following form:

[0150] In practical applications, most elements in vector x are 0, with only a small number of non-zero elements. For example, we can assume that there are only R non-zero elements. Therefore, even if the number of measurement samples K (i.e., K frequency points) is much less than the number of unknowns N (i.e., the number of target objects N), the values ​​of the R non-zero elements can still be accurately recovered. That is, vector x can be recovered based on K frequency points, and the perception results can be analyzed based on vector x.

[0151] Based on the aforementioned observation matrix, since the goal of sparse sensing signal design is to achieve optimal observation performance by selecting a small number of frequency resources, the column correlation of the matrix can be introduced to quantitatively evaluate its quality. Its column relevance can be defined as:

[0152] Where, ψ′ i The result of normalizing ψ, i.e. Column correlation describes the correlation between two different time delay measurement bases. Ideally, we want each column of the observation matrix to be orthogonal, i.e., the column correlation is 0. However, in practice, when the dimension K of the matrix is ​​less than N, the rank rank(Ψ) of the matrix is ​​less than orthogonal to N, which means that the columns of matrix Ψ cannot be completely orthogonal.

[0153] Since the observation matrix can be written in the following form:

[0154] The correlation between column p and column q can be expressed as:

[0155] Where, τ p =pΔτ,τ q =qΔτ;

[0156] Where Δτ=1 / NΔf

[0157] The above text, in conjunction with Figures 1 and 2, briefly introduces the scenarios in which the communication method provided in the embodiments of this application can be applied, as well as the basic concepts that may be involved in the embodiments of this application.

[0158] Each column in the above observation matrix corresponds to a ranging target. After passing through the ranging target, the transmitted signal can be received by the receiver. The maximum number of ranging targets that can be distinguished based on N candidate frequency points is N. Among these N ranging targets, the distance corresponding to the nth ranging target is n*Δτ*c, which is the sum of the distances from the transmitter to the ranging target and then to the receiver.

[0159] When K frequency points are selected from N uniformly distributed candidate frequency points for sensing, interference will occur between the N ranging targets that can be distinguished based on the N candidate frequency points. In order to reduce this interference, we can try to minimize the maximum value of the interference between the N ranging targets, that is, to minimize the column correlation of the observation matrix corresponding to the K frequency points. For a matrix, when the column correlation between any two columns of the matrix is ​​equal, the column correlation of the matrix reaches the theoretical minimum value. This theoretical minimum value is called the lower bound of the Welch theory.

[0160] Based on this, this application provides examples of determining K frequencies from N frequencies for sensing. In these examples, the column correlations of the observation matrices corresponding to the K frequencies out of the N frequencies all reach or approach the lower bound of the Welch theory, thereby minimizing the maximum value of interference between the N ranging targets. These examples are given in the form of sensing signal patterns, which indicate the K frequencies out of the N frequencies, thus allowing the determination of frequency domain resources for sensing based on the sparse sensing signal patterns provided in this application.

[0161] First, the sparse sensing signal pattern provided in this application will be introduced.

[0162] Based on the above description of the observation matrix, the Welch bound of the observation matrix can be determined.

[0163] For the above observation matrix, the column correlation satisfies the following relationship:

[0164] As can be seen from the above formula, for a given matrix, the upper bound of its column correlation is 1, and the lower bound is... Right now This is the Welch theoretical lower bound for the column correlation of the observation matrix.

[0165] Based on this, this application provides some candidate patterns for sparse sensing signals. Specifically, when selecting K frequency points from N candidate frequency points for sensing, there are a total of Such frequency combinations, in this Among the various frequency point combinations, there may be some frequency point combinations whose column correlation of the observation matrix can reach or approach the lower bound of Welch's theory. In this case, the K frequency points in the frequency point combination whose column correlation of the corresponding observation matrix can reach or approach the lower bound of Welch's theory can be regarded as a candidate sensing signal pattern (referred to as candidate pattern).

[0166] The column correlations of the observation matrices corresponding to the candidate patterns provided in this application all reach or approach the lower bound of the Welch theory. Each candidate pattern includes a combination of frequency points determined from N uniformly distributed frequency points. This combination of frequency points includes K frequency points. That is, each candidate pattern indicates K frequency points out of N frequency points, and the column correlations of the observation matrices corresponding to these K frequency points all reach or approach the lower bound of the Welch theory. Each candidate pattern corresponds to a first parameter N and a second parameter K. The first parameter N is the number of candidate frequency points, and the second parameter K is the number of frequency points selected for sensing.

[0167] In this application, the column correlation of the observation matrix corresponding to the candidate pattern reaches the lower bound of Welch's theory, which can be understood as: the value of the column correlation of the observation matrix corresponding to the candidate pattern is equal to...

[0168] The column correlation of the observation matrix corresponding to the candidate pattern approximates the lower bound of the Welch theory. This can be understood as: the difference between the column correlation value of the observation matrix corresponding to the candidate pattern and the lower bound of the Welch theory is less than or equal to a first threshold. Optionally, the value of the first threshold is, for example, 1 × 10⁻⁶. -6 .

[0169] For the sake of brevity and ease of understanding, the phrase "the column correlation of the observation matrix corresponding to the candidate pattern can reach or approximate the lower bound of the Welch theory" will be referred to as "the candidate pattern can reach or approximate the lower bound of the Welch theory" in the following text.

[0170] For example, Table 1 shows some candidate designs provided in this application. It should be understood that Table 1 is only a partial list of candidate designs for ease of understanding, and all candidate designs provided in this application are listed below.

[0171] Table 1

[0172] Table 1 shows two candidate patterns. For example, when N = 11, K = 5, and the corresponding sparse pattern is 1-3-4-5-9. That is, when there are 11 candidate frequency points, the sparse pattern that reaches or approaches the lower bound of Welch theory includes 5 frequency points. These five frequency points are the 1st, 3rd, 4th, 5th, and 9th frequency points out of the 11 frequency points. It should be understood that 1, 3, 4, 5, and 9 are the first indices of the K frequency points in the N frequency points. Another example is when N = 19, K = 9, and the corresponding sparse pattern... The sparse pattern is 1-4-5-6-7-9-11-16-17, meaning that when there are 19 candidate frequency points, the sparse pattern that reaches or approaches the lower bound of Welch theory includes 9 frequency points. These five frequency points are the 1st, 4th, 5th, 6th, 7th, 9th, 11th, 16th and 17th frequency points out of the 19 frequency points. It should be understood that 1, 4, 5, 6, 7, 9, 11, 16 and 17 are the first indices of the K frequency points in the N frequency points.

[0173] It should be understood that the first index of the K frequency points in the N frequency points refers to the position of the K frequency points in the N frequency points when the N frequency points are arranged in ascending order of frequency.

[0174] Optionally, if the first index of a frequency point is i, it means that the frequency point is the i-th frequency point among N frequency points, and the i-th frequency point is the i-th frequency point arranged in ascending order of frequency among the N frequency points. For example, if the first index of a frequency point is 3, it means that the frequency point is the 3rd in ascending order among the N frequency points.

[0175] For example, when N=11, the first frequency point is the first frequency point among the 11 candidate frequency points arranged in ascending order of frequency, the third frequency point is the third frequency point among the 11 frequency points arranged in ascending order of frequency, and similarly, the fourth, fifth and ninth frequency points are the fourth, fifth and ninth frequency points among the 11 frequency points arranged in ascending order of frequency.

[0176] For example, when N=19, the first frequency point is the first frequency point among the 19 candidate frequency points arranged in ascending order of frequency. Similarly, the 4th, 5th, 6th, 7th, 9th, 11th, 16th, and 17th frequency points are the 4th, 5th, 6th, 7th, 9th, 11th, 16th, and 17th frequency points among the 11 frequency points arranged in ascending order of frequency.

[0177] Optionally, the i-th frequency point can also be the i-th frequency point among N frequency points arranged in descending order of frequency.

[0178] For example, when N=11, the first frequency point is the first frequency point among the 11 candidate frequency points arranged in descending order of frequency, the third frequency point is the third frequency point among the 11 frequency points arranged in descending order of frequency, and similarly, the fourth, fifth and ninth frequency points are the fourth, fifth and ninth frequency points among the 11 frequency points arranged in descending order of frequency.

[0179] For example, when N=19, the first frequency point is the first frequency point among the 19 candidate frequency points arranged in descending order of frequency. Similarly, the fourth, fifth, sixth, seventh, ninth, eleventh, sixteenth, and seventeenth frequency points are the fourth, fifth, sixth, seventh, ninth, eleventh, sixteenth, and seventeenth frequency points among the eleven frequency points arranged in descending order of frequency.

[0180] The following text will use the i-th frequency point as an example, where the i-th frequency point is one of the N frequency points arranged in ascending order of frequency.

[0181] It should be understood that the candidate patterns shown in Table 1 above are presented in the form of an index, which can be called the first index. The first index is the index of the N frequency points arranged in ascending order. It should be understood that candidate patterns can also be represented in other ways.

[0182] Optionally, the candidate pattern includes the first index of the frequency point with the smallest frequency among the K frequency points and K-1 differences, where each difference is the absolute value of the difference between any two adjacent first indices. In this case, the candidate pattern in Table 1 can be represented as:

[0183] Table 2

[0184] As shown in Table 2, the candidate pattern corresponding to one index in Table 2 is the same as the candidate pattern corresponding to the same index in Table 1, only the representation is different.

[0185] Optionally, the candidate pattern includes the first index of the highest frequency among the K frequency points and K-1 differences, where each difference is the absolute value of the difference between any two adjacent first indices. In this case, the candidate pattern in Table 1 can be represented as:

[0186] Table 3

[0187] As shown in Table 3, the candidate pattern corresponding to one index in Table 3 is the same as the candidate pattern corresponding to the same index in Table 1, only the representation is different.

[0188] Optionally, the candidate pattern includes the first index (referred to as index 1) of the frequency point with the smallest or largest frequency among the K frequency points, and K-1 differences. These K-1 differences are the absolute values ​​of the differences between the K-1 first indices (excluding index 1) and index 1. Taking index 1 as the first index of the frequency point with the smallest frequency among the K frequency points as an example, in this case, the candidate pattern in Table 1 can be represented as:

[0189] Table 4

[0190] As shown in Table 4, the candidate pattern corresponding to one index in Table 4 is the same as the candidate pattern corresponding to the same index in Table 1, only the representation is different.

[0191] Optionally, the candidate pattern is a bitmap corresponding to N frequency points, where each bit in the bitmap indicates whether one of the N frequency points is used for sensing. In this case, the candidate patterns in Table 1 can be represented as follows:

[0192] Table 5

[0193] As shown in Table 5, the candidate pattern corresponding to one index in Table 5 is the same as the candidate pattern corresponding to the same index in Table 1, only the representation is different.

[0194] Optionally, the candidate pattern includes an index of multiple frequency point combinations and an index of at least one frequency point in each of the multiple frequency point combinations. For example, among N frequency points arranged in ascending order of frequency, every 5 frequency points are considered as a frequency point combination. In this case, the candidate pattern in Table 1 can be represented as follows:

[0195] Table 6

[0196] As shown in Table 6, the candidate pattern corresponding to one index in Table 6 is the same as the candidate pattern corresponding to the same index in Table 1, only the representation is different.

[0197] Optionally, the candidate pattern includes a bitmap corresponding to N frequency points, which are divided into multiple frequency point combinations. Each frequency point combination includes at least one frequency point. The bitmap includes a first-level bitmap and a second-level bitmap. Each bit in the first-level bitmap indicates whether one of the frequency point combinations is used for sensing. Each group of bits in the second-level bitmap corresponds to one frequency point combination, and one bit in each group indicates whether one of the frequency points in the corresponding frequency point combination is used for sensing. It should be understood that if the first-level bitmap indicates that a frequency point combination is not used for sensing, the second-level bitmap corresponding to that frequency point combination is not included in the bitmap. For example, among the N frequency points arranged in ascending order of frequency, every 3 frequency points are considered as a frequency point combination. In this case, the candidate pattern in Table 1 can be represented as follows:

[0198] Table 7

[0199] As shown in Table 7, the candidate pattern corresponding to one index in Table 7 is the same as the candidate pattern corresponding to the same index in Table 1, only the representation is different.

[0200] Based on the multiple candidate patterns provided in this application, when it is necessary to determine the sensing signal sparsely distributed in the frequency domain and minimize the column correlation of the observation matrix corresponding to the sparse sensing signal, a pattern can be directly selected from the multiple candidate patterns and mapped into a sensing signal, and then sensing can be performed through the mapped sensing signal.

[0201] It should be understood that when it is necessary to determine the frequency domain resources for sensing, the available frequency domain resources can be divided into Q uniformly distributed candidate frequency points according to the sensing requirements, and M frequency points for sensing can be determined from the Q frequency points based on the candidate pattern provided in this application.

[0202] Specifically, a pattern (referred to as the first pattern) can be selected from a pre-configured pool of candidate patterns based on sensing requirements. It should be understood that among all candidate patterns, the value of the first parameter N corresponding to the first pattern is closest to the value of Q. Therefore, based on the K frequency points indicated by the first pattern, M frequency points out of the Q frequency points can be determined. The column correlation of the observation matrix corresponding to these M frequency points reaches or approaches the lower bound of the Welch theory.

[0203] In the first implementation, there exists a candidate pattern where N = Q, and the candidate pattern with N = Q is the first pattern.

[0204] For example, if Q = 11 candidate frequency points are determined based on the sensing requirements, then the first pattern is the pattern corresponding to index 1. As shown in Table 1, the first pattern corresponds to N = 11 and K = 5. The first pattern indicates the 1st, 3rd, 4th, 5th and 9th frequency points among the 11 frequency points. Therefore, the 1st, 3rd, 4th, 5th and 9th frequency points among the Q frequency points can be used as the frequency points for sensing. At this time, M = 5.

[0205] In the second implementation, there is no candidate pattern where N = Q; therefore, N in the first pattern is not equal to Q.

[0206] When the value of N corresponding to the first pattern is greater than Q, if the frequency points indicated by the first pattern include the frequency points between the (Q+1)th and Nth frequency points among the N frequency points (for example, including frequency point 1), then the determined M frequency points do not include frequency point 1. This method is called truncation.

[0207] For example, if Q = 7 candidate frequency points are determined based on the sensing requirements, then the first pattern is the pattern corresponding to index 1. As shown in Table 1, the first pattern corresponds to N = 11 and K = 5. The first pattern indicates the 1st, 3rd, 4th, 5th and 9th frequency points among the 11 frequency points. Therefore, the 1st, 3rd, 4th and 5th frequency points among the Q frequency points can be used as the frequency points for sensing. At this time, M = 4.

[0208] When the value of N corresponding to the first pattern is less than Q, the M frequency points can include only the K frequency points indicated by the first pattern. This method is called zero padding. Alternatively, in addition to including the K frequency points indicated by the first pattern, the M frequency points can also include other frequency points after the K frequency points. This method is called filling. For example, according to the order of the K frequency points indicated by the first pattern, the (N+1)th frequency point in the Q frequency points is taken as the first frequency point, and the frequency points are re-filled by cyclic shifting.

[0209] The following explains the methods for padding with zeros and filling in the blanks:

[0210] For example, if Q = 65 candidate frequency points are determined based on sensing requirements, then the corresponding first pattern is:

[0211] Table 8

[0212] If cyclic shifting is performed, the determined M frequency points are [1-2-3-4-5-7-8-9-10-13-14-15-17-19-20-25-27-28-29-33-34-36-37-39-42-46-49-50-53-55-57-64-65], with a corresponding column correlation of 0.1675 and a Welch theoretical lower bound of 0.1231. If zero-padding is performed, the determined M frequency points are [1-2-3-4-5-7-8-9-10-13-14-15-17-19-20-25-27-28-29-33-34-36-37-39-42-46-49-50-53-55-57], with a corresponding column correlation of 0.129, which is the lower bound of Welch theory. Therefore, zero-padding is the preferred method for determining the M frequency points.

[0213] It should be understood that the maximum number of ranging targets that can be distinguished based on Q candidate frequency points is Q. Since M of these Q frequency points are determined based on the sparse sensing signal pattern provided in this application, the interference between these Q ranging targets can reach or approach the theoretical minimum.

[0214] It should be understood that the aforementioned candidate patterns can be pre-configured in the communication device (e.g., network equipment or terminal equipment). When there is a need for sensing, a pattern can be selected from the pre-configured candidate patterns and mapped into a sensing signal, and then sensing can be performed through the mapped sensing signal.

[0215] Based on the above multiple candidate sensing signal patterns, this application also provides a communication method that can select which sparse sensing signal pattern to use according to sensing requirements, and determine the frequency domain resources used for sensing based on the selected sparse sensing signal pattern.

[0216] It should be understood that the communication method provided in this application embodiment can be applied to systems that communicate using multi-antenna technology, such as the communication system 100 shown in FIG1. ​​This communication system may include at least one network device and / or at least one terminal device. It should also be understood that the embodiments shown below do not particularly limit the specific structure of the execution subject of the method provided in this application embodiment, as long as communication can be performed according to the method provided in this application embodiment by running a program that records the code of the method provided in this application embodiment. For example, the execution subject of the method provided in this application embodiment can be a device, or a functional module within the device capable of calling and executing a program.

[0217] Figure 9 is a schematic flowchart of a communication method 900 provided in this application. It includes the following steps:

[0218] Step 901: The transmitting device, receiving device, or network device determines the first pattern and determines M frequency points based on the first pattern.

[0219] It should be understood that the first pattern is determined from a plurality of pre-configured candidate sensing signal patterns based on sensing requirement parameters.

[0220] The sensing requirements parameters include signal sparsity, and optionally, one or more of the following parameters: minimum bandwidth, ranging resolution, and maximum unambiguous ranging distance. It should be understood that minimum bandwidth refers to the minimum bandwidth required for the sensing service; that is, the bandwidth used for sensing cannot be less than this minimum bandwidth. Since the ranging resolution requirement can be considered as the sensing bandwidth requirement, both the minimum bandwidth and the ranging resolution can be considered as ranging resolution requirement parameters. Signal sparsity refers to the ratio of the number of frequency points used for sensing to the number of candidate frequency points.

[0221] In the first implementation, the transmitting device, receiving device, or network device can determine the sparse sensing signal pattern based on the sensing requirements, that is, it can determine the first pattern from a number of pre-configured candidate sensing signal patterns based on the sensing requirement parameters.

[0222] The following examples illustrate how to determine the first pattern based on perceived demand parameters, and how to determine M frequency points from Q frequency points based on the first pattern. It should be understood that the method for determining the first pattern will differ depending on the perceived demand parameters.

[0223] Example 1

[0224] The perception requirement parameters include the ranging resolution requirement parameters, that is, the perception requirement parameters include the minimum bandwidth B or the ranging resolution Δr.

[0225] In this scenario, the transmitting device, receiving device, or network device can determine the pattern closest to the signal sparsity from a pre-configured pool of candidate sensing signal patterns as the first pattern. Since the first pattern indicates K frequency points out of N frequency points, the number of candidate frequency points Q = N, and correspondingly, the number of frequency points actually used for sensing M = K. Optionally, the pattern with the least frequency domain resource consumption can be determined from the pre-configured pool of candidate sensing signal patterns as the first pattern.

[0226] It should be understood that the pattern with the least frequency domain resource consumption is selected as the first pattern from multiple pre-configured candidate sensing signal patterns, thereby saving a portion of frequency domain resources. These frequency domain resources can be used for other purposes, thus improving resource utilization.

[0227] Since the sensing requirement parameter includes either the minimum bandwidth B or the ranging resolution Δr, the minimum bandwidth B can be determined using this sensing requirement parameter. Specifically, when the sensing requirement parameter includes the ranging resolution Δr:

[0228] Where c is the speed of light under standard atmospheric conditions.

[0229] After determining the first pattern and the minimum bandwidth B, the minimum bandwidth B can be divided into N parts based on the first parameter N, with each part corresponding to a frequency point. Then, the M frequency points used for sensing are the K frequency points indicated by the first pattern.

[0230] Specifically, the maximum sampling interval of the sensing signal in the frequency domain is first determined based on the minimum bandwidth B and N. It should be understood that, in order to meet the ranging resolution requirements, the frequency interval between the frequency points actually used for sensing should be less than or equal to Δf. sensing .

[0231] Then, for the maximum sampling interval Δf sensing Perform a floor operation:

[0232] Optionally, the SCS can be rounded down to the nearest integer multiple, i.e.

[0233] Alternatively, you can round down to the nearest integer multiple of the Block value. It should be understood that the bandwidth of a block is equal to 12 subcarriers.

[0234] Based on the above equation, the frequency granularity Δf′ of the sensed signal in the frequency domain can be determined. sensing That is, a frequency granularity of Q frequency points, and the actual bandwidth used for sensing, B′=NΔf′, can be determined. sensing It should be understood that the frequency granularity of the Q frequency points is the frequency interval between any two adjacent frequency points in these Q uniformly distributed frequency points. It should also be understood that the frequency granularity Δf′ of the Q frequency points... sensing Once determined, the frequency interval between any two frequency points among the M frequency points is greater than the frequency granularity Δf′ of the Q frequency points. sensing .

[0235] Based on the first pattern mentioned above and the frequency granularity Δf′ of Q frequency points. sensing We can determine the M frequency points actually used for sensing, and the frequencies of these M frequency points are k*Δf′ respectively. sensing +PointA

[0236] Where k represents the index of the K frequency points indicated by the first pattern, and point A is the frequency reference point.

[0237] Example 2

[0238] Perception requirements parameters include the maximum unambiguous distance r for ranging. max .

[0239] In this scenario, the transmitting device, receiving device, or network device can determine the pattern closest to the signal sparsity from a pre-configured pool of candidate sensing signal patterns as the first pattern. Since the first pattern indicates K frequency points out of N frequency points, the number of candidate frequency points Q = N, and correspondingly, the number of frequency points M actually used for sensing is also equal to K. Optionally, the pattern with the least frequency domain resource consumption can be determined from the pre-configured pool of candidate sensing signal patterns as the first pattern.

[0240] Because the sensing requirements parameters include the maximum unambiguous distance r for ranging. max Therefore, the sensing service needs to prioritize ensuring the maximum unambiguous ranging distance, and then base its decisions on this maximum unambiguous ranging distance r. max Determine the maximum sampling interval Δf of the sensed signal in the frequency domain. sensing :

[0241] Then, for the maximum sampling interval Δf sensing Perform a floor operation:

[0242] Optionally, the subcarrier spacing (SCS) can be rounded down to the nearest integer multiple, i.e.

[0243] Alternatively, you can round down to the nearest integer multiple of the Block value. It should be understood that the bandwidth of a block is equal to 12 subcarriers.

[0244] Based on the above equation, the frequency granularity Δf′ of the sensed signal in the frequency domain can be determined. sensing This refers to the frequency granularity of Q frequency points. It should be understood that the frequency granularity of Q frequency points is the frequency interval between any two adjacent frequency points in these Q uniformly distributed frequency points. It should also be understood that the frequency granularity Δf′ of Q frequency points... sensing Once determined, the frequency interval between any two frequency points among the M frequency points is greater than the frequency granularity Δf′. sensing .

[0245] In determining the frequency granularity Δf′ of the first pattern and Q frequency points. sensing Then, frequency granularity Δf′ can be based on Q frequency points. sensing The bandwidth B′ actually used for sensing is determined by the first parameter N: B′=NΔf′ sensing

[0246] Based on the first pattern mentioned above and the frequency granularity Δf′ of Q frequency points. sensingIt can be determined that there are M frequency points actually used for sensing, and the frequencies of these M frequency points are respectively

[0247] k*Δf′ sensing +Point A

[0248] Where k represents the index of the K frequency points indicated by the first pattern, and point A is the frequency reference point.

[0249] Example 3

[0250] Perception requirements parameters include the ranging resolution requirement and the maximum unambiguous ranging distance r. max The sensing requirements parameters include the minimum bandwidth B and the maximum unambiguous ranging distance r. max Alternatively, the perception requirement parameters include the ranging resolution Δr and the maximum unambiguous ranging distance r. max .

[0251] In this case, the transmitting device, receiving device, or network device can first determine the minimum bandwidth B based on the ranging resolution requirement parameter. For example, when the sensing requirement parameter includes the ranging resolution Δr:

[0252] It should be understood that the bandwidth actually used for sensing should be an integer multiple of the subcarrier spacing. Furthermore, to meet the ranging resolution requirements, the bandwidth actually used for sensing should be greater than or equal to this minimum bandwidth B. Therefore, the minimum bandwidth B can be rounded up.

[0253] Optionally, you can round down to the nearest integer multiple of SCS.

[0254] Alternatively, you can round down to the nearest integer multiple of the block.

[0255] Based on the above formula, the bandwidth B′ of the sensed signal can be determined. It should be understood that the bandwidth actually used for sensing should be greater than or equal to this bandwidth B′.

[0256] Furthermore, the maximum unambiguous distance r of the ranging measurement can also be used as a basis. max Determine the maximum sampling interval Δf of the sensed signal in the frequency domain. sensing :

[0257] Then, for the maximum sampling interval Δf sensing Perform a floor operation:

[0258] Optionally, the subcarrier spacing (SCS) can be rounded down to the nearest integer multiple, i.e.

[0259] Alternatively, you can round down to the nearest integer multiple of the Block value.

[0260] Based on the above equation, the frequency granularity Δf′ of the sensed signal in the frequency domain can be determined. sensing This refers to the frequency granularity of Q frequency points. It should be understood that the frequency granularity of Q frequency points is the frequency interval between any two adjacent frequency points in these Q uniformly distributed frequency points. It should also be understood that the frequency granularity Δf′ of Q frequency points... sensing Once determined, the frequency interval between any two frequency points among the M frequency points is greater than the frequency granularity Δf′ of the Q frequency points. sensing .

[0261] In determining the bandwidth B′ of the sensed signal and the frequency granularity Δf′ of Q frequency points. sensing Then, the number Q of candidate frequency points of the sensed signal can be determined:

[0262] Based on the value of Q, the first pattern can be determined. The N value of the first pattern is the one closest to Q among all candidate patterns, and N ≤ Q. Optionally, the pattern with the least frequency domain resource consumption can be determined as the first pattern from a pre-configured pool of candidate patterns. Optionally, the pattern closest to the signal sparsity can be determined as the first pattern from a pre-configured pool of candidate patterns.

[0263] The process of selecting the pattern closest to the signal sparsity from a pre-configured pool of candidate patterns as the first pattern can be understood as choosing a pattern whose K / N ratio is closest to the given signal sparsity. For example, if the given signal sparsity is 0.25, and multiple candidate patterns meet the requirements of ranging resolution and maximum unambiguous ranging distance, as shown in pattern 1 and pattern 2, where pattern 1 has a K / N ratio of 0.24 and pattern 2 has a K / N ratio of 0.5, pattern 1 is clearly closer to the given signal sparsity, therefore pattern 1 is preferred as the first pattern.

[0264] Based on the first pattern mentioned above and the frequency granularity Δf′ of Q frequency points. sensing We can determine the M frequency points actually used for sensing, and the frequencies of these M frequency points are k*Δf′ respectively. sensing +Point A

[0265] Where k represents the index of the K frequency points indicated by the first pattern, and point A is the frequency reference point.

[0266] In the second implementation, the sending or receiving device can use a pattern indicated by another device as the first pattern.

[0267] Specifically, the transmitting or receiving device can receive the first pattern and the frequency granularity Δf′ of Q frequency points.sensing For example, the transmitting device can receive the first pattern and the frequency granularity Δf′ of Q frequency points from the receiving device or network device (e.g., SMF network element). sensing Alternatively, the receiving device can receive the first pattern and the frequency granularity Δf′ of Q frequency points from the transmitting device or network device (e.g., an SMF network element). sensing .

[0268] Based on the first diagram and the frequency granularity Δf′ of the Q frequency points. sensing M frequency points can be determined from Q frequency points, and the frequencies of these M frequency points are k*Δf′ respectively. sensing +Point A

[0269] Where k represents the index of the K frequency points indicated by the first pattern, and point A is the frequency reference point.

[0270] In the third implementation, either the sending device or the receiving device can receive a second index sent by another device. For example, the sending device can receive a second index from the receiving device or a network device (e.g., an SMF network element), or the receiving device can receive a second index from the sending device or a network device (e.g., an SMF network element).

[0271] The second index, along with the first pattern and the frequency granularity Δf′ of Q frequency points, is... sensing There is a pre-configured first mapping relationship, so that the transmitting or receiving device can determine the first pattern and the frequency granularity of Q frequency points based on the second index.

[0272] Then, based on the first pattern and the frequency granularity Δf′ of the Q frequency points. sensing From Q frequency points, determine M frequency points, the frequencies of which are k*Δf′. sensing +Point A

[0273] Where k represents the index of the K frequency points indicated by the first pattern, and point A is the frequency reference point.

[0274] The first mapping relationship can be referred to in Table 9. It should be understood that Table 9 is only an example of the first mapping relationship. As long as the sensing requirement parameters are met and the column phase relationship of the observation matrix corresponding to the sparse sensing signal reaches the Welch bound, this application does not limit the specific first mapping relationship.

[0275] Table 9

[0276] S902, the transmitting device transmits sensing signals on M frequency points, and correspondingly, the receiving device receives sensing signals on M frequency points.

[0277] In this process, the sensing signals transmitted by the transmitting device on M frequency points are processed by the target object after passing through the air interface (e.g., reflected by the target object), and the receiving device can receive the sensing signals on M frequency points.

[0278] It should be understood that if the transmitting device determines the first pattern and the M frequency points based on the sensing demand information in step S901, then before step S902, the transmitting device sends the information of the M frequency points to the receiving device.

[0279] Alternatively, if the receiving device determines the first pattern and the M frequency points based on the sensing requirement information in step S901, then before step S902, the receiving device sends the information of the M frequency points to the transmitting device.

[0280] Alternatively, if the network device (e.g., SMF network element) determines the first pattern and the M frequency points based on the sensing demand information in step S901, then before step S902, the network device sends the information of the M frequency points to the transmitting device and the receiving device sends the information of the M frequency points to the transmitting device.

[0281] The information of the M frequency points includes a second index, or the information of the M frequency points includes the first pattern and the frequency granularity of the Q frequency points, or the information of the M frequency points includes a second pattern, which includes the index value of the M frequency points among the Q frequency points.

[0282] For example, the sensing signal can be an orthogonal frequency division multiplexing (OFDM) signal.

[0283] S903, the receiving device performs sensing measurements based on the sensing signal and obtains the sensing measurement results.

[0284] For example, the sensing measurement results can be information such as the distance, angle, speed, position, and intensity of the target object, without limitation.

[0285] Optionally, the receiving device can also feed back the sensing measurement results to the sending device, and correspondingly, the sending device receives the sensing measurement results fed back from the receiving device.

[0286] For example, the receiving device can send the sensing measurement results back to the sending device via an air interface.

[0287] Figure 10 is a schematic flowchart of a communication method 1000 provided in this application. It corresponds to the scheme in method 900 where the network device determines a first pattern and the M frequency points based on perceived demand information, and then sends the information of the M frequency points to the transmitting and receiving devices. It should be understood that method 1000 is a specific implementation of method 900. Method 1000 includes the following steps:

[0288] S1001, any one of the sending device, receiving device, and network device initiates a sensing service request.

[0289] S1002, the transmitting and receiving devices send their respective capability information to the network device, which includes information such as supported frequency bands and bandwidth.

[0290] S1003, the sending end device or the receiving end device sends the sensing requirement parameters to the network device, or the network device determines the sensing requirement parameters according to the sensing service request in step S1001.

[0291] The sensing requirements parameters include one or more of the following: minimum bandwidth, ranging resolution, unambiguous ranging distance, and signal sparsity. It should be understood that minimum bandwidth refers to the minimum bandwidth required for the sensing service; that is, the bandwidth used for sensing cannot be less than this minimum bandwidth. Since the ranging resolution requirement can be considered as the sensing bandwidth requirement, both the minimum bandwidth and the ranging resolution can be considered as parameters related to the ranging resolution requirement. Signal sparsity refers to the ratio of the number of frequency points determined for sensing to the number of candidate frequency points.

[0292] S1004, the network device determines the first pattern from a plurality of pre-configured candidate sensing signal patterns based on sensing requirement parameters, and determines M frequency points based on the first pattern.

[0293] Step S304 can be implemented by referring to the first method of step S901.

[0294] S1005, the network device sends information on M frequency points to the transmitting and receiving devices.

[0295] The information of the M frequency points includes a second index, or the information of the M frequency points includes the first pattern and the frequency granularity of the Q frequency points, or the information of the M frequency points includes the index value of the M frequency points.

[0296] S1006, the transmitting device transmits sensing signals on M frequency points, and correspondingly, the receiving device receives sensing signals on M frequency points.

[0297] S1007, the receiving device performs sensing measurements based on the sensing signal and obtains the sensing measurement results.

[0298] Optionally, the receiving device can also feed back the sensing measurement results to the sending device, and correspondingly, the sending device receives the sensing measurement results fed back from the receiving device.

[0299] Figure 11 is a schematic flowchart of a communication method 1100 provided in this application. It corresponds to the scheme in method 900 where the transmitting device determines a first pattern and the M frequency points based on perceived demand information, and then sends the information of the M frequency points to the receiving device. It should be understood that method 1100 is a specific implementation of method 900. Method 1100 includes the following steps:

[0300] S1101, Either the sending device or the receiving device initiates a sensing service request.

[0301] S1102, the transmitting and receiving devices exchange their respective capability information, which includes information such as supported frequency bands and bandwidth.

[0302] S1103, the transmitting device determines the sensing requirement parameters according to the sensing service request in step S1001.

[0303] The sensing requirements parameters include one or more of the following: minimum bandwidth, ranging resolution, unambiguous ranging distance, and signal sparsity. It should be understood that minimum bandwidth refers to the minimum bandwidth required for the sensing service; that is, the bandwidth used for sensing cannot be less than this minimum bandwidth. Since the ranging resolution requirement can be considered as the sensing bandwidth requirement, both the minimum bandwidth and the ranging resolution can be considered as parameters related to the ranging resolution requirement. Signal sparsity refers to the ratio of the number of frequency points determined for sensing to the number of candidate frequency points.

[0304] S1104, the transmitting device determines the first pattern from a plurality of pre-configured candidate sensing signal patterns based on sensing requirement parameters, and determines M frequency points based on the first pattern.

[0305] Step S404 can be implemented by referring to the first method of step S901.

[0306] S1105, the transmitting device sends information on M frequency points to the receiving device.

[0307] The information of the M frequency points includes a second index, or the information of the M frequency points includes the first pattern and the frequency granularity of the Q frequency points, or the information of the M frequency points includes the index value of the M frequency points.

[0308] S1106, the transmitting device transmits sensing signals on M frequency points, and correspondingly, the receiving device receives sensing signals on M frequency points.

[0309] S1107, the receiving device performs sensing measurements based on the sensing signal and obtains the sensing measurement results.

[0310] Optionally, the receiving device can also feed back the sensing measurement results to the sending device, and correspondingly, the sending device receives the sensing measurement results fed back from the receiving device.

[0311] Optionally, the transmitting device in this application embodiment can be a terminal device or a network device. When the transmitting device is a network device, the processing actions of the network device (such as determining M frequency points, generating sensing signals, etc.) can be executed by the CU and / or DU of the network device, and the transmitting and receiving actions of the network device (such as sending frequency point information of M frequency points, sending sensing signals, receiving sensing measurement results, etc.) can be executed by the RU of the network device.

[0312] Optionally, the receiving device in this application embodiment can be a terminal device or a network device. When the receiving device is a network device, the processing actions of the network device (such as performing sensing measurements, generating sensing measurement results, etc.) can be executed by the CU and / or DU of the network device, and the transmitting and receiving actions of the network device (such as receiving sensing signals, feeding back sensing measurement results, etc.) can be executed by the RU of the network device.

[0313] It is understandable that the CU, DU, and RU of a network device can be deployed independently, or the CU and DU can be deployed in one network device, or the CU, DU, and RU can be deployed in one network device, without any restrictions.

[0314] Below are candidate graphs provided in this application that reach or approximate the lower bound of Welch's theory:

[0315] Optionally, candidate patterns can be classified based on signal sparsity. For example, Table 10 shows candidate patterns with signal sparsity close to 1 / 2.

[0316] Table 10

[0317] Table 11 shows candidate patterns with signal sparsity close to 1 / 4.

[0318] Table 11

[0319] Table 12 shows candidate patterns with a signal sparsity of approximately 1 / 8.

[0320] Table 12

[0321] The communication method provided in the embodiments of this application has been described in detail above with reference to Figures 9 to 11. The above communication method is mainly described from the perspective of interaction between the sending end device and the receiving end device, or between the network device and the sending end device and the receiving end device. It can be understood that, in order to realize the above functions, the first IAB node, the second IAB node, and the network device include the corresponding hardware structure and / or software module for performing each function.

[0322] Those skilled in the art will recognize that, based on the units and algorithm steps described in conjunction with the embodiments disclosed herein, this application can be implemented in hardware or a combination of hardware and computer software. Whether a function is implemented in hardware or by computer software driving hardware depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of this application.

[0323] The communication device provided in this application is described in detail below with reference to Figures 12 to 14. It should be understood that the description of the device embodiments corresponds to the description of the method embodiments. Therefore, for details not described in detail, please refer to the method embodiments above; for brevity, some details will not be repeated.

[0324] This application embodiment can divide the transmitting or receiving device into functional modules according to the above method examples. For example, each function can be divided into its own functional modules, or two or more functions can be integrated into one processing module. The integrated module can be implemented in hardware or as a software functional module. It should be noted that the module division in this application embodiment is illustrative and only represents one logical functional division. In actual implementation, there may be other division methods. The following description uses the division of functional modules according to each function as an example.

[0325] Figure 12 is a schematic block diagram of a communication device 10 provided in an embodiment of this application. The device 10 includes a transceiver module 11 and a processing module 12. The transceiver module 11 can implement corresponding communication functions, and the processing module 12 is used for data processing. In other words, the transceiver module 11 is used to perform operations related to receiving and sending, while the processing module 12 is used to perform other operations besides receiving and sending. The transceiver module 11 can also be referred to as a communication interface or a communication unit.

[0326] Optionally, the device 10 may further include a storage module 13, which can be used to store instructions and / or data. The processing module 12 can read the instructions and / or data in the storage module to enable the device to perform the operation of the device in the aforementioned method embodiments.

[0327] In one design, the device 10 may correspond to the transmitting device in the above method embodiments, or to a component of the transmitting device (such as a chip).

[0328] The device 10 can implement the steps or processes corresponding to those executed by the transmitting device in the above method embodiments. The transceiver module 11 can be used to perform transceiver-related operations of the transmitting device in the above method embodiments, and the processing module 12 can be used to perform processing-related operations of the transmitting device in the above method embodiments.

[0329] When the device 10 is used to execute the method in FIG9, the transceiver module 11 can be used to execute the steps of sending and receiving information in the method, such as step S920; the processing module 12 can be used to execute the processing steps in the method.

[0330] When the device 10 is used to execute the method in FIG10, the transceiver module 11 can be used to execute the step of sending and receiving information in the method; the processing module 12 can be used to execute the processing step in the method.

[0331] When the device 10 is used to execute the method in FIG11, the transceiver module 11 can be used to execute the step of sending and receiving information in the method; the processing module 12 can be used to execute the processing step in the method.

[0332] It should be understood that the specific process of each unit performing the above-mentioned corresponding steps has been described in detail in the above method embodiments, and will not be repeated here for the sake of brevity.

[0333] In another design, the device 10 may correspond to a network device in the above method embodiment, or a component (such as a chip) of a second communication device.

[0334] The device 10 can implement the steps or processes performed by the network device corresponding to the method embodiments described above. The transceiver module 11 can be used to perform the transceiver-related operations of the network device in the method embodiments described above, and the processing module 12 can be used to perform the processing-related operations of the network device in the method embodiments described above.

[0335] When the device 10 is used to execute the method in FIG9, the transceiver module 11 can be used to execute the step of sending and receiving information in the method, such as step S520; the processing module 12 can be used to execute the processing step in the method, such as step S910.

[0336] When the device 10 is used to execute the method in FIG10, the transceiver module 11 can be used to execute the step of sending and receiving information in the method; the processing module 12 can be used to execute the processing step in the method.

[0337] When the device 10 is used to execute the method in FIG11, the transceiver module 11 can be used to execute the step of sending and receiving information in the method; the processing module 12 can be used to execute the processing step in the method.

[0338] It should be understood that the specific process of each unit performing the above-mentioned corresponding steps has been described in detail in the above method embodiments, and will not be repeated here for the sake of brevity.

[0339] It should also be understood that the device 10 here is embodied in the form of a functional module. The term "module" here can refer to an application-specific integrated circuit (ASIC), electronic circuitry, a processor (e.g., a shared processor, a proprietary processor, or a group processor, etc.) and memory for executing one or more software or firmware programs, integrated logic circuitry, and / or other suitable components supporting the described functions. In an alternative example, those skilled in the art will understand that device 10 may specifically be a transmitting device in the above embodiments, used to execute the various processes and / or steps corresponding to the transmitting device in the above method embodiments; or, device 10 may specifically be a network device in the above embodiments, used to execute the various processes and / or steps corresponding to the network device in the above method embodiments; or, device 10 may specifically be a receiving device in the above embodiments, used to execute the various processes and / or steps corresponding to the receiving device in the above method embodiments. To avoid repetition, further details are omitted here.

[0340] The apparatus 10 of each of the above-described schemes has the function of implementing the corresponding steps performed by the devices (such as IAB-donor, IAB-node, and core network elements) in the above-described methods. This function can be implemented by hardware or by hardware executing corresponding software. The hardware or software includes one or more modules corresponding to the above-described functions; for example, the transceiver module can be replaced by a transceiver (for example, the transmitting unit in the transceiver module can be replaced by a transmitter, and the receiving unit in the transceiver module can be replaced by a receiver), and other units, such as processing modules, can be replaced by processors, which respectively execute the transceiver operations and related processing operations in each method embodiment.

[0341] In addition, the transceiver module 11 can also be a transceiver circuit (for example, it may include a receiving circuit and a transmitting circuit), and the processing module can be a processing circuit.

[0342] Figure 13 is a schematic diagram of another communication device 20 provided in an embodiment of this application. The device 20 includes a processor 21, which is used to execute computer programs or instructions stored in a memory 22, or to read data / signaling stored in the memory 22, to perform the methods in the above-described method embodiments. Optionally, there may be one or more processors 21.

[0343] Optionally, as shown in FIG13, the device 20 further includes a memory 22 for storing computer programs or instructions and / or data. The memory 22 may be integrated with the processor 21 or may be disposed separately. Optionally, there may be one or more memories 22.

[0344] Optionally, as shown in FIG13, the device 20 further includes a transceiver 23 for receiving and / or transmitting signals. For example, the processor 21 is used to control the transceiver 23 to receive and / or transmit signals.

[0345] As one option, the device 20 is used to implement the operations performed by the transmitting device in the various method embodiments described above.

[0346] As an alternative, the device 20 is used to implement the operations performed by the receiving device in the various method embodiments described above.

[0347] As another option, the device 20 is used to implement the operations performed by the network device in the various method embodiments described above.

[0348] It should be understood that the processor mentioned in the embodiments of this application can be a central processing unit (CPU), or other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. A general-purpose processor can be a microprocessor or any conventional processor.

[0349] It should also be understood that the memory mentioned in the embodiments of this application can be volatile memory and / or non-volatile memory. Non-volatile memory can be read-only memory (ROM), programmable read-only memory (PROM), erasable programmable read-only memory (EPROM), electrically erasable programmable read-only memory (EEPROM), or flash memory. Volatile memory can be random access memory (RAM). For example, RAM can be used as an external cache. By way of example and not limitation, RAM includes the following forms: static random access memory (SRAM), dynamic random access memory (DRAM), synchronous dynamic random access memory (SDRAM), double data rate synchronous dynamic random access memory (DDR SDRAM), enhanced synchronous dynamic random access memory (ESDRAM), synchronous linked dynamic random access memory (SLDRAM), and direct rambus RAM (DR RAM).

[0350] It should be noted that when the processor is a general-purpose processor, DSP, ASIC, FPGA, or other programmable logic device, discrete gate or transistor logic device, or discrete hardware component, the memory (storage module) can be integrated into the processor.

[0351] It should also be noted that the memory described herein is intended to include, but is not limited to, these and any other suitable types of memory.

[0352] Figure 14 is a schematic diagram of a chip system 30 provided in an embodiment of this application. The chip system 30 (or may also be called a processing system) includes logic circuitry 31 and an input / output interface 32.

[0353] The logic circuit 31 can be a processing circuit in the chip system 30. The logic circuit 31 can be coupled to a memory unit, calling instructions from the memory unit, enabling the chip system 30 to implement the methods and functions of the embodiments of this application. The input / output interface 32 can be an input / output circuit in the chip system 30, outputting processed information from the chip system 30, or inputting data or signaling information to be processed into the chip system 30 for processing.

[0354] As one approach, the chip system 30 is used to implement the operations performed by the transmitting device, receiving device, or network device in the various method embodiments described above.

[0355] For example, logic circuit 31 is used to implement processing-related operations performed by the sending device, receiving device, or network device in the above method embodiments; input / output interface 32 is used to implement sending and / or receiving-related operations performed by the sending device, receiving device, or network device in the above method embodiments.

[0356] This application also provides a computer-readable storage medium storing computer instructions for implementing the methods executed by a sending device, a receiving device, or a network device in the above-described method embodiments.

[0357] For example, when the computer program is executed by a computer, it enables the computer to implement the methods performed by the sending end device, receiving end device, or network device in the various embodiments of the above methods.

[0358] This application also provides a computer program product comprising instructions that, when executed by a computer, implement the methods performed by the sending end device, receiving end device, or network device in the above-described method embodiments.

[0359] This application also provides a communication system, including the aforementioned transmitting end device, receiving end device, or network device.

[0360] The explanations and beneficial effects of the relevant contents in any of the devices provided above can be found in the corresponding method embodiments provided above, and will not be repeated here.

[0361] In the several embodiments provided in this application, it should be understood that the disclosed apparatus and methods can be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative; for instance, the division of units is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the mutual coupling or direct coupling or communication connection shown or discussed may be through some interfaces, and the indirect coupling or communication connection of apparatus or units may be electrical, mechanical, or other forms.

[0362] Those skilled in the art will recognize that the units and algorithm steps of the various examples described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of this application.

[0363] Those skilled in the art will understand that, for the sake of convenience and brevity, the specific working processes of the systems, devices, and units described above can be referred to the corresponding processes in the foregoing method embodiments, and will not be repeated here.

[0364] In the several embodiments provided in this application, it should be understood that the disclosed systems, apparatuses, and methods can be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative; for instance, the division of units is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be through some interfaces; the indirect coupling or communication connection between apparatuses or units may be electrical, mechanical, or other forms.

[0365] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0366] In addition, the functional units in the various embodiments of this application can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit.

[0367] If the aforementioned functions are implemented as software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, or a portion of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of this application. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0368] The above description is merely a specific embodiment of this application, but the scope of protection of this application is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in this application should be included within the scope of protection of this application. Therefore, the scope of protection of this application should be determined by the scope of the claims.

Claims

1. A communication method, characterized in that, include: M frequency points are determined, which are determined from Q frequency points according to a first pattern. The first pattern is determined from a plurality of pre-configured candidate sensing signal patterns according to sensing requirement parameters. The column correlation of the observation matrix corresponding to each candidate sensing signal pattern reaches or approaches the lower bound of the Welch theory. The sensing requirement parameters include signal sparsity, and Q and M are integers greater than 1. Transmit or receive sensing signals at the M frequency points.

2. A communication method, characterized in that, include: M frequency points are determined, which are determined from Q frequency points according to a first pattern. The first pattern is determined from a plurality of pre-configured candidate sensing signal patterns according to sensing requirement parameters. The column correlation of the observation matrix corresponding to each candidate sensing signal pattern reaches or approaches the lower bound of the Welch theory. The sensing requirement parameters include signal sparsity, and Q and M are integers greater than 1. Send information from the M frequency points.

3. The method according to claim 1 or 2, characterized in that, The value of M is determined based on the sparsity of the signal.

4. The method according to any one of claims 1 to 3, characterized in that, The first pattern indicates K frequency points out of N frequency points, and the first pattern is one of the plurality of candidate sensing signal patterns.

5. The method according to any one of claims 1 to 4, characterized in that, The sensing requirements parameters also include one or more of the following parameters: minimum bandwidth, ranging resolution, and maximum unambiguous ranging distance.

6. The method according to any one of claims 1 to 5, characterized in that, The first pattern corresponds to N frequency points. The first pattern includes K first indices, which are indices representing the order of the N frequency points arranged in ascending order, or... The first pattern includes a first index of the frequency point with the smallest frequency among the K frequency points and K-1 differences, where the difference is the absolute value of the difference between any two adjacent first indices among the K first indices, or... The first pattern includes a first index of the frequency point with the highest frequency among the K frequency points and K-1 differences, where the difference is the absolute value of the difference between any two adjacent first indices among the K first indices, or... The first pattern is a bitmap corresponding to the N frequency points, where each bit in the bitmap indicates whether one of the N frequency points is used for sensing, or... The first pattern includes an index of multiple frequency point combinations and an index of at least one frequency point in each of the multiple frequency point combinations.

7. The method according to any one of claims 1 to 6, characterized in that, The method further includes: The first pattern is determined from the plurality of candidate sensing signal patterns based on the sensing requirement parameters.

8. The method according to claim 7, characterized in that, The sensing requirements parameters also include minimum bandwidth or ranging resolution. The method further includes: determining the frequency granularity of the Q frequency points based on the sensing requirement parameters, subcarrier spacing, and the first pattern. Determining the M frequency points includes: determining the M frequency points based on the first pattern and the frequency granularity of the Q frequency points.

9. The method according to claim 7, characterized in that, The sensing requirement parameters also include the maximum unambiguous ranging distance. The method further includes: determining the frequency granularity of the Q frequency points based on the sensing requirement parameters and the subcarrier spacing; Determining the M frequency points includes: determining the M frequency points based on the first pattern and the frequency granularity of the Q frequency points.

10. The method according to claim 7, characterized in that, The sensing requirement parameters also include ranging resolution and unambiguous ranging distance; alternatively, the sensing requirement parameters also include minimum bandwidth and unambiguous ranging distance. The step of determining the first pattern from the plurality of candidate sensing signal patterns based on sensing requirement parameters includes: The value of Q is determined based on the sensing requirement parameters and the subcarrier spacing; The first pattern is determined based on the value of Q. The first pattern is one of the plurality of candidate sensing signal patterns. The absolute value of the difference between N and Q corresponding to the first pattern is less than or equal to the absolute value of the difference between N and Q corresponding to other patterns among the plurality of candidate sensing signal patterns.

11. The method according to claim 10, characterized in that, The step of determining the value of Q based on the sensing requirement parameters and the subcarrier spacing includes: determining the frequency granularity of the Q frequency points and the bandwidth used for sensing based on the sensing requirement parameters and the subcarrier spacing; The value of Q is determined based on the frequency granularity of the Q frequency points and the bandwidth used for sensing. Determining the M frequency points includes: determining the M frequency points based on the first pattern and the frequency granularity of the Q frequency points.

12. The method according to claim 1, characterized in that, Before determining the M frequency points, the method further includes: Receive the second index; The frequency granularity of the first pattern and the Q frequency points is determined according to the second index; Determining the M frequency points includes: determining the M frequency points based on the first pattern and the frequency granularity of the Q frequency points.

13. The method according to claim 1, characterized in that, Before determining the M frequency points, the method further includes: Receive information from the M frequency points.

14. The method according to claim 1, characterized in that, After determining the M frequency points, the method further includes: Send information from the M frequency points.

15. The method according to any one of claims 1 to 14, characterized in that, The first pattern is the pattern that is closest to the signal sparsity among the patterns that satisfy the sensing requirement parameters, or the first pattern is the pattern that occupies the least frequency domain resources among the patterns that satisfy the sensing requirement parameters.

16. A communication device, characterized in that, include: One or more functional modules for performing the method as described in any one of claims 1 to 15.

17. A communication device, characterized in that, The device includes a processor coupled to a memory for storing computer programs or instructions, and the processor is configured to execute the computer programs or instructions in the memory such that the method as claimed in any one of claims 1 to 15 is performed.

18. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a computer program or instructions that, when executed on a computer, cause the method as described in any one of claims 1 to 15 to be performed.

19. A chip system, characterized in that, Includes: a processor for retrieving and running a computer program from memory, such that the method as described in any one of claims 1 to 15 is performed.

20. A computer program product, characterized in that, When the computer program product is run on a computer, the method as described in any one of claims 1 to 15 is performed.

21. A chip, characterized in that, The chip is installed in a communication device. The chip includes a processor and a communication interface. The processor reads instructions and runs them through the communication interface, causing the communication device to perform the method as described in any one of claims 1 to 15.

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