Communication method and apparatus

Abstract

A communication method and apparatus, which can reduce the feedback overhead of sensing information on the basis of the sparsity of wavelet coefficients. The method comprises: an apparatus for acquiring sensing information performs M-level discrete wavelet transform on the sensing information to obtain a sensing information codebook, and sends the sensing information codebook to a network, wherein the network may recover the sensing information on the basis of the sensing information codebook. The sensing information may comprise sensing data at each position point within a sensing space. The sensing information codebook comprises a scale coefficient codebook of the highest decomposition level (i.e., the M-th level) and wavelet coefficient codebooks of all decomposition levels (i.e., M levels). Each of the M wavelet coefficient codebooks is in one-to-one correspondence with each level of discrete wavelet transform. The j-th wavelet coefficient codebook comprises some of the wavelet coefficients obtained after j-th level discrete wavelet transform, j = 1, 2,…, and M, M being a positive integer greater than or equal to 1.

Description

Communication methods and devices

[0001] This application claims priority to Chinese Patent Application No. 202411050209.9, filed with the State Intellectual Property Office of China on July 31, 2024, entitled "Communication Method and Apparatus", the entire contents of which are incorporated herein by reference. Technical Field

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

[0003] Sensing is generally categorized into single-site sensing and dual-site sensing. In single-site sensing, the transmitting and receiving ends of the sensing signal are the same device; in dual-site sensing, the transmitting and receiving ends of the sensing signal are two different devices. In an integrated communication and sensing system, the transmitting end of the sensing signal can be a terminal or a base station, and the receiving end of the sensing signal can also be a terminal or a base station.

[0004] When a terminal acts as a receiver of sensing signals, it may need to feed back the sensing information obtained from the sensing signals to the base station. Currently, one method for feeding back sensing information is to divide the sensing space into multiple location grids. The sensing information fed back by the terminal includes the location index of each location grid and the power value of each location grid, where the power value of each location point is quantized using multiple bits.

[0005] To improve imaging resolution and accuracy, the granularity of the aforementioned location grid is small (e.g., reaching the decimeter level), and the number of quantization bits for the power value is high, resulting in the amount of sensing information exceeding gigabits and excessive feedback overhead. Summary of the Invention

[0006] This application provides a communication method and apparatus that can reduce the feedback overhead of perceived information.

[0007] Firstly, a communication method is provided. This method can be executed by a first communication device, a component of the first communication device (such as its processor, chip, or chip system), or a logic module or software capable of implementing all or part of the functions of the first communication device. The method includes: acquiring sensing information, which includes sensing data for each location point within a sensing space; determining a sensing information codebook; and transmitting the sensing information codebook. The sensing information codebook is obtained by performing an M-level discrete wavelet transform on the sensing information. The sensing information codebook includes an M-level scaling coefficient codebook and M wavelet coefficient codebooks. The j-th wavelet coefficient codebook corresponds to the j-th level discrete wavelet transform and includes some wavelet coefficients from the wavelet coefficients obtained after the j-th level discrete wavelet transform, where j = 1, 2, ..., M, and M is a positive integer greater than or equal to 1.

[0008] Based on this scheme, the sensing information feedback unit performs an M-level discrete wavelet transform on the sensing information, including sensing data from all locations within the sensing space, to obtain a sensing information codebook. The sensing information codebook carries the scaling coefficients of the highest decomposition level and some wavelet coefficients from all decomposition levels, and is ultimately reported. Because wavelet coefficients are sparsity—that is, some wavelet coefficient values ​​tend to 0—these partial wavelet coefficients have little or no impact on the recovery of sensing information. Therefore, the partial wavelet coefficients carried in the sensing information codebook can be wavelet coefficients with larger values. This reduces feedback overhead compared to reporting all wavelet coefficients or the original sensing information, without affecting sensing accuracy.

[0009] In one possible design, determining the codebook for the sensing information includes: determining a set of binary wavelet functions based on the basis wavelet functions; and performing an M-level discrete wavelet transform on the sensing information based on the set of binary wavelet functions and the set of binary scaling functions corresponding to the set of binary wavelet functions.

[0010] In one possible design, the perceived information is subjected to an M-level discrete wavelet transform based on the set of binary wavelet functions and the corresponding set of binary scaling functions. This includes: performing a j-level Y-dimensional discrete wavelet transform on the perceived information based on the j-th level binary scaling function in the set of binary scaling functions and the j-th level binary wavelet function in the set of binary wavelet functions, to obtain the j-th level scaling coefficients and j-th level wavelet coefficients, where j = 1, 2, ..., M.

[0011] Based on the two possible implementations mentioned above, the set of binary wavelet functions can be determined based on the basis wavelet functions. Then, based on the set of binary wavelet functions and its corresponding set of binary scaling functions, M-level discrete wavelet transform can be performed on the perceived information, ensuring the execution of the discrete wavelet transform and thus ensuring the generation of the subsequent perceived information codebook.

[0012] In one possible design, the method further includes receiving third indication information and / or fourth indication information. The third indication information indicates a set of basis wavelet functions, where the basis wavelet functions are wavelet functions within the set; or, the third indication information indicates a basis wavelet function. The fourth indication information indicates the discrete wavelet transform series M.

[0013] Based on this possible design, the network can flexibly control the basis wavelet functions and transform series of the discrete wavelet transform, thereby optimizing computational overhead and decomposition performance.

[0014] Secondly, a communication method is provided. This method can be executed by a second communication device, or by a component of the second communication device, such as its processor, chip, or chip system, or by a logic module or software capable of implementing all or part of the functions of the second communication device. The method includes: receiving a sensing information codebook, which includes an M-th level scale coefficient codebook and M wavelet coefficient codebooks, where the j-th wavelet coefficient codebook corresponds to a j-th level discrete wavelet transform, and includes a portion of the wavelet coefficients obtained after the j-th level discrete wavelet transform, j = 1, 2, ..., M, where M is a positive integer greater than or equal to 1; and determining sensing information, which is obtained by performing an M-th level discrete wavelet inverse transform on the sensing information codebook, and includes sensing data for each location point within the sensing space. The technical effects of this second aspect are similar to those of the first aspect described above, and will not be elaborated further here.

[0015] In one possible design, determining the sensing information includes: determining a set of binary wavelet functions based on the basis wavelet functions; and performing an M-level discrete wavelet inverse transform on the sensing information codebook based on the set of binary wavelet functions and the set of binary scaling functions corresponding to the set of binary wavelet functions.

[0016] In one possible design, the perceived information is subjected to an M-level discrete wavelet transform based on the set of binary wavelet functions and the set of binary scaling functions corresponding to the set of binary wavelet functions. This includes: performing an M-level discrete wavelet inverse transform on the M wavelet coefficient codebooks based on the set of binary scaling functions; and performing an M-level discrete wavelet inverse transform on the M-level scale coefficient codebooks based on the binary scaling function corresponding to the M-level scale space in the set of binary scaling functions.

[0017] In one possible design, the method further includes sending a third indication message and / or a fourth indication message. The third indication message indicates a set of basis wavelet functions, where the basis wavelet functions are wavelet functions within the set; or, the third indication message indicates a basis wavelet function. The fourth indication message indicates the discrete wavelet transform series M.

[0018] In combination with the first or second aspect, in one possible design, the j-th wavelet coefficient codebook includes wavelet coefficients that are greater than or equal to the first threshold among the wavelet coefficients obtained after the j-th level discrete wavelet transform.

[0019] Based on this possible design, since higher-valued wavelet coefficients have a greater impact on the recovery of perceived information, while lower-valued wavelet coefficients have a smaller impact on the recovery of perceived information, reporting wavelet coefficients with values ​​greater than or equal to the first threshold in the perceived information codebook, i.e., reporting higher-valued wavelet coefficients, can help the receiver of the perceived information codebook recover perceived information while reducing feedback overhead.

[0020] In combination with the first or second aspect, in one possible design, the first threshold includes M sub-thresholds; the j-th wavelet coefficient codebook includes wavelet coefficients that are greater than or equal to the j-th sub-threshold among the M sub-thresholds obtained after the j-th level discrete wavelet transform.

[0021] Based on this possible design, different thresholds can be set for different wavelet coefficient codebooks, thereby improving the flexibility of wavelet coefficient reporting. This avoids situations where, under a single threshold, all wavelet coefficients obtained from a certain level of wavelet transform are less than that threshold, resulting in the failure to report wavelet coefficients obtained from that level of wavelet transform, thus affecting the recovery of perceived information.

[0022] Combining the first or second aspect, in one possible design, the j-th wavelet coefficient codebook includes indication information j and B. j Wavelet coefficients; where the indicator information j indicates B. j The index of each wavelet coefficient in the j-th level wavelet space is determined based on the perception space.

[0023] Based on this possible design, the mapping relationship between wavelet coefficients and indices (or position points) can be reported in the wavelet coefficient codebook, thereby enabling the receiving end of the sensing information codebook to recover the sensing information based on the mapping relationship, thus improving the reliability of sensing information recovery.

[0024] In conjunction with either the first or second aspect, in one possible design, the instruction information j includes B. j The index of each wavelet coefficient in the j-th order wavelet space; or, the indication information j includes the numerical value j, and the numerical value j is related to B. j The index associations of wavelet coefficients in the j-th order wavelet space.

[0025] Based on this possible design, multiple indication methods for wavelet coefficient indexes are provided, which can improve the flexibility of index indication and make it applicable to various scenarios. For example, if the indication information j includes the index, it can be applied to scenarios where the number of feedback wavelet coefficients is irregular, such as different wavelet coefficient codebooks containing different numbers of wavelet coefficients; if the indication information j includes the numerical value j, it can be applied to scenarios where the number of feedback wavelet coefficients at each level is fixed.

[0026] In conjunction with either the first or second aspect, in one possible design, the j-th wavelet coefficient codebook further includes second indication information, which indicates the number B of wavelet coefficients included in the j-th wavelet coefficient codebook. j .

[0027] In conjunction with either the first or second aspect, in one possible design, where the indication information j includes a numerical value j, the indication information j is carried in a first field, the size of which is... Bit, C represents permutation and combination operation, X is the total number of wavelet coefficients obtained after the j-th level discrete wavelet transform, and X is a positive integer greater than 1.

[0028] Combining the first or second aspect, in one possible design, the Mth wavelet coefficient codebook in the M wavelet coefficient codebooks includes the Mth level B... M The index of wavelet coefficients, B M There are M wavelet coefficients. The i-th wavelet coefficient codebook in the M wavelet coefficient codebook includes those related to B. M The index of each wavelet coefficient corresponds to the i-th level B. i There are wavelet coefficients, i = 1, 2, ..., M-1. Among them, the M-th level B... M The index of each wavelet coefficient is B. M The index of each wavelet coefficient in the M-th wavelet space, which is determined based on the perception space.

[0029] Based on this possible design, since the wavelet space of the later stage can be understood as a downsampling of the wavelet space of the earlier stage, a certain index in the wavelet space of the later stage can correspond to multiple corresponding indices in the wavelet space of the earlier stage. Therefore, the B wavelet space of the Mth stage is reported. M When indexing wavelet coefficients, the i-th level B i The index of each wavelet coefficient is B. M The index of each wavelet coefficient corresponds to the index in the i-th level wavelet space. That is, there is no need to explicitly report the indices of the wavelet coefficients from level M-1 to level 1, which can further reduce the feedback overhead.

[0030] Combining the first or second aspect, in one possible design, the perception space and the j-th level wavelet space are Y-dimensional spaces, j = 1, 2, ..., M, where Y is a positive integer greater than 1. The maximum value of the index in the y-th dimension of the j-th level wavelet space is... Z y To perceive the size of the space in the y-th dimension, This indicates rounding up to the nearest integer.

[0031] Combining the first or second aspect, in one possible design, the M-th level scale coefficient codebook includes P scale coefficients, where:

[0032] Where Y is the dimension of the perceptual space and the M-th scale space, P y,M denoted as the total number of indices in the y-th dimension of the M-th scale space, which is determined based on the perceptual space, and ∏ represents a product.

[0033] Combining the first or second aspect, in one possible design,

[0034] Among them, Z y To perceive the size of the space in the y-th dimension, This indicates rounding up to the nearest integer.

[0035] Based on the above three possible designs, it is possible to realize the transformation from the perception space to the multi-level wavelet space and the scale space, laying the foundation for the multi-level discrete wavelet transform of the perception information, ensuring that the discrete wavelet transform can be executed, thereby obtaining the perception information codebook and reducing feedback overhead.

[0036] Thirdly, a communication device is provided for implementing various methods. The communication device includes modules, units, or means corresponding to the implementation of the methods, wherein the modules, units, or means can be implemented in hardware, software, or by hardware executing corresponding software. The hardware or software includes one or more modules or units corresponding to the functions.

[0037] In some possible designs, the communication device may include a processing module and a transceiver module. The processing module can be used to implement the processing functions in any of the above aspects and any possible implementations thereof. The transceiver module may include a receiving module and a transmitting module, respectively used to implement the receiving function and the transmitting function in any of the above aspects and any possible implementations thereof.

[0038] In some possible designs, the transceiver module can consist of transceiver circuits, transceivers, transceivers, or communication interfaces.

[0039] Fourthly, a communication device is provided, comprising: a processor and a memory; the memory being used to store computer instructions that, when executed by the processor, cause the communication device to perform the method described in any of the above aspects and any possible design thereof.

[0040] Fifthly, a communication device is provided, comprising: a processor and a communication interface; the communication interface being used to communicate with a module outside the communication device; the processor being used to execute computer programs or instructions to cause the communication device to perform the methods described in any of the above aspects and any possible designs thereof.

[0041] A sixth aspect provides a communication device comprising: at least one processor; said processor being configured to execute a computer program or instructions stored in a memory to cause the communication device to perform the methods described in any of the foregoing aspects and any possible designs thereof. The memory may be coupled to the processor, or may be independent of the processor.

[0042] In a seventh aspect, a communication device (e.g., a chip or chip system) is provided, the communication device including a processor for implementing the functions involved in any of the above aspects and any possible designs thereof.

[0043] In some possible designs, the communication device includes a memory for storing necessary program instructions and data.

[0044] In some possible designs, when the device is a chip system, it can be composed of chips or contain chips and other discrete components.

[0045] The communication device described in the third to seventh aspects may be the first communication device in the first aspect, or a device included in the first communication device, such as a chip or chip system; or the communication device may be the second communication device in the second aspect, or a device included in the second communication device, such as a chip or chip system.

[0046] Eighthly, a communication device is provided, which may be a first communication device, or a module or unit (e.g., a chip, chip system, or circuit) in the first communication device that performs the methods / operations / steps / actions described in the first aspect, or a module or unit that can be used in conjunction with the first communication device; or, the communication device may be a second communication device, or a module or unit (e.g., a chip, chip system, or circuit) in the second communication device that performs the methods / operations / steps / actions described in the second aspect, or a module or unit that can be used in conjunction with the second communication device.

[0047] It is understandable that when the communication device provided by any of the third to eighth aspects is a chip, the sending action / function of the communication device can be understood as outputting information, and the receiving action / function of the communication device can be understood as inputting information.

[0048] A ninth aspect provides a computer-readable storage medium storing a computer program or instructions that, when executed on a communication device, enable the communication device to perform the methods described in any of the foregoing aspects and any possible design thereof.

[0049] In a tenth aspect, a computer program product containing instructions is provided, which, when run on a communication device, enables the communication device to perform the methods described in any of the foregoing aspects and any possible design thereof.

[0050] Eleventhly, a communication system is provided, comprising a first communication device and a second communication device. The first communication device is used to implement the method described in the first aspect and any possible design thereof, and the second communication device is used to implement the method described in the second aspect and any possible design thereof.

[0051] The technical effects of any of the design methods in aspects three through eleven can be found in the technical effects of different design methods in aspects one or two, and will not be repeated here. Attached Figure Description

[0052] Figure 1 is a schematic diagram of the perception scene provided in an embodiment of this application;

[0053] Figure 2 is a flowchart illustrating the UE-assisted sensing imaging technology based on base station transmission and terminal reception provided in an embodiment of this application;

[0054] Figure 3 is a schematic diagram of the division of a sensing space provided in an embodiment of this application;

[0055] Figure 4 is a schematic diagram of the structure of a communication system provided in an embodiment of this application;

[0056] Figure 5 is a schematic diagram of another communication system provided in an embodiment of this application;

[0057] Figure 6 is a schematic diagram of another communication system provided in an embodiment of this application;

[0058] Figure 7 is a flowchart illustrating a communication method provided in an embodiment of this application;

[0059] Figure 8 is a schematic diagram of the structure of a perception information codebook provided in an embodiment of this application;

[0060] Figure 9 is a schematic diagram of the perception space and wavelet space provided in the embodiments of this application;

[0061] Figures 10-12 are schematic diagrams of the communication device provided in the embodiments of this application;

[0062] Figure 13 is a schematic diagram of the structure of a processor provided in an embodiment of this application. Detailed Implementation

[0063] In the description of this application, unless otherwise stated, " / " indicates that the objects before and after are in an "or" relationship. For example, A / B can mean A or B. "And / or" in this application is merely a description of the relationship between the related objects, indicating that there can be three relationships. For example, A and / or B can mean: A exists alone, A and B exist simultaneously, and B exists alone. A and B can be singular or plural.

[0064] In the description of this application, unless otherwise stated, "multiple" means two or more. "At least one of the following" or similar expressions refer to any combination of these items, including any combination of a single item or a plurality of items. For example, at least one of a, b, or c can mean: a, b, c, ab, ac, bc, or abc, where a, b, and c can be single or multiple.

[0065] Furthermore, to facilitate a clear description of the technical solutions in the embodiments of this application, the terms "first" and "second" are used in the embodiments of this application to distinguish identical or similar items with substantially the same function and effect. Those skilled in the art will understand that the terms "first" and "second" do not limit the quantity or execution order, and the terms "first" and "second" are not necessarily different.

[0066] In the embodiments of this application, the terms "exemplary" or "for example" are used to indicate that something is an example, illustration, or description. Any embodiment or design that is described as "exemplary" or "for example" in the embodiments of this application should not be construed as being more preferred or advantageous than other embodiments or design. Specifically, the use of terms such as "exemplary" or "for example" is intended to present the relevant concepts in a specific manner to facilitate understanding.

[0067] It is understood that the term "embodiment" used throughout the specification means that a specific feature, structure, or characteristic related to an embodiment is included in at least one embodiment of this application. Therefore, various embodiments throughout the specification do not necessarily refer to the same embodiment. Furthermore, these specific features, structures, or characteristics can be combined in any suitable manner in one or more embodiments. It is understood that in the various embodiments of this application, the sequence number of each process does not imply the order of execution; the execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of this application.

[0068] It is understood that in this application, "...when" and "if" both refer to the corresponding processing that will be carried out under certain objective circumstances, and are not limited to a specific time, nor do they require a judgment action to be performed during implementation, nor do they imply any other limitations.

[0069] It is understood that some optional features in the embodiments of this application can be implemented independently in certain scenarios without relying on other features, such as the current solution on which they are based, to solve the corresponding technical problems and achieve the corresponding effects. Alternatively, they can be combined with other features as needed in certain scenarios. Correspondingly, the apparatus given in the embodiments of this application can also implement these features or functions, which will not be elaborated here.

[0070] In this application, unless otherwise specified, the same or similar parts between the various embodiments can be referred to each other. In the various embodiments of this application, unless otherwise specified or there is a logical conflict, the terminology and / or descriptions between different embodiments are consistent and can be mutually referenced. Technical features in different embodiments can be combined to form new embodiments based on their inherent logical relationships. The following descriptions of the embodiments of this application do not constitute a limitation on the scope of protection of this application.

[0071] To facilitate understanding of the technical solutions of the embodiments of this application, a brief introduction to the relevant technologies of this application is given below.

[0072] 1. Wireless communication:

[0073] In wireless communication systems, communication can be categorized into different types based on the type of transmitter and receiver. For example, sending information from a network device or base station (BS) to a terminal or user equipment (UE) is typically called downlink (DL) communication, while sending information from a terminal to a network device is called uplink (UL) communication.

[0074] In fifth-generation (5G) wireless communication systems, also known as new radio access technology (NR): the physical downlink shared channel (PDSCH) and the physical uplink shared channel (PUSCH) are used for DL ​​(deep downlink) and UL (ultra-low uplink) data transmission, respectively; the physical uplink control channel (PUCCH) is used by the terminal to send feedback information, channel state reports, or uplink scheduling requests; and the physical downlink control channel (PDCCH) is used to transmit downlink control information (DCI), which is mainly used for scheduling decisions of PDSCH, PUSCH, and PUCCH.

[0075] 2. Wireless Sensing:

[0076] Wireless sensing is an important technology for the future. Its technical principles differ somewhat from wireless communication. For example, in wireless communication, the transmitter modulates information onto radio waves and sends it to the receiver, which then demodulates the signal to obtain the information. Wireless sensing, however, requires the transmitter to send radio waves into the surrounding environment. When these radio waves strike the surface of the target, they are reflected, and the receiver receives and processes these reflected waves to obtain information such as the target's position, speed, and type.

[0077] For example, based on whether the perceived target is moving, it can be divided into moving targets (such as vehicles, drones, etc.) and stationary targets (such as roads, tall buildings, etc.). Depending on the method of modeling the scattering points, perceived targets can be divided into point targets (such as small drones) and extended multi-point targets (also known as area targets, such as large buildings, etc.).

[0078] Generally, sensing can be categorized into single-site sensing and dual-site sensing modes. In single-site sensing mode, the transmitting and receiving ends of the sensing signal are the same device. In terms of the sensing process, this station must both transmit and receive the reflected signals from the target surface; therefore, single-site sensing mode can also be called a self-transmitting and self-receiving module.

[0079] In dual-station sensing mode, the transmitting and receiving ends of the sensing signals are two different devices. From the sensing process perspective, station A transmits the sensing signal, and the reflected signal from the target surface is received by station B. Therefore, dual-station sensing mode can also be called self-transmitting and other-receiving or A-transmitting and B-receiving mode.

[0080] 3. Integrated communication and sensing:

[0081] In the evolution of 5G technology towards 5G-Advanced (5G-A) and future communication technologies, integrated communication and sensing technology is considered one of the key technologies for expanding the service capabilities of mobile communication networks. The core idea of ​​this technology is to add sensing capabilities to the mobile communication network, building capabilities for target detection, imaging, and identification, thereby integrating communication and sensing capabilities into a single network to achieve harmonious coexistence and even mutual benefit.

[0082] For example, in the integrated communication sensing technology, from the perspective of sensing modes, it can include the six sensing scenarios shown in Figure 1. Among them, sensing scenario (1) and sensing scenario (4) are single-site sensing modes, where sensing scenario (1) is self-transmitted and self-received by the base station, and sensing scenario (4) is self-transmitted and self-received by the terminal. Sensing scenarios (2), (3), (5), and (6) are dual-site sensing modes, where sensing scenario (2) is transmitted by base station A and received by base station B, sensing scenario (3) is transmitted by the base station and received by the terminal, sensing scenario (5) is transmitted by the terminal and received by the base station, and sensing scenario (6) is transmitted by terminal A and received by terminal B. Among them, sensing scenarios (3)-(6) can also be called UE-assisted sensing scenarios.

[0083] Imaging stationary targets such as high-rise buildings is an important application scenario for integrated communication and sensing technology. In UE-assisted sensing scenarios where the base station transmits and the terminal receives data, the terminal's multi-view and ranging capabilities can be utilized to compensate for the insufficient field of view and imaging accuracy of the base station's self-transmitting and self-receiving mode.

[0084] For example, as shown in Figure 2, the UE-assisted sensing imaging technology based on base station transmission and terminal reception mainly consists of the following three steps:

[0085] 1) The base station sends a sensing signal. After the sensing signal is reflected / scattered by the sensing target, the terminal receives the sensing signal and uses algorithms such as back projection (BP) and discrete fourier transform (DFT) to obtain sensing imaging information.

[0086] Typically, sensing imaging information is a three-dimensional power spectrum consisting of distance, horizontal angle, and vertical angle, with the base station or terminal as the coordinate origin. This three-dimensional sensing power spectrum is composed of the power values ​​of all locations within the sensing range. Each location corresponds to a certain distance, a certain horizontal angle, and a certain vertical angle, and has a unique sensing power value.

[0087] For example, as shown in Figure 3, the sensing space can be divided into multiple location grids, with each location point corresponding to a location grid. The location of the center point of the location grid or its location index is used for indication. The higher the power value of a location point, the stronger the reflection / scattering ability of the sensing signal through that location point, and the more likely that a sensing target exists at that location point; otherwise, if the power value of the location point is very low, it indicates that there may be no sensing target at that location point.

[0088] 2) The terminal feeds back the sensing and imaging information to the base station. Correspondingly, the base station receives the sensing and imaging information fed back by the terminal.

[0089] The sensing imaging information includes the power values ​​of all locations within the sensing space (or sensing coverage area). The power value of each location is quantized using multiple bits.

[0090] To improve imaging resolution and accuracy, the aforementioned location grid is divided into smaller granularities (e.g., reaching the decimeter level), and the number of quantization bits for the power values ​​is also higher, with the amount of bits of perceived imaging information typically exceeding gigabit. Here, gigabit (Gbits) represents a gigabit (equivalent to a billion bits of information).

[0091] 3) The base station processes the perceived imaging information.

[0092] For example, the base station fuses the sensing and imaging information fed back by the terminal with other sensing and imaging information (such as sensing and imaging information fed back by other terminals or sensing and imaging information received by the base station itself) to reconstruct the surrounding environment. In this process, the fusion of sensing and imaging information can increase the power value of locations where sensing targets exist, thereby improving imaging accuracy.

[0093] The above scheme requires the terminal to report the power values ​​of all locations in the sensing space, that is, the power values ​​need to be reported point by point. However, since the granularity of the location grid reaches the decimeter level, the location points in the sensing space are dense, and the quantization bits of the power values ​​are also large, resulting in the number of bits of sensing imaging information exceeding gigabit, and the feedback overhead is too high.

[0094] Based on this, this application provides a communication method in which the transmitting end of the sensing information can perform discrete wavelet transform on the sensing information and report the scale coefficients and wavelet coefficients after the discrete wavelet transform, thereby utilizing the sparsity of the wavelet coefficients to reduce the feedback overhead of the sensing information.

[0095] The technical solutions of this application embodiment can be used in various communication systems, including 3GPP communication systems such as 4th generation (4G) systems (e.g., Long Term Evolution (LTE) systems), 5G systems (e.g., NR systems), LTE and 5G hybrid networking systems, integrated communication and sensing systems, non-terrestrial networks (NTN), device-to-device (D2D) communication systems, vehicle-to-everything (V2X) communication systems, machine-type communication (MTC) systems, Internet of Things (IoT) systems, or other future communication systems. The communication system can also be a non-3GPP communication system; there is no limitation on this.

[0096] The communication systems described above are merely illustrative examples, and are not limited to those described herein. The communication systems provided in this application do not impose any limitations on the solutions described herein. This will be explained uniformly here and will not be repeated below.

[0097] Figure 4 illustrates a possible, non-limiting system diagram. As shown in Figure 4, the communication system 40 includes a radio access network (RAN) 400 and a core network (CN) 500. Optionally, it may also include the Internet (not shown in Figure 4). The RAN 400 includes at least one RAN node (410a and 410b in Figure 4, collectively referred to as 410) and at least one terminal (420a-420j in Figure 4, collectively referred to as 420). The core network 500 includes at least one core network device.

[0098] Optionally, RAN 400 may also include other RAN nodes, such as wireless relay equipment and / or wireless backhaul equipment (not shown in Figure 4). Terminal 420 is wirelessly connected to RAN node 410. RAN node 410 is wirelessly or wired connected to core network 500. The core network equipment in core network 500 and RAN node 410 in RAN 400 can be different physical devices, or they can be the same physical device integrating core network logical functions and wireless access network logical functions.

[0099] In one possible implementation, RAN 400 can be a 3GPP-related cellular system, such as a 4G or 5G mobile communication system, an NTN system (e.g., an NTN supporting pass-through mode and / or regenerative mode, or an NTN supporting eye-viewing mode (earth fixed cell) and / or non-eye-viewing mode (earth moving cell), or a future-oriented evolution system. RAN 400 can also be an open RAN (O-RAN or ORAN), a cloud radio access network (CRAN), or a wireless fidelity (WiFi) system. RAN 400 can also be a communication system integrating two or more of the above systems.

[0100] In some scenarios, the roles of RAN node 410 and terminal 420 are relative. For example, in Figure 4, network element 420i can be a helicopter or drone, which can be configured as a mobile base station. For terminal 420j accessing RAN 400 through network element 420i, network element 420i is a base station; but for base station 410a, network element 420i is a terminal. RAN node 410 and terminal 420 are sometimes referred to as communication devices. For example, in Figure 4, network elements 410a and 410b can be understood as communication devices with base station functions, and network elements 420a-420j can be understood as communication devices with terminal functions.

[0101] In one possible implementation, RAN node 410 is a network-side device with wireless transceiver capabilities. RAN nodes, sometimes also referred to as RAN entities or access nodes, constitute part of the communication system and are used to assist terminals in achieving wireless access. Multiple RAN nodes 410 in the communication system 20 can be of the same type or different types.

[0102] As one possible implementation, RAN node 410 can be a base station, an evolved NodeB (eNodeB), an access point (AP), a transmission reception point (TRP), a next-generation NodeB (gNB) in a 5G mobile communication system, a base station evolved from a 3GPP system, a base station in a future mobile communication system, an access node in a WiFi system, a wireless relay node, a wireless backhaul node, etc. For example, a RAN node can contain one or more co-located or non-co-located transmission reception points.

[0103] For example, a RAN node can be a macro base station (as shown in Figure 4, 410a), a micro base station or indoor station (as shown in Figure 4, 410b), a relay node or donor node, or a radio controller in a CRAN scenario. Optionally, a RAN node can also be a server, wearable device, vehicle, or in-vehicle equipment. For example, in V2X technology, a RAN node can be a roadside unit (RSU).

[0104] As another possible implementation, multiple RAN nodes collaborate to assist terminal devices in achieving wireless access, with different RAN nodes each implementing some of the functions of the access network equipment. For example, RAN nodes can be central units (CU), distributed units (DU), CU-control plane (CP), CU-user plane (UP), radio units (RU), or sensing units (SU), etc.

[0105] For example, the CU and DU can be configured separately or included in the same network element, such as in the baseband unit (BBU). The RU can be included in radio frequency equipment or radio frequency units, such as in a remote radio unit (RRU), an active antenna unit (AAU), or a remote radio head (RRH).

[0106] 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 an O-RAN central unit (O-CU), DU can also be called an O-RAN distributed unit (O-DU), CU-CP can also be called an O-RAN central unit control plane (O-CU-CP), CU-UP can also be called an O-RAN central unit user plane (O-CU-UP), and RU can also be called an O-RAN radio unit (O-RU).

[0107] For example, the SU is mainly used to implement sensing-related functions, such as sending sensing signals and / or receiving echo signals of sensing signals, performing corresponding signal processing based on the received echo signals to obtain sensing measurement data, performing sensing-related processing, or sending and / or receiving sensing information / sensing data, etc.

[0108] For example, SU can be a function or entity within the access network device, or it can be a function or entity outside the access network device. SU can also have other names, which are not specifically limited in this application.

[0109] As another possible implementation, the RAN node can also be a non-real time ran intelligent controller (Non-RT RIC or NRT RIC) and / or a near-real time ran intelligent controller (Near-RT RIC or nRT RIC).

[0110] Non-RT RIC is used to implement non-real-time intelligent management of the RAN, enabling artificial intelligence (AI) / machine learning (ML) for model training and updates, and guiding applications / functions within the Near-RT RIC based on policies. Near-RT RIC is used to implement near real-time intelligent management of the RAN, achieving near real-time control and optimization of O-RAN modules and resources through data collection and related operations on the E2 interface. The E2 interface can be understood as an open interface between two nodes (or endpoints).

[0111] All or part of the functions of the RAN node in this application can also be implemented through software functions running on hardware, or through virtualization functions instantiated on a platform (e.g., a cloud platform), or through software modules, hardware modules, or a combination of software and hardware modules. The RAN node in this application can also be a logical node, logical module, or software capable of implementing all or part of the functions of the access network equipment, or a device with some access network equipment functions, such as a chip system, which can be installed in the access network equipment.

[0112] In one possible implementation, the core network equipment may refer to the equipment in the core network 500 that provides service support to the terminal. In this embodiment, the core network equipment in the core network 500 includes sensing function (SF) network elements. SF network elements are mainly used to implement sensing functions, which may include, for example, sensing control functions and / or sensing computing functions. Furthermore, the SF network elements can also support sensing billing functions when the terminal and / or RAN node perform sensing operations.

[0113] For example, the sensing control function may include identifying sensing devices, sensing nodes, etc. A sensing device can be understood as a device that transmits and / or receives sensing signals. Furthermore, the sensing device performs corresponding signal processing based on the received echo signals to obtain sensing measurement data. For example, the sensing device can be a RAN node or a terminal, etc. A sensing node can refer to a network node in a wireless network that participates in the sensing service process. The sensing computing function may include performing corresponding signal processing on the echo signals received by the sensing device to obtain sensing measurement data, and further processing based on the sensing measurement data and application information to obtain sensing results, etc.

[0114] For example, an SF network element can sometimes be called a communication device; for instance, an SF network element can be understood as a communication device with core network sensing capabilities. Furthermore, an SF network element can also be called a sensing server, etc., without limitation.

[0115] In one possible scenario, the functionality of the SF network element can be implemented by the network data analytics function (NWDAF) network element, or the SF network element and the NWDAF network element can be co-located. Alternatively, the SF network element can be deployed integrated with the core network or deployed independently.

[0116] Optionally, in addition to SF network elements, the core network equipment in Core Network 500 may also include at least one of the following: access and mobility management function (AMF) network elements, session management function (SMF) network elements, user plane function (UPF) network elements, policy control function (PCF) network elements, unified data management (UDM) network elements, application function (AF) network elements, network exposure function (NEF) network elements, and location management function (LMF) network elements. Of course, Core Network 500 may also include other core network equipment without limitation.

[0117] The AMF (Agency Flow Management) network element is primarily responsible for mobility management in mobile networks, such as user location updates, user registration with the network, and user handover. The SMF (Signal Flow Management) network element is primarily responsible for session management in mobile networks, such as session establishment, modification, and release. The UPF (User Plane Functional Element) network element is responsible for connecting to external networks and processing user packets, such as forwarding and accounting. The PCF (Package Flow Management) network element is primarily responsible for providing policies to the AMF and SMF, such as Quality of Service (QoS) policies and slice selection policies. The UDM (User DM) network element is used to store user data, such as subscription information and authentication / authorization information. The AF (Agency Flow Management) network element is responsible for providing services to the 3GPP network. The NEF (Network Flow Equipment) network element is mainly used to open up the capabilities of various network functions and is responsible for converting internal and external information. The LMF (Location Flow Management) network element is primarily responsible for location management, such as initiating location procedures and locating specific terminals.

[0118] It should be noted that in this application, network elements can also be referred to as entities or functional entities. For example, an SF network element can also be referred to as an SF entity or an SF functional entity. In addition, the aforementioned AMF network elements, SMF network elements, UPF network elements, PCF network elements, UDM network elements, AF network elements, NEF network elements, and LMF network elements may have other names in future communication systems, and this application does not impose specific limitations on them.

[0119] For example, Figure 5 shows a specific implementation of the system shown in Figure 4. In this system, the SF network element has interfaces with other network elements such as the AMF, allowing them to communicate. For instance, the SF network element has an NS1 interface with the AMF network element, an NS2 interface with the NEF network element, an NS3 interface with the UDM network element, an NS4 interface with the NWDAF network element, an NS6 interface with the LMF network element, an NS5 interface with the PCF network element, and an NS7 interface with the UPF network element. It is understood that the interfaces between the SF network element and other network elements may have other names, and this application does not specifically limit them.

[0120] As one possible implementation, sensing control signaling between SF network elements and RAN nodes / terminals can be transmitted through AMF network elements or directly (e.g., there is a communication interface between RAN nodes and SF network elements). Sensing measurement data acquired by RAN nodes / terminals can be transmitted to SF network elements via control plane or user plane. Specifically, when sensing measurement data is transmitted via user plane, it can be forwarded through UPF or directly transmitted to SF network elements; when sensing measurement data is transmitted via control plane, it can be forwarded through AMF network elements.

[0121] As one possible implementation, when the RAN transmits sensing information / sensing data to the CB, as shown in Figure 6, the SU can transmit sensing information / sensing data to the SF network element through the AMF or UPF network element; or the CU can transmit sensing information / sensing data to the SF network element through the AMF or UPF network element; or the SU or CU can directly transmit sensing information / sensing data to the SF network element, for example, there is a communication interface between the SU and the SF network element, or there is a communication interface between the CU and the SF network element.

[0122] As shown in Figure 6, the SU can connect to SF network elements (directly or indirectly). For example, the SU can interact with SF network elements to meet related sensing requirements. Furthermore, the SU can also connect to other core network elements such as AMF and UPF network elements. On the RAN side, the SU can connect to CU, DU, or RU; for example, there may be a communication interface between the CU and SU. There may or may not be a communication interface between the SU and DU. If there is no communication interface between the SU and DU, they can communicate through the CU.

[0123] Based on the architecture shown in Figure 6, when the terminal reports sensing information / sensing data to the RAN, the transmission path of the sensing information / sensing data can be: terminal → DU → CU → SU, or the transmission path can be: terminal → DU → SU, or the terminal can directly send sensing information / sensing data to the SU through the interface between the terminal and the SU (such as S-Uu).

[0124] In one possible implementation, terminal 420 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, etc.) built into the aforementioned devices. The terminal is used to connect people, objects, and machines, and can be widely used in various scenarios, such as: cellular communication, D2D communication, V2X communication, MTC communication, IoT, virtual reality (VR), augmented reality (AR), industrial control, self-driving, remote medical care, smart grid, smart furniture, smart office, smart wearables, smart transportation, smart city, drones, robots, etc. For example, a terminal can be a handheld terminal in cellular communication, a communication device in D2D, an IoT device in MTC, a camera in intelligent transportation and smart cities, or a communication device on a drone; or, a terminal can be a mobile phone, tablet computer, computer with wireless transceiver capabilities, wearable device, vehicle, drone, helicopter, airplane, ship, robot, robotic arm, smart home device, etc. The embodiments of this application do not limit the device form of the terminal. A terminal may sometimes be referred to as a 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.

[0125] It should be noted that the system described in the embodiments of this application is for the purpose of more clearly illustrating the technical solutions of the embodiments of this application, and does not constitute a limitation on the technical solutions provided in the embodiments of this application. As those skilled in the art will know, with the evolution of network architecture and the emergence of new business scenarios, the technical solutions provided in the embodiments of this application are also applicable to similar technical problems.

[0126] The communication method provided in this application will be described below with reference to the communication system shown in Figure 4, taking the interaction between communication devices as an example. It should be noted that in the following embodiments of this application, the message names, parameter names, or information names between communication devices are just examples, and other names may be used in other embodiments. The method provided in this application does not specifically limit these names.

[0127] It is understood that in the embodiments of this application, each communication device may execute some or all of the steps in the embodiments of this application. These steps or operations are merely examples, and the embodiments of this application may also execute other operations or variations thereof. Furthermore, the steps may be executed in different orders as presented in the embodiments of this application, and it is not necessary to execute all the operations in the embodiments of this application.

[0128] It is understood that this application uses a communication device as an example to illustrate the interaction, but this application does not limit the execution subject of the interaction. For example, the method executed by the communication device in this application can also be executed by a module (e.g., a chip, chip system, or processor) applied to the communication device, or it can be implemented by a logic node, logic module, or software that can implement all or part of the functions of the communication device.

[0129] The communication method provided in the embodiments of this application will be described below. As shown in FIG7, the communication method may include the following steps:

[0130] S701, The first communication device acquires sensing information. The sensing information includes sensing data for each location point within the sensing space.

[0131] In one possible implementation, the first communication device is a receiver of the sensing signal. The transmitter of the sensing signal can be the first communication device, or it can be another communication device other than the first communication device, without limitation. For example, the first communication device can be a terminal, or it can be a RAN node.

[0132] For example, when the first communication device is a terminal, the transmitting end of the sensing signal can be a RAN node, another terminal, or the first communication device; when the first communication device is a RAN node, the transmitting end of the sensing signal can be a terminal, another RAN node, or the first communication device, without limitation. When both the transmitting end and the receiving end of the sensing signal are the first communication device, it is a self-transmitting and self-receiving mode.

[0133] For example, the sensing data can be determined based on the sensing signal, and the sensing information can include the sensing data of each location point within the sensing space. For instance, the transmitting end of the sensing signal can send the sensing signal to the surrounding environment, and the first communication device receives the sensing signal reflected by the target, processes the received sensing signal reflected by the target, obtains the sensing data of each location point within the sensing space, and uses the sensing data of each location point as sensing information. This application does not limit the way the first communication device processes the sensing signal reflected by the target.

[0134] Furthermore, this application does not specifically limit the implementation of the first communication device acquiring sensing information. In addition to the methods exemplified above, the first communication device may also acquire sensing information from other devices, such as other devices sending sensing information to the first communication device. In this case, the first communication device may not be the receiving end of the sensing information.

[0135] In one possible implementation, the sensing space can also be understood as the sensing coverage area corresponding to the sensing signal. Therefore, the sensing space can also be called the sensing coverage area, and the two can be used interchangeably. This will be used consistently here, and will not be repeated in subsequent embodiments. In addition, the sensing space can have other names, and this application does not specifically limit the name of the sensing space.

[0136] As one possible implementation, the perception space is a Y-dimensional space, where Y is a positive integer greater than 1. For example, Y equals 2 or Y equals 3. Exemplarily, this Y-dimensional perception space can be at least two of the following dimensions: distance dimension, horizontal angle dimension, or vertical angle dimension. For example, it can be a three-dimensional space including distance, horizontal, and vertical dimensions, or a two-dimensional space including any two of these dimensions. Of course, the perception space can also be a Y-dimensional space including other dimensions; this application does not limit the specific dimensions of the perception space.

[0137] For example, the distance dimension can also be called the subcarrier dimension, the horizontal angle dimension can also be called the horizontal dimension or the horizontal direction dimension, and the vertical angle dimension can also be called the vertical dimension or the vertical direction dimension. Of course, the distance dimension, the horizontal angle dimension, or the vertical angle dimension can also have other names, and this application does not specifically limit them.

[0138] For ease of description, the following embodiments of this application use a three-dimensional space including distance, horizontal, and vertical dimensions as an example for illustration. It is understood that the methods of the embodiments of this application are still applicable to perception spaces with other dimensions, and the distance, horizontal, or vertical dimensions described below can be replaced with other dimensions for understanding; further details will not be provided.

[0139] As one possible implementation, the size of the sensing space can be determined based on the configuration parameters of the sensing signal. For example, when the first communication device is a terminal, the RAN node can send configuration information of the reference signal to the terminal, and the terminal receives this configuration information from the RAN node, which includes the configuration parameters of the reference signal.

[0140] For example, the configuration parameters of the reference signal configured in the RAN node may include: the number of subcarriers N0, the number of horizontal ports N1, the number of vertical ports N2, the subcarrier oversampling factor O0, the horizontal oversampling factor O1, and the vertical oversampling factor O2. In this case, the sensing space includes N0O0 values ​​in the distance dimension, N1O1 values ​​in the horizontal angle dimension, and N2O2 values ​​in the vertical angle dimension; or, the sensing space has a size of N0O0 in the distance dimension, N1O1 in the horizontal angle dimension, and N2O2 in the vertical angle dimension. Therefore, the sensing space can be considered to include a total of N0O0N1O1N2O2 location points.

[0141] The number of subcarriers can be understood as the number of subcarriers occupied by the sensing signal. The number of horizontal ports can be understood as the number of horizontal antenna ports occupied by the sensing signal or used to transmit the sensing signal. The number of vertical ports can be understood as the number of vertical antenna ports occupied by the sensing signal or used to transmit the sensing signal.

[0142] As one possible implementation, the sensing data of a location point in the sensing space can be the power value of the sensing signal received or reflected at that location point, or it can be other sensing data, such as the amplitude value of the sensing signal received or reflected at that location point. This application does not limit the specific form of the sensing data. For example, the sensing data of a certain location point in the sensing space can be represented as P(s,m,n), s∈[0,N0O0-1],m∈[0,N1O1-1],n∈[0,N2O2-1]. Here, s can be understood as the index of the distance dimension, or the subcarrier index after oversampling; m can be understood as the horizontal angle index or horizontal direction index after oversampling; and n can be understood as the vertical angle index or vertical direction index after oversampling.

[0143] As one possible implementation, the sensing space can use the location of the transmitting or receiving end of the sensing signal as the origin of the coordinate system. The distance R(s) between a certain location point and the origin, the horizontal angle θ(m) in the horizontal dimension, and the vertical angle θ(n) in the vertical dimension satisfy:

[0144] Where c is the speed of light, Δf is the spacing between adjacent subcarriers used to transmit sensing signals, i.e., the subcarrier spacing, λ is the subcarrier wavelength, d1 is the spacing between antenna ports in the horizontal direction, and d2 is the spacing between antenna ports in the vertical direction. The explanations of s, m, and n can be found in the aforementioned related explanations and will not be repeated here.

[0145] It should be noted that step S701 is an optional step, meaning that step S701 can be omitted.

[0146] S702, The first communication device determines the sensing information codebook.

[0147] In one possible implementation, the first communication device can perform an M-level discrete wavelet transform (DWT) on the sensed information to determine the sensed information codebook. That is, the sensed information codebook can be considered to be obtained by performing an M-level discrete wavelet transform on the sensed information. M is a positive integer greater than or equal to 1.

[0148] For example, after the first communication device performs an M-level discrete wavelet transform on the sensed information, it can obtain M-level scaling coefficients and M-level wavelet coefficients. The j-th scaling coefficient in the M-level scaling coefficients and the j-th wavelet coefficient in the M-level wavelet coefficients are obtained after performing a j-th level discrete wavelet transform on the sensed information, where j = 1, 2, ..., M.

[0149] For example, the j-th level scaling coefficients include multiple scaling coefficients, and the j-th level wavelet coefficients include multiple wavelet coefficients. That is, the j-th level scaling coefficients include all scaling coefficients obtained after the j-th level discrete wavelet transform, and the j-th level wavelet coefficients include all wavelet orders obtained after the j-th level discrete wavelet transform.

[0150] The perceptual information codebook includes an M-th level scaling coefficient codebook and M wavelet coefficient codebooks. The j-th wavelet coefficient codebook in the M wavelet coefficient codebooks corresponds to the j-th level discrete wavelet transform. The j-th wavelet coefficient codebook includes some or all of the wavelet coefficients obtained after the j-th level discrete wavelet transform, where j = 1, 2, ..., M.

[0151] In other words, the Mth-level scale coefficients after performing an M-level discrete wavelet transform on the perceived information can be quantized into an Mth-level scale coefficient codebook; some or all of the wavelet coefficients in the jth-level wavelet coefficients after performing an M-level discrete wavelet transform on the perceived information can be quantized into the jth wavelet coefficient codebook, and finally the M wavelet coefficient codebooks in the perceived information codebook are obtained.

[0152] As one possible implementation, the j-th wavelet coefficient codebook includes wavelet coefficients that are greater than or equal to the first threshold among the wavelet coefficients obtained after the j-th level discrete wavelet transform.

[0153] As an example, the first threshold is a threshold A, and all wavelet coefficients in the j-th wavelet coefficient codebook are greater than or equal to the first threshold A.

[0154] As another example, the first threshold includes M sub-thresholds {A1, A2, ..., A...} M}, the wavelet coefficients in the j-th wavelet coefficient codebook are greater than or equal to the j-th sub-threshold A among the M sub-thresholds. j .

[0155] For example, the first threshold A or M sub-thresholds {A1, A2, ..., A M The parameters can be predefined by the protocol, preconfigured by the RAN node, preconfigured by the core network element (such as the SF network element), or determined by the first communication device itself, without restriction.

[0156] As another possible implementation, the j-th wavelet coefficient codebook includes high-priority wavelet coefficients from the wavelet coefficients obtained after the j-th level discrete wavelet transform. For example, the wavelet coefficients obtained after the j-th level discrete wavelet transform can be divided into high-priority wavelet coefficients and low-priority wavelet coefficients, and the j-th wavelet coefficient codebook includes high-priority wavelet coefficients. Furthermore, the embodiments of this application do not specifically limit the method of classifying the high and low priorities of wavelet coefficients.

[0157] S703, the first communication device sends the sensing information codebook. Correspondingly, the second communication device receives the sensing information codebook.

[0158] In one possible implementation, the second communication device may or may not be a transmitter of sensing signals. For example, the second communication device may be a sensing control node, a sensing center node, etc., without limitation. For instance, the product form of the second communication device may be a RAN node, such as a SU, or it may be a core network element, such as an SF network element.

[0159] As one possible implementation, when the first communication device is a terminal and the second communication device is a SU, the terminal can send a perception information codebook to the DU, and then the DU sends the perception information codebook to the CU, and the CU sends the perception information codebook to the SU; or, the terminal can send a perception information codebook to the DU, and then the DU sends the perception information codebook to the SU through the interface between the DU and the SU; or, the terminal can send the perception information codebook to the SU through the interface between the terminal and the SU (such as the S-Uu interface).

[0160] As another possible implementation, when the first communication device is an access network device and the second communication device is an SF network element, the SU may send the perception information codebook to the SF network element through the AMF network element or the SMF network element; or the CU may send the perception information codebook to the SF network element through the AMF network element or the UPF network element; or the SU may send the perception information codebook to the SF network element through the interface between the SU and the SF network element; or the CU may send the perception information codebook to the SF network element through the interface between the CU and the SF network element.

[0161] S704. The second communication device determines the sensing information based on the sensing information codebook.

[0162] As one possible implementation, the second communication device can perform an M-level discrete wavelet inverse transform on the sensing information codebook to determine the sensing information. That is, the sensing information can be considered as obtained by performing an M-level discrete wavelet inverse transform on the sensing information codebook. The sensing information includes sensing data for each location point within the sensing space. Refer to the descriptions of sensing space, location points, and sensing data in step S701 above; they will not be repeated here.

[0163] For example, the sensing information determined by the second communication device based on the sensing information codebook can be exactly the same as the sensing information obtained by the first communication device in step S701, or it can be sensing information with a certain degree of loss of precision based on the sensing information obtained by the first communication device in step S701. The certain degree of loss of precision can be understood as precision that does not affect the sensing performance, or precision that has a very small impact on the sensing performance.

[0164] As one possible implementation, after determining the sensing information, the second communication device can perform corresponding processing based on the sensing information, such as determining the target's position, time delay, speed, etc., or it can fuse with sensing information from other devices to reconstruct the surrounding environment, etc. This application does not make specific limitations in this regard.

[0165] Based on the above scheme, an M-level discrete wavelet transform is performed on the sensing information, including sensing data from all locations within the sensing space, to obtain a sensing information codebook. The sensing information codebook carries the scaling coefficients of the highest decomposition level (i.e., the M-th level scaling coefficient codebook) and partial wavelet coefficients from all decomposition levels (i.e., M wavelet coefficient codebooks, which may include some wavelet coefficients from the wavelet coefficients obtained after the j-th level discrete wavelet transform). Finally, the sensing information codebook is reported. Because wavelet coefficients are sparsity, meaning some wavelet coefficient values ​​tend to 0, their impact on the recovery of sensing information is small or even negligible. Therefore, the partial wavelet coefficients carried in the sensing information codebook can be wavelet coefficients with larger values. This reduces feedback overhead compared to reporting all wavelet coefficients or the original sensing information, without affecting sensing accuracy.

[0166] The overall process of the communication method provided in this application has been described above. The relevant steps and information in the communication method will be described in detail below.

[0167] In one possible implementation, step S702 above, where the first communication device determines the sensing information codebook, may include the following steps S7021 and S7022 (not shown in FIG7):

[0168] S7021. The first communication device determines the set of binary wavelet functions based on the basis wavelet functions.

[0169] As one possible implementation, the basis wavelet function belongs to a set of basis wavelet functions, which includes at least one wavelet function. For example, the set of basis wavelet functions could be {Haar, Bior, db}, where Haar, Bior, and db each represent a wavelet function.

[0170] For example, the set of basis wavelet functions may be predefined by the protocol, or it may be configured by the access network device to the first communication device. For instance, the access network device may send third indication information to the first communication device, which can be used to indicate or configure the set of basis wavelet functions. Subsequently, the first communication device may select a wavelet function from the set of basis wavelet functions as the basis wavelet function, or the access network device may indicate a wavelet function from the set of basis wavelet functions as the basis wavelet function.

[0171] As another possible implementation, a set of basis wavelet functions may not exist; the access network device can indicate the basis wavelet function to the first communication device. For example, the access network device sends third indication information to the first communication device, which indicates the basis wavelet function. For instance, the third indication information includes an identifier for the basis wavelet function.

[0172] In one possible implementation, the set of binary wavelet functions includes the binary wavelet functions corresponding to each dimension of the j-th level wavelet space, j = 1, 2, ..., M. Here, the j-th level wavelet space is a Y-dimensional space, meaning the dimension of the wavelet space is the same as the dimension of the perception space. Furthermore, the binary wavelet function corresponding to each dimension of the j-th level wavelet space can also be understood as the j-th level binary wavelet function.

[0173] As one possible implementation, the j-th order wavelet space is determined based on the perceptual space. For example, the maximum value of the index in the y-th dimension of the j-th order wavelet space is... Among them, Z y To perceive the size of the space in the y-th dimension, This indicates rounding up. That is, the maximum value of the index in the first dimension of the j-th level wavelet space is... The maximum value of the index in the second dimension is And so on, the maximum value of the index in the Y-th dimension is

[0174] For example, taking Y = 3, where the Y dimensions of the perception space are distance, horizontal angle, and vertical angle, and the first dimension of the j-th level wavelet space corresponds to the distance dimension of the perception space, the second dimension corresponds to the horizontal angle dimension of the perception space, and the third dimension corresponds to the vertical angle dimension of the perception space, the index in the first dimension of the j-th level wavelet space can be represented as k, where the maximum value of k is... The index in the second dimension of the j-th level wavelet space can be represented as l, where the maximum value of l is... The index in the third dimension of the j-th level wavelet space can be represented as i, where the maximum value of i is...

[0175] As one possible implementation, taking Y = 3 as an example, where the Y dimensions of the perception space are distance dimension, horizontal angle dimension, and vertical angle dimension, the binary wavelet function corresponding to the first dimension of the j-th level wavelet space and the basis wavelet function satisfy the following relationship:

[0176] Where ψ(t) is the basis wavelet function. j,k (t) represents the j-th binary wavelet function (or j-th level binary wavelet function) corresponding to the first dimension of the j-th level wavelet space, j = 1, 2, ..., M, or j ∈ [1, M]. k is the index in the first dimension, k = 0, 1, ..., Kj-1, or k ∈ [0, Kj-1]. j -1],

[0177] The binary wavelet function corresponding to the second dimension of the j-th order wavelet space and the basis wavelet function satisfy the following relationship:

[0178] Where ψ(t) is the basis wavelet function. j,l (t) represents the j-th binary wavelet function (or j-th level binary wavelet function) corresponding to the second dimension of the j-th level wavelet space, j = 1, 2, ..., M, or j ∈ [1, M]. l is the index in the second dimension, l = 0, 1, ..., L j -1, or l∈[0,L] j -1],

[0179] The binary wavelet function corresponding to the third dimension of the j-th order wavelet space and the basis wavelet function satisfy the following relationship:

[0180] Where ψ(t) is the basis wavelet function. j,i (t) represents the j-th binary wavelet function (or j-th level binary wavelet function) corresponding to the third dimension of the j-th level wavelet space, j = 1, 2, ..., M, or j ∈ [1, M]. i is the index in the third dimension, i = 0, 1, ..., I. j -1, or i∈[0,I j -1],

[0181] As one possible implementation, taking Y = 3 as an example, where the Y dimensions of the perception space are distance dimension, horizontal angle dimension, and vertical angle dimension, the j-th order wavelet space can be represented in the first dimension as {u j |j∈[1,M]}, or in other words, the first dimension of the j-th order wavelet space can be represented as {u j |j∈[1,M]};The j-th order wavelet space can be represented in the second dimension as {v j |j∈[1,M]}, or in other words, the second dimension of the j-th order wavelet space can be represented as {v j |j∈[1,M]};The j-th order wavelet space can be represented in the third dimension as {w j |j∈[1,M]}, or in other words, the third dimension of the j-th order wavelet space can be represented as {w j |j∈[1,M]}. Where:

[0182] Correspondingly, the j-th level three-dimensional wavelet space can be represented as This represents the Kronecker product. The meaning of each parameter can be found in the relevant explanations above, and will not be repeated here.

[0183] S7022. Perform M-level discrete wavelet transform on the perceived information based on the set of binary wavelet functions and the set of binary scaling functions corresponding to the set of binary wavelet functions.

[0184] As one possible implementation, M can be understood as the discrete wavelet transform level. The access network device can configure the discrete wavelet transform level M to the first communication device. For example, the access network device can send a fourth indication message to the first communication device indicating the discrete wavelet transform level M. For instance, the fourth indication message may include M, or it may include the index of M in the set of discrete wavelet transform levels. This set of discrete wavelet transform levels may include multiple discrete wavelet transform levels, which may be predefined by the protocol or configured by the access network device, without limitation.

[0185] As one possible implementation, the set of binary scaling functions includes the binary scaling function corresponding to each dimension of the j-th level scale space, j = 1, 2, ..., M. Here, the j-th level scale space is a Y-dimensional space, meaning the dimensions of the scale space and the perceptual space are the same. Furthermore, the binary scaling function corresponding to each dimension of the j-th level scale space can also be understood as the j-th level binary scaling function.

[0186] For example, the j-th scale space is determined based on the perceptual space. For instance, the maximum value of the index in the y-th dimension of the j-th scale space is... Where is the size of the perception space in the y-th dimension. This indicates rounding up. Refer to the above explanation of the j-th order wavelet space; it will not be repeated here.

[0187] As one possible implementation, a binary wavelet function in the set of binary wavelet functions corresponds to a binary scaling function in the set of binary scaling functions. This correspondence can be preset or configured by the access network device, and is not limited thereto.

[0188] For example, taking Y = 3, and the Y dimensions of the perception space being distance dimension, horizontal angle dimension, and vertical angle dimension respectively, the binary wavelet function corresponding to the first dimension of the j-th level wavelet space, and the binary scaling function corresponding to the first dimension of the j-th level scale space, are as follows:

[0189] in, It is a basis-binary scaling function. There is a correspondence between it and the basis wavelet function. This is the binary scaling function corresponding to the first dimension of the j-th scale space. The meanings of the other parameters can be found in the relevant explanations above, and will not be repeated here.

[0190] The binary wavelet function corresponding to the second dimension of the j-th level wavelet space, and the binary scaling function corresponding to the second dimension of the j-th level scale space, are:

[0191] in, This is the binary scaling function corresponding to the second dimension of the j-th scale space. The meanings of the other parameters can be found in the relevant explanations above, and will not be repeated here.

[0192] The binary wavelet function corresponding to the third dimension of the j-th level wavelet space, and the binary scaling function corresponding to the third dimension of the j-th level scale space, are:

[0193] in, This is the binary scaling function corresponding to the third dimension of the j-th scale space. The meanings of the other parameters can be found in the relevant explanations above, and will not be repeated here.

[0194] For example, taking Y = 3, and the Y dimensions of the perceptual space being the distance dimension, the horizontal angle dimension, and the vertical angle dimension, the j-th scale space can be represented in the first dimension as {u′ j |j∈[1,M]}, or in other words, the first dimension of the j-th scale space can be represented as {u′ j |j∈[1,M]};The j-th scale space can be represented as {v′} in the second dimension. j|j∈[1,M]}, or in other words, the second dimension of the j-th scale space can be represented as {v′} j |j∈[1,M]};The j-th level scale space can be represented as {w′} in the third dimension. j |j∈[1,M]}, or in other words, the third dimension of the j-th scale space can be represented as {w′ j |j∈[1,M]}. Where:

[0195] Correspondingly, the j-th level three-dimensional scale space can be represented as This represents the Kronecker product. The meaning of each parameter can be found in the relevant explanations above, and will not be repeated here.

[0196] As one possible implementation, the first communication device performs a level j Y-dimensional discrete wavelet transform on the sensed information based on the level j binary scaling function in the set of binary scaling functions and the level j binary wavelet function in the set of binary wavelet functions, to obtain the level j scaling coefficients and level j wavelet coefficients, j = 1, 2, ..., M.

[0197] For example, taking Y = 3, and wavelet space and scale space including the 1st, 2nd, and 3rd dimensions, the j-th level scale coefficient can be expressed as:

[0198] r j ={r j (k,l,i),k∈[0,K j -1],l∈[0,L j -1], i∈[0,I j -1],j∈[1,M]}

[0199] Correspondingly, the M-th level scaling factor can be expressed as:

[0200] r M ={r M (k,l,i),k∈[0,K j -1],l∈[0,L j -1], i∈[0,I j -1]}

[0201] The j-th level wavelet coefficients can be expressed as:

[0202] q j ={q j (k,l,i),k∈[0,K j -1],l∈[0,L j -1], i∈[0,I j -1],j∈[1,M]}

[0203] The explanations of the parameters mentioned above can be found in the relevant descriptions of the corresponding parameters mentioned above, and will not be repeated here.

[0204] For example, taking Y = 3, the perception space including distance dimension, horizontal angle dimension, and vertical angle dimension, and the perception information represented as P(s,m,n), s∈[0,N0O0-1], m∈[0,N1O1-1], n∈[0,N2O2-1], when j=1, the first communication device performs a first-level discrete wavelet transform on the perception information according to the first-level binary wavelet function, which may include:

[0205] First, perform a one-dimensional discrete wavelet transform on the perceptual information P(s,m,n) in the distance dimension (s∈[0,N0O0-1]). Right now:

[0206] in, The first-order binary wavelet function ψj corresponding to the first dimension. 1,k The conjugate function of (s), ψj= 1,k (s) refers to the binary wavelet function ψj corresponding to the first dimension of the first-level wavelet space mentioned above. 1,k (t). After performing a one-dimensional discrete wavelet transform on the distance dimension, the distance dimension is transformed to the first dimension k of the wavelet space.

[0207] Furthermore, regarding Perform a one-dimensional discrete wavelet transform in the horizontal angular dimension (m∈[0,N1O1-1]). Right now:

[0208] in, The first-order binary wavelet function ψ corresponding to the second dimension j＝1,l The conjugate function of (m), ψ j＝1,l (m) is the binary wavelet function ψ corresponding to the second dimension of the first-level wavelet space mentioned above. j＝1,l (t). In the horizontal angular dimension, for After performing a one-dimensional discrete wavelet transform, the horizontal angular dimension is transformed to the second dimension l of the wavelet space.

[0209] Furthermore, regarding Perform a one-dimensional discrete wavelet transform in the vertical angular dimension (n∈[0,N2O2-1]). Right now:

[0210] in, The first-order binary wavelet function ψ corresponding to the third dimension j＝1,i The conjugate function of (n), ψ j＝1,i(n) is the binary wavelet function ψ corresponding to the third dimension of the first-level wavelet space mentioned above. j＝1,i (t). In the vertical angular dimension, for After performing a one-dimensional discrete wavelet transform, the vertical angle dimension is transformed to the third dimension i of the wavelet space. j＝1 (k,l,i) represents the first-order wavelet coefficients.

[0211] Similarly, performing a first-order discrete wavelet transform on the perceived information using a first-order binary scaling function can include: performing a one-dimensional discrete wavelet transform on the perceived information in the distance dimension using the first-order binary scaling function corresponding to the first dimension. right A one-dimensional discrete wavelet transform is obtained by applying the first-order binary scaling function corresponding to the second dimension in the horizontal angular dimension. right The first-order scaling coefficients r are obtained by performing a one-dimensional discrete wavelet transform using the first-order binary scaling function corresponding to the third dimension in the vertical angle dimension. j＝1 (k,l,i).

[0212] Similarly, performing a j-th level discrete wavelet transform on the perceived information using the j-th level binary wavelet function can include: performing a one-dimensional discrete wavelet transform on the perceived information in the distance dimension using the j-th level binary wavelet function corresponding to the first dimension. right A one-dimensional discrete wavelet transform is obtained by using the j-th level binary wavelet function corresponding to the second dimension in the horizontal angle dimension. right The j-th level wavelet coefficient q is obtained by performing a one-dimensional discrete wavelet transform using the j-th level binary wavelet function corresponding to the third dimension in the vertical angle dimension. j (k,l,i). j=2,…,M.

[0213] Similarly, performing a j-th level discrete wavelet transform on the perceived information based on the j-th level binary scaling function can include: performing a one-dimensional discrete wavelet transform on the perceived information in the distance dimension using the j-th level binary scaling function corresponding to the first dimension. right A one-dimensional discrete wavelet transform is obtained by applying the j-th level binary scaling function corresponding to the second dimension in the horizontal angular dimension. right The j-th level scaling coefficient r is obtained by performing a one-dimensional discrete wavelet transform using the j-th level binary scaling function corresponding to the third dimension in the vertical angle dimension. j (k,l,i). j=2,…,M.

[0214] It should be noted that the above is only one example of performing M-level discrete wavelet transform on perceived information. Other methods can also be used to perform M-level discrete wavelet transform on perceived information, and this application does not make any specific limitations on this.

[0215] The process of M-level discrete wavelet transform has been explained above. The following section introduces the M-level scale coefficient codebook and the M wavelet coefficient codebooks included in the perceptual information codebook.

[0216] In one possible implementation, the M-th level scaling coefficient codebook includes P scaling coefficients (values). Y represents the dimensions of the perceptual space and the M-th scale space, P y , M The total number of indices in the y-th dimension of the M-th scale space, which is determined based on the perceptual space, for example... Z y Let be the size of the perceptual space in the y-th dimension, and ∏ denote the product. Refer to the preceding explanation of scale space; it will not be repeated here.

[0217] For example, taking Y = 3, and the M-th scale space including the 1st, 2nd, and 3rd dimensions, when y = 1, the total number of indices P of the 1st dimension of the M-th scale space is... y,M That is, K M When y = 2, the total number of indices P in the second dimension of the M-th scale space. y,M That is, L M When y = 3, the total number of indices P in the third dimension of the M-th scale space. y,M That is, I M For details, please refer to the aforementioned explanations, which will not be repeated here.

[0218] For example, taking Y = 3, and the M-th scale space including the 1st, 2nd, and 3rd dimensions, then the M-th scale coefficient codebook includes K. M ×L M ×I M Each scaling factor (value). For example, each value can be derived from A. r Each bit indicates that the scaling coefficient of level M can be encoded into a format containing A, following the order of distance dimension (or the first dimension), then horizontal angle dimension (or the second dimension), then vertical angle dimension (or the third dimension) (or any other order). r ×K M ×L M ×I M The scale coefficient bitmap is a bit map of 100 bits, also known as the scale coefficient codebook.

[0219] In one possible implementation, the M wavelet coefficient codebooks in the perception information codebook may be implemented in the following two ways:

[0220] Method 1: Wavelet coefficients at each level are reported separately.

[0221] As one possible implementation, the j-th wavelet coefficient codebook in the M wavelet coefficient codebooks includes indication information j and B. j There are wavelet coefficients, j = 1, 2, ..., M. Among them, the indicator information j indicates B. j The indices of the wavelet coefficients in the j-th order wavelet space. The j-th order wavelet space can be found in the aforementioned explanation and will not be repeated here.

[0222] For example, each wavelet coefficient in the j-th wavelet coefficient codebook can be derived from A. q Each bit carries or indicates something. Furthermore, the indication information j may have the following two implementations:

[0223] Method A, Instruction information j includes B j The index of each wavelet coefficient in the j-th order wavelet space.

[0224] For example, taking Y = 3 and the M-level wavelet space including the 1st, 2nd, and 3rd dimensions as an example, for the corresponding index k,l,i in the j-th level wavelet space, k∈[0,K] j -1],l∈[0,L j -1], i∈[0,I j -1],j∈[1,M], can be respectively derived from log2K j log2L j log2 I j Each bit carries or indicates something. Therefore, the indication information j can contain log2K bits. j +log2L j +log2 I j A bitmap of bits.

[0225] For example, based on the implementation of the aforementioned indication information j, the index of the wavelet coefficient in the j-th level wavelet space can be indicated according to the order of k, then l, then i (or other orders). Let the index of a certain wavelet coefficient in the j-th wavelet coefficient codebook corresponding to the j-th level wavelet space be (2,1,3), log2K j log2L j log2 I j If all are 4, then when encoding in the order of 2, 1, 3, the index corresponding to the wavelet coefficient in the j-th level wavelet space can be represented as 0010 0001 0011, or the indication information j can be represented as 0010 0001 0011.

[0226] Based on the above scheme, under mode A, the structure of the perceptual information codebook can be as shown in Figure 8(a). Referring to Figure 8(a), the perceptual information codebook includes the M-th level scale coefficient codebook, the M-th level (number) wavelet coefficient codebook, the (M-1)-th level (number) wavelet coefficient codebook, ..., the 1st level (number) wavelet coefficient codebook.

[0227] Furthermore, each level of wavelet coefficient codebook includes B j A set of wavelet coefficients and their indices. For example, the wavelet coefficient codebook of the j-th level includes the 1st wavelet coefficient and its index, the 2nd wavelet coefficient and its index, the 3rd wavelet coefficient and its index, ..., the B-th wavelet coefficient. j Wavelet coefficients and their indices.

[0228] As one possible implementation, method A can be applied to scenarios where the number of feedback wavelet coefficients is irregular. For example, different wavelet coefficient codebooks may include different numbers of wavelet coefficients. Method A can also be applied to other scenarios. This application does not limit the applicable scenarios of method A, nor does the scenario of irregular feedback wavelet coefficient numbers impose any limitations on the solution of this application.

[0229] Method B, the instruction information j includes a value j, which is related to B. j The index associations of wavelet coefficients in the j-th order wavelet space.

[0230] As one possible implementation, in method B, the number B of wavelet coefficients included in the j-th wavelet coefficient codebook is known. j For example, the first communication device and the second communication device can negotiate B in advance. j Or the protocol can define B j Alternatively, access network devices, sensing and control nodes, or SF network elements can be pre-configured with B. j That is, given all X wavelet coefficients obtained from the j-th level discrete wavelet transform, select B... j Each wavelet coefficient is reported, therefore, the reported B j The wavelet coefficients may exist. There are possible combinations. Here, X is the total number of wavelet coefficients obtained after the j-th level discrete wavelet transform, and X is a positive integer greater than 1. C represents permutation and combination operations.

[0231] For example, taking Y = 3, and the M-level wavelet space including the 1st, 2nd, and 3rd dimensions, then X = K j ×L j ×I j Reported B j The wavelet coefficients may exist. A number of possible combinations.

[0232] Therefore, the indication information j can be carried in the first field, and the size of the first field can be [missing information]. Bits, the first field Each bit value is the numerical value j, and each value in the first field is associated with (or corresponds to) B. j A combination of wavelet coefficients. For example, the values ​​of the first field and their corresponding B... j The combinations of wavelet coefficients are shown in Table 1 below.

[0233] Table 1

[0234] For example, B corresponds to each combination j The wavelet coefficients and the correspondence between the values ​​of the first field and the combination can be pre-negotiated by the first and second communication devices, or pre-configured by the access network equipment, sensing control node, or SF network element, or pre-defined by the protocol, without restriction.

[0235] Based on the above scheme, under mode B, the structure of the perceptual information codebook can be as shown in Figure 8(b). Referring to Figure 8(b), the perceptual information codebook includes the M-th level scale coefficient codebook, the M-th level (number) wavelet coefficient codebook, the (M-1)-th level (number) wavelet coefficient codebook, ..., the 1st level (number) wavelet coefficient codebook.

[0236] Furthermore, each level of wavelet coefficient codebook includes B j The combination of wavelet coefficients and B j Wavelet coefficients. For example, the codebook of the j-th level wavelet coefficients includes B. j The combination of wavelet coefficients indicates the following: 1st wavelet coefficient, 2nd wavelet coefficient, 3rd wavelet coefficient, ..., Bth wavelet coefficient. j Wavelet coefficients.

[0237] As one possible implementation, method B can be applied to scenarios where the number of wavelet coefficients at each level of the feedback is fixed. Of course, method B can also be applied to other scenarios. This application does not limit the applicable scenarios of method B, nor does the scenario where the number of wavelet coefficients at each level of the feedback is fixed impose any limitations on the solution of this application.

[0238] As one possible implementation, in mode one, the j-th wavelet coefficient codebook further includes second indication information, which indicates the number B of wavelet coefficients included in the j-th wavelet coefficient codebook. j .

[0239] Method 2: Correlation and reporting of wavelet coefficients at all levels.

[0240] As one possible implementation, the Mth wavelet coefficient codebook in the M wavelet coefficient codebooks includes the Mth level B... MThe index of each wavelet coefficient and the B M There are M wavelet coefficients. The i-th wavelet coefficient codebook in the M wavelet coefficient codebook includes the wavelet coefficients related to the B... M The index of each wavelet coefficient corresponds to the Bi wavelet coefficients of the i-th level, where i = 1, 2, ..., M-1. Among them, the Bi wavelet coefficients of the M-th level... M The index of each wavelet coefficient is B. M The index of each wavelet coefficient in the M-th level wavelet space. For an explanation of the wavelet space, please refer to the aforementioned description, which will not be repeated here.

[0241] In other words, in this second method, the index of the highest decomposition level and some wavelet coefficients of all decomposition levels are reported. For example, B... M The reporting method for the index of wavelet coefficients can refer to the relevant implementation of the indicator information j in Method 1 above, and the reporting method for wavelet coefficients can refer to the relevant implementation of wavelet coefficients in Method 1 above, which will not be repeated here.

[0242] For example, the first-level wavelet space can be understood as a downsampling of the perceptual space, the second-level wavelet space can be understood as a downsampling of the first-level wavelet space, and so on. Each subsequent level of wavelet space can be understood as a downsampling of the preceding level of wavelet space. Therefore, a certain index in a subsequent level of wavelet space can correspond to multiple corresponding indices in a preceding level of wavelet space. Thus, in method two, the M-th level B can be reported. M The index of wavelet coefficients, B at level i. i The index of each wavelet coefficient is B. M The index of each wavelet coefficient corresponds to the index in the i-th level wavelet space. There is no need to report the indices of wavelet coefficients from level M-1 to level 1, thus further reducing overhead.

[0243] For example, taking a two-dimensional perceptual space as shown in Figure 9(a), assuming the perceptual space has 64 location points, and the first-level wavelet space is downsampled by a factor of 4, then the first-level wavelet space includes 16 indices (or location points). The index (0,0) of the first-level wavelet space corresponds to the indices (0,0), (0,1), (1,0), and (1,1) of the perceptual space. The second-level wavelet space is downsampled by a factor of 4, then the second-level wavelet space includes 4 indices (or location points). The index (0,0) of the second-level wavelet space corresponds to the indices (0,0), (0,1), (1,0), and (1,1) of the first-level wavelet space.

[0244] Furthermore, when the wavelet coefficient value corresponding to a certain index in a later level is high, the wavelet coefficient value at the corresponding index in the previous level is usually also high. Therefore, in the M-th level B... MWhen the wavelet coefficients are relatively high, the wavelet coefficients in all M sensing information codebooks are also relatively high, which is beneficial for recovering the sensing information.

[0245] In one possible implementation, in step S704 above, the second communication device determining the sensing information may include: the second communication device performing an M-level inverse discrete wavelet transform (IDWT) on the sensing information codebook to obtain the sensing information.

[0246] For example, the second communication device can determine a set of binary wavelet functions based on the basis wavelet functions, and then perform an M-level discrete wavelet inverse transform on the sensing information codebook based on the set of binary wavelet functions and the corresponding binary scaling functions to obtain the sensing information. For instance, an M-level discrete wavelet inverse transform is performed on the M wavelet coefficient codebook based on the set of binary wavelet functions, and an M-level discrete wavelet inverse transform is performed on the M-level scale coefficient codebook based on the binary scaling function corresponding to the M-level scale space in the set of binary scaling functions. The basis wavelet functions, the set of binary wavelet functions, and the set of binary scaling functions can be referred to the relevant descriptions in step S702 above, and will not be repeated here.

[0247] It is understood that the basis wavelet functions, binary wavelet function set, and binary scaling function set used by the second communication device are the same as those used by the first communication device in step S702 above. For example, the second communication device can be an access network device, and the second communication device can configure the basis wavelet function set and / or basis wavelet functions to the first communication device. Refer to the relevant description in step S7021 above; it will not be repeated here.

[0248] For example, when the second communication device configures a set of basis wavelet functions to the first communication device, and the first communication device selects a wavelet function from the set as the basis wavelet function, the first communication device can also send information to the second communication device to indicate the basis wavelet function it has selected.

[0249] Furthermore, the second communication device can use the same method as the first communication device to determine the set of binary wavelet functions based on the basis wavelet functions, thereby ensuring that the set of binary wavelet functions and the set of binary scaling functions it determines are the same as those determined by the first communication device. This determination method can be indicated by the second communication device to the first communication device, or by the first communication device to the second communication device, or it can be predefined by the protocol; there are no restrictions.

[0250] For example, taking the perception space as a three-dimensional space including distance dimension, horizontal angle dimension, and vertical angle dimension, and the perception information represented as P(s,m,n), the second communication device performs an M-level discrete wavelet inverse transform on the perception information codebook based on the set of binary wavelet functions and their corresponding set of binary scaling functions, which can be expressed as:

[0251] in, Let q represent the j-th level three-dimensional discrete wavelet inverse transform IDWT. j (k,l,i) represents the wavelet coefficients of the j-th order, r j＝M (k,l,i) represents the scaling factor at level M. This indicates that the discrete wavelet inverse transform is performed on the j-th level wavelet coefficients, and ψ represents the binary wavelet function. This indicates that the discrete wavelet inverse transform is performed on the M-th level scaling coefficients. This represents the binary scaling function.

[0252] For example, the discrete wavelet inverse transform corresponding to the distance dimension can be expressed as:

[0253] Where, ψ j,k (s) is the binary wavelet function corresponding to the first dimension of the j-th level wavelet space. It is the binary scaling function corresponding to the first dimension of the M-th scale space.

[0254] Similarly, the discrete wavelet inverse transform corresponding to the horizontal angular dimension can be expressed as:

[0255] Where, ψ j,l (m) is the binary wavelet function corresponding to the second dimension of the j-th level wavelet space. It is the binary scaling function corresponding to the second dimension of the M-th scale space.

[0256] Similarly, the discrete wavelet inverse transform corresponding to the vertical angular dimension can be expressed as:

[0257] Where, ψ j,i (n) is the binary wavelet function corresponding to the third dimension of the j-th level wavelet space. This is the binary scaling function corresponding to the third dimension of the M-th scale space. Detailed explanations of the above parameters can be found in step S702, and will not be repeated here.

[0258] Based on the above scheme, the second communication device can obtain the sensing information by performing an M-level discrete wavelet inverse transform on the sensing information codebook. Since the sensing information codebook carries the scale coefficient values ​​of the highest decomposition level and some wavelet coefficients of all decomposition levels, for example, it carries wavelet coefficients with larger coefficient values ​​but does not need to carry wavelet coefficients that tend to 0. Therefore, compared with carrying all wavelet coefficients or carrying the original sensing information, it can reduce the feedback overhead and basically does not affect the sensing accuracy.

[0259] For example, as shown in Figure 9(b), the sensing accuracy when feeding back the original sensing information and the sensing information codebook provided in this application is illustrated. The horizontal axis represents the compression ratio, which is the number of bits in the original sensing information divided by the number of bits in the sensing information codebook. For instance, a compression ratio of 1 indicates that the original sensing information is not compressed, and a compression ratio of 2 indicates that the ratio of the number of bits in the original sensing information to the number of bits in the sensing information codebook is 2, meaning the number of bits in the sensing information codebook is half the number of bits in the original sensing information.

[0260] The vertical axis represents perception accuracy; a larger value indicates lower perception accuracy. At a compression ratio of 1, the perception accuracy is 1.17, meaning the accuracy when feeding back the original perception information is 1.17. At compression ratios of 2 and 5, the perception accuracies are 1.13 and 1.15 respectively, with no loss of accuracy compared to feeding back the original perception information. At a compression ratio of 10, the perception accuracy is 1.21, a loss of approximately 3.4% (1.21-1.17) / 1.17 compared to feeding back the original perception information; at a compression ratio of 15, the perception accuracy is 1.33, a loss of approximately 14% (1.33-1.17) / 1.17 compared to feeding back the original perception information. This means that a compression ratio of 10x can be achieved with a perception accuracy loss of less than 5%, resulting in a 10x reduction in feedback overhead. Therefore, the solution provided in this application can reduce feedback overhead with minimal impact on perception accuracy.

[0261] In one possible implementation, for the above method embodiments, in a CU-DU architecture or ORAN system, the function of interaction between the access network device and the terminal can be implemented by the DU or O-DU. The information sent by the access network device to the terminal can be generated by the DU or O-DU, or it can be generated by the CU or O-CU and sent to the DU or O-DU. The function of interaction between the access network device and the core network can be implemented by the CU or O-CU. The processing function of the access network device can be implemented by the CU or O-CU, or by the DU or O-DU, or by a combination of CU and DU (or O-CU and O-DU), without limitation.

[0262] The method provided in this application has been described above. In addition, this application also provides a communication device for implementing the functions described in the above method embodiments.

[0263] It is understood that, in order to achieve the aforementioned functions, the communication device includes hardware structures and / or software modules corresponding to the execution of each function. Those skilled in the art should readily recognize that, based on the units and algorithm steps of the examples 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 executed 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.

[0264] This application embodiment can divide the communication device into functional modules according to the above method embodiment. For example, each function can be divided into a separate functional module, 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.

[0265] Figure 10 shows a schematic diagram of a communication device 100. The communication device 100 includes a processing module 1001 and a transceiver module 1002. The communication device 100 can be used to implement the functions of the first or second communication device described above.

[0266] In some embodiments, the communication device 100 may further include a storage module (not shown in FIG10) for storing program instructions and data.

[0267] In some embodiments, the transceiver module 1002, also referred to as a transceiver unit, is used to implement sending and / or receiving functions. The transceiver module 1002 may consist of a transceiver circuit, a transceiver, a transceiver unit, or a communication interface.

[0268] In some embodiments, the transceiver module 1002 may include a receiving module and a sending module, respectively configured to perform receiving and sending steps performed by the first communication device or the second communication device in the above method embodiments, and / or other processes to support the technology described herein; the processing module 1001 may be configured to perform processing steps performed by the first communication device or the second communication device in the above method embodiments, and / or other processes to support the technology described herein.

[0269] When the communication device 100 is used to perform the functions of the first communication device:

[0270] Processing module 1001 is used to acquire sensing information, which includes sensing data of each location point in the sensing space; processing module 1001 is also used to determine the sensing information codebook, which is obtained by performing an M-level discrete wavelet transform on the sensing information; the sensing information codebook includes an M-level scale coefficient codebook and M wavelet coefficient codebooks, the j-th wavelet coefficient codebook in the M wavelet coefficient codebooks corresponds to the j-level discrete wavelet transform, and the j-th wavelet coefficient codebook includes some wavelet coefficients in the wavelet coefficients obtained after the j-level discrete wavelet transform, j = 1, 2, ..., M, where M is a positive integer greater than or equal to 1; transceiver module 1002 is used to transmit the sensing information codebook.

[0271] Optionally, the processing module 1001 is used to determine the codebook of the perceived information, including: the processing module 1001 is used to determine the set of binary wavelet functions based on the basis wavelet functions; the processing module 1001 is also used to perform M-level discrete wavelet transform on the perceived information based on the set of binary wavelet functions and the set of binary scaling functions corresponding to the set of binary wavelet functions.

[0272] Optionally, the processing module 1001 is used to perform an M-level discrete wavelet transform on the perceived information based on the set of binary wavelet functions and the set of binary scaling functions corresponding to the set of binary wavelet functions. This includes: the processing module 1001 is used to perform a j-level Y-dimensional discrete wavelet transform on the perceived information based on the j-th level binary scaling function in the set of binary scaling functions and the j-th level binary wavelet function in the set of binary wavelet functions, to obtain the j-th level scaling coefficients and the j-th level wavelet coefficients, j = 1, 2, ..., M.

[0273] Optionally, the transceiver module 1002 is further configured to receive third indication information and / or fourth indication information. The third indication information indicates a set of basis wavelet functions, where the basis wavelet functions are wavelet functions within the set; or, the third indication information indicates a basis wavelet function. The fourth indication information indicates the discrete wavelet transform series M.

[0274] When the communication device 100 is used to implement the functions of the second communication device:

[0275] The transceiver module 1002 is used to receive the sensing information codebook, which includes the M-th level scale coefficient codebook and M wavelet coefficient codebooks. The j-th wavelet coefficient codebook in the M wavelet coefficient codebooks corresponds to the j-th level discrete wavelet transform. The j-th wavelet coefficient codebook includes some wavelet coefficients in the wavelet coefficients obtained after the j-th level discrete wavelet transform, j = 1, 2, ..., M, where M is a positive integer greater than or equal to 1. The processing module 1001 is used to determine the sensing information, which is obtained by performing an M-th level discrete wavelet inverse transform on the sensing information codebook. The sensing information includes the sensing data of each location point in the sensing space.

[0276] Optionally, the processing module 1001 is used to determine the perceived information, including: the processing module 1001 is used to determine the set of binary wavelet functions based on the basis wavelet functions; the processing module 1001 is also used to perform M-level discrete wavelet inverse transform on the perceived information codebook based on the set of binary wavelet functions and the set of binary scaling functions corresponding to the set of binary wavelet functions.

[0277] Optionally, the processing module 1001 is used to perform an M-level discrete wavelet transform on the perceived information based on the set of binary wavelet functions and the set of binary scaling functions corresponding to the set of binary wavelet functions. This includes: the processing module 1001 performing an M-level discrete wavelet inverse transform on the M wavelet coefficient codebooks based on the set of binary scaling functions; and the processing module 1001 further performing an M-level discrete wavelet inverse transform on the M-level scale coefficient codebook based on the binary scaling function corresponding to the M-level scale space in the set of binary scaling functions.

[0278] Optionally, the transceiver module 1002 is further configured to send third indication information and / or fourth indication information. The third indication information indicates a set of basis wavelet functions, where the basis wavelet functions are wavelet functions within the set; or, the third indication information indicates a basis wavelet function. The fourth indication information indicates the discrete wavelet transform series M.

[0279] All relevant content of each step involved in the above method embodiments can be referenced from the functional description of the corresponding functional module, and will not be repeated here.

[0280] In this application, the communication device 100 can be presented in an integrated manner by dividing it into various functional modules. Here, "module" can refer to an application-specific integrated circuit (ASIC), a circuit, a processor and memory that executes one or more software or firmware programs, integrated logic circuits, and / or other devices that can provide the above functions.

[0281] In some embodiments, when the communication device 100 in FIG10 is a chip or chip system, the function / implementation process of the transceiver module 1002 can be implemented through the input / output interface (or communication interface) of the chip or chip system, and the function / implementation process of the processing module 1001 can be implemented through the processor (or processing circuit) of the chip or chip system.

[0282] Since the communication device 100 provided in this embodiment can execute the above method, the technical effects it can achieve can be referred to the above method embodiment, and will not be repeated here.

[0283] As a possible product form, the first or second communication device described in the embodiments of this application can be implemented using one or more field programmable gate arrays (FPGAs), programmable logic devices (PLDs), controllers, state machines, gate logic, discrete hardware components, any other suitable circuits, or any combination of circuits capable of performing the various functions described throughout this application.

[0284] As another possible product form, the first or second communication device described in this application embodiment can be implemented using a general bus architecture. For ease of explanation, refer to FIG11, which is a schematic diagram of the structure of a communication device 1100 provided in an embodiment of this application. The communication device 1100 includes a processor 1101 and a transceiver 1102. The communication device 1100 can be a first communication device, or a chip or chip system therein; or, the communication device 1100 can be a second communication device, or a chip or module therein. FIG11 only shows the main components of the communication device 1100. In addition to the processor 1101 and transceiver 1102, the communication device may further include a memory 1103 and input / output devices (not shown in FIG11).

[0285] Optionally, the processor 1101 is mainly used to process communication protocols and communication data, control the entire communication device, execute software programs, and process the data of the software programs, thereby implementing the methods provided in the above-described method embodiments. The memory 1103 is mainly used to store software programs and data. The transceiver 1102 may include a radio frequency (RF) circuit and an antenna. The RF circuit is mainly used for converting baseband signals to RF signals and processing RF signals. The antenna is mainly used for transmitting and receiving RF signals in the form of electromagnetic waves. Input / output devices, such as touch screens, displays, and keyboards, are mainly used to receive user input data and output data to the user.

[0286] Optionally, the processor 1101, transceiver 1102, and memory 1103 can be connected via a communication bus.

[0287] When the communication device is powered on, the processor 1101 can read the software program in the memory 1103, execute the instructions of the software program, and process the data of the software program. When data needs to be transmitted wirelessly, the processor 1101 performs baseband processing on the data to be transmitted and outputs the baseband signal to the radio frequency (RF) circuit. The RF circuit processes the baseband signal and transmits the RF signal outward in the form of electromagnetic waves through the antenna. When data is sent to the communication device, the RF circuit receives the RF signal through the antenna, converts the RF signal into a baseband signal, and outputs the baseband signal to the processor 1101. The processor 1101 converts the baseband signal into data and processes the data.

[0288] In another implementation, the radio frequency circuitry and antenna can be set up independently of the processor performing baseband processing. For example, in a distributed scenario, the radio frequency circuitry and antenna can be arranged remotely, independent of the communication device.

[0289] In some embodiments, those skilled in the art will recognize that the above-described communication device 100 can take the form of the communication device 1100 shown in FIG11 in terms of hardware implementation.

[0290] As an example, the function / implementation process of the processing module 1001 in Figure 10 can be implemented by the processor 1101 in the communication device 1100 shown in Figure 11 calling computer execution instructions stored in the memory 1103. The function / implementation process of the transceiver module 1002 in Figure 10 can be implemented by the transceiver 1102 in the communication device 1100 shown in Figure 11.

[0291] As another possible product form, the first or second communication device in this application may adopt the composition structure shown in FIG12, or include the components shown in FIG12. FIG12 is a schematic diagram of the composition of a communication device 1200 provided in this application. The communication device 1200 may be the first communication device or a chip or system-on-a-chip in the first communication device; or, it may be the second communication device or a chip or system-on-a-chip in the second communication device.

[0292] As shown in FIG12, the communication device 1200 includes at least one processor 1201 and at least one communication interface (FIG12 is merely an example illustrating the inclusion of a communication interface 1204 and a processor 1201). Optionally, the communication device 1200 may further include at least one of a communication bus 1202, a memory 1203, and a computer-readable storage medium 1207.

[0293] Processor 1201 may be a general-purpose central processing unit (CPU), a general-purpose processor, a network processor (NP), a digital signal processor (DSP), a microprocessor (e.g., x86, ARM), a microcontroller, an FPGA, a PLD, a state machine, gated logic, discrete hardware circuitry, other suitable hardware configured to perform various functions, or any combination thereof. Processor 1201 may also be other devices with processing capabilities, such as circuits, devices, or software modules, without limitation.

[0294] The communication bus 1202 is used to connect different components in the communication device 1200, enabling communication between them. The communication bus 1202 can be a Peripheral Component Interconnect (PCI) bus or an Extended Industry Standard Architecture (EISA) bus, etc. This bus can be divided into address bus, data bus, control bus, etc. For ease of illustration, only one thick line is used in Figure 12, but this does not mean there is only one bus or one type of bus. For example, the communication bus 1202 can include any number of interconnect buses and bridges, depending on the specific application and overall design constraints of the communication device. Furthermore, the communication bus 1202 can also link various other circuits, such as timing sources, peripherals, voltage regulators, and power management circuits.

[0295] Communication interface 1204 is used for communicating with other devices or communication networks. For example, communication interface 1204 can be a module, circuit, or any device capable of enabling communication.

[0296] As one possible implementation, the communication interface 1204 can also be an input / output interface located within the processor 1201, used to implement signal input and signal output of the processor.

[0297] As another possible implementation, communication interface 1204 can also be understood as a bus interface. It provides an interface between the communication bus and the transceiver. The transceiver can provide an interface or device for communicating with various other devices via wireless / wired transmission media. The transceiver can be coupled to an antenna array, and the transceiver and antenna array can be used together for communication with the appropriate type of network.

[0298] The memory 1203 can be a device with storage function for storing instructions and / or data. The instructions can be computer programs. For example, the memory 1203 can be a read-only memory (ROM) or other type of static storage device capable of storing static information and / or instructions; it can also be a random access memory (RAM) or other type of dynamic storage device capable of storing information and / or instructions; it can also be an electrically erasable programmable read-only memory (EEPROM), a compact disc read-only memory (CD-ROM) or other optical disc storage, optical disc storage (including compressed optical discs, laser discs, optical discs, universal optical discs, Blu-ray discs, etc.), magnetic disk storage media, or other magnetic storage devices, etc., without limitation.

[0299] It should be noted that the memory 1203 can exist independently of the processor 1201, or it can be integrated with the processor 1201. The memory 1203 can be located inside or outside the communication device 1200, without limitation.

[0300] The processor 1201 can be used to execute instructions stored in the memory 1203, or to execute computer programs or instructions stored in the computer-readable storage medium 1207, to implement the methods provided in the above embodiments of this application.

[0301] For example, the processor 1201 may also implement at least one of the following functions, or the processor 1201 executes instructions or computer programs stored in the memory 1203 or computer-readable storage medium 1207 to implement at least one of the following functions: encoding, decoding, rate matching, rate matching de-scrambling, scrambling, modulation, demodulation, layer mapping, fast fourier transform (FFT), inverse fast fourier transform (IFFT), inverse discrete fourier transform (IDFT), precoding, resource element (RE) mapping, channel equalization, RE de-mapping, digital beamforming (BF), adding cyclic prefix (CP), removing CP, etc.

[0302] Optionally, the processor 1201 and / or memory 1203 may include an artificial intelligence (AI) module, which is used to implement AI-related functions. The AI ​​module can be implemented through software, hardware, or a combination of both. For example, the AI ​​module may include a radio network intelligent controller (RIC) module. For example, the AI ​​module can be a near real-time RIC or a non-real-time RIC.

[0303] As an optional implementation, the communication device 1200 may also include an output device 1205 and an input device 1206 (neither shown in Figure 12). The output device 1205 communicates with the processor 1201 and can display information in various ways. For example, the output device 1205 may be a liquid crystal display (LCD), a light-emitting diode (LED) display device, a cathode ray tube (CRT) display device, or a projector, etc. The input device 1206 communicates with the processor 1201 and can receive user input in various ways. For example, the input device 1206 may be a mouse, keyboard, touchscreen device, or sensing device, etc.

[0304] In some embodiments, those skilled in the art will recognize that the communication device 100 shown in FIG10 can take the form of the communication device 1200 shown in FIG12 in terms of hardware implementation.

[0305] As an example, the function / implementation process of the processing module 1001 in Figure 10 can be implemented by the processor 1201 in the communication device 1200 shown in Figure 12 calling computer execution instructions stored in the memory 1203. The function / implementation process of the transceiver module 1002 in Figure 10 can be implemented by the communication interface 1204 in the communication device 1200 shown in Figure 12.

[0306] It should be noted that the structure shown in Figure 12 does not constitute a specific limitation on the first or second communication device. For example, in other embodiments of this application, the first or second communication device may include more or fewer components than shown in the figure, or combine some components, or split some components, or have different component arrangements. The components shown in the figure may be implemented in hardware, software, or a combination of software and hardware.

[0307] In one possible implementation, the processor in this application embodiment may include communication and processing circuitry. The communication and processing circuitry may include one or more hardware components that provide a physical structure that performs various processes related to wireless communication or sensing (such as signal reception and / or signal transmission). The communication and processing circuitry may include two or more transmit / receive chains. The functions implemented by the communication and processing circuitry may also be processed on a computer-readable medium.

[0308] In another possible implementation, as shown in Figure 13, the processor may include: a sensing information processing module (or circuit), an encoding circuit, and a mapping circuit. The sensing information processing module can be used to perform an M-level discrete wavelet transform on the sensing information to obtain M-level scaling coefficients and M-level wavelet coefficients. The encoding circuit can be used to encode the M-level scaling coefficients and M-level wavelet coefficients. For example, the encoding circuit may include encoder 1 and encoder 2. Encoder 1 is used to encode the M-level scaling coefficients (e.g., using Polar code encoding) to generate an M-level scaling coefficient codebook, and encoder 2 is used to encode the M-level wavelet coefficients (e.g., using Polar code encoding) to generate M wavelet coefficient codebooks. The mapping circuit is used to map the sensing information codebook onto transmission resources, such as mapping to REs in uplink transmission resources carrying the uplink channel, such as time slots or subframes, using mapping / multiplexing techniques in PUSCH. Furthermore, the sensing information codebook can be encapsulated or carried in a transport block (TB).

[0309] For example, the functions of the aforementioned sensing information processing module, encoding circuit, and mapping circuit can also be processed on a computer-readable medium. Furthermore, the sensing information processing module, encoding circuit, and mapping circuit may have other names, and this application does not specifically limit them.

[0310] In some embodiments, this application also provides a communication device, which includes a processor for implementing the methods in any of the above method embodiments.

[0311] As one possible implementation, the communication device also includes a memory. This memory stores necessary computer programs and data. The computer program may include instructions, which a processor can invoke to instruct the communication device to execute the methods described in any of the above method embodiments. Alternatively, the memory may not be present in the communication device.

[0312] As another possible implementation, the communication device also includes an interface circuit, which is a code / data read / write interface circuit, used to receive computer execution instructions (which are stored in memory and may be read directly from memory or may be transmitted through other devices) and transmit them to the processor.

[0313] As another possible implementation, the communication device also includes a communication interface for communicating with modules outside the communication device.

[0314] It is understood that the communication device can be a chip or a chip system. When the communication device is a chip system, it can be composed of chips or may include chips and other discrete devices. This application does not specifically limit this.

[0315] This application also provides a computer-readable storage medium having a computer program or instructions stored thereon, which, when executed by a computer, implements the functions of any of the above-described method embodiments.

[0316] This application also provides a computer program product that, when executed by a computer, implements the functions of any of the above method embodiments.

[0317] 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.

[0318] It is understood that the systems, apparatuses, and methods described in this application can also 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 couplings or direct couplings or communication connections shown or discussed may be through some interfaces; indirect couplings or communication connections between devices or units may be electrical, mechanical, or other forms.

[0319] The units described as separate components may or may not be physically separate; that is, they may be located in one place or distributed across multiple network units. The components shown as units may or may not be physical units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0320] 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.

[0321] In the above embodiments, implementation can be achieved, in whole or in part, through software, hardware, firmware, or any combination thereof. When implemented using software programs, implementation can be, in whole or in part, in the form of a computer program product. This computer program product includes one or more computer instructions. When the computer program instructions are loaded and executed on a computer, all or part of the processes or functions described in the embodiments of this application are generated. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. The computer instructions can be stored in a computer-readable storage medium or transmitted from one computer-readable storage medium to another. For example, the computer instructions can be transmitted from one website, computer, server, or data center to another via wired (e.g., coaxial cable, fiber optic, digital subscriber line (DSL)) or wireless (e.g., infrared, wireless, microwave, etc.) means. The computer-readable storage medium can be any available medium accessible to a computer or a data storage device containing one or more servers, data centers, etc., that can be integrated with the medium. The available medium can be a magnetic medium (e.g., floppy disk, hard disk, magnetic tape), an optical medium (e.g., DVD), or a semiconductor medium (e.g., solid-state drive (SSD)). In this embodiment, the computer may include the aforementioned apparatus.

[0322] Although this application has been described herein in conjunction with various embodiments, those skilled in the art, by reviewing the accompanying drawings, disclosure, and appended claims, will understand and implement other variations of the disclosed embodiments in carrying out the claimed application. In the claims, the word "comprising" does not exclude other components or steps, and "a" or "an" does not exclude a plurality. A single processor or other unit can implement several functions listed in the claims. While different dependent claims may recite certain measures, this does not mean that these measures cannot be combined to produce good results.

[0323] Although this application has been described in conjunction with specific features and embodiments, it is obvious that various modifications and combinations can be made thereto without departing from the scope of this application. Accordingly, this specification and drawings are merely illustrative descriptions of the application as defined by the appended claims, and are considered to cover any and all modifications, variations, combinations, or equivalents within the scope of this application. Clearly, those skilled in the art can make various alterations and modifications to this application without departing from its scope. Thus, if such modifications and modifications fall within the scope of the claims and their equivalents, this application is also intended to include such modifications and modifications.

Claims

1. A communication method characterized by comprising: The method comprises: obtaining perception information, the perception information comprising perception data of each position point in a perception space; determining a perception information codebook, the perception information codebook being obtained by performing M-level discrete wavelet transform on the perception information; the perception information codebook comprising an Mth-level scale coefficient codebook and M wavelet coefficient codebooks, a jth wavelet coefficient codebook in the M wavelet coefficient codebooks corresponding to jth-level discrete wavelet transform, the jth wavelet coefficient codebook comprising part of wavelet coefficients obtained after the jth-level discrete wavelet transform, j=1, 2, …, M, M being a positive integer greater than or equal to 1; sending the perception information codebook.

2. The method of claim 1, wherein, The jth wavelet coefficient codebook comprises wavelet coefficients greater than or equal to a first threshold value in the wavelet coefficients obtained after the jth-level discrete wavelet transform.

3. The method of claim 1 or 2, wherein: The jth wavelet coefficient codebook comprises indication information j and B j wavelet coefficients; wherein the indication information j indicates an index corresponding to the B j wavelet coefficients in a jth level wavelet space, and the jth level wavelet space is determined according to the perception space.

4. The method of claim 3, wherein, The indication information j includes the B j The indices of the wavelet coefficients in the j-th order wavelet space; or... The indication information j includes a value j, which is associated with the index corresponding to the jth level wavelet coefficient in the B j wavelet space.

5. The method of claim 4, wherein, The jth wavelet coefficient codebook further comprises second indication information, the second indication information indicating a number B of wavelet coefficients included in the jth wavelet coefficient codebook j .

6. The method according to claim 4 or 5, characterized in that, In the case that the indication information j includes a numerical value j, the indication information j is carried in a first field, and the size of the first field is bits, C represents a permutation and combination operation, X is the total number of wavelet coefficients obtained after the jth level of discrete wavelet transform, and X is a positive integer greater than 1.

7. The method of claim 1, wherein, The Mth wavelet coefficient codebook of the M wavelet coefficient codebooks comprises an index of Mth level B M wavelet coefficients, the B M wavelet coefficients. The i-th wavelet coefficient codebook in the M wavelet coefficient codebooks comprises the i-th level B M wavelet coefficients corresponding to the index of the B i wavelet coefficients, i = 1, 2, …, M-1. wherein the B M index of the B M th wavelet coefficient in the Mth level wavelet space, the Mth level wavelet space being determined according to the perceptual space.

8. The method according to any one of claims 3-7, characterized in that, the perception space and the jth-level wavelet space are Y-dimensional spaces, j=1, 2, …, M, Y being a positive integer greater than 1; The maximum value of the index in the yth dimension of the jth level wavelet space is y = 1, 2,..., Y, Z y for the size of the perception space in the y-th dimension, represents rounding up.

9. The method according to any one of claims 1 to 8, characterized in that, The Mth-level scale factor codebook includes P scale factors; wherein: wherein Y is the dimension of the perceptual space and the Mth level scale space, P y,M is the total number of indexes of the yth dimension of the Mth level scale space, the Mth level scale space is determined according to the perceptual space, and ∏ represents a continuous multiplication.

10. The method of claim 9, wherein, wherein Z y is the size of the perception space in the yth dimension, represents rounding up.

11. The method according to any one of claims 1 to 10, characterized in that, determining the perception information codebook comprises: determining a dyadic wavelet function set according to a base wavelet function; performing M-level discrete wavelet transform on the perception information according to the dyadic wavelet function set and a dyadic scale function set corresponding to the dyadic wavelet function set.

12. The method of claim 11, wherein, performing M-level discrete wavelet transform on the perception information according to the dyadic wavelet function set and a dyadic scale function set corresponding to the dyadic wavelet function set comprises: performing jth-level Y-dimensional discrete wavelet transform on the perception information according to a jth dyadic scale function in the dyadic scale function set and a jth dyadic wavelet function in the dyadic wavelet function set, to obtain jth-level scale coefficients and jth-level wavelet coefficients, j=1, 2, …, M.

13. The method according to claim 11 or 12, characterized in that, The method further comprises: receiving third indication information and / or fourth indication information; wherein the third indication information indicates a base wavelet function set, the base wavelet function being a wavelet function in the base wavelet function set; or the third indication information indicates the base wavelet function; the fourth indication information indicates the number M of discrete wavelet transform levels.

14. A communication method, comprising: The method comprises: receiving a perception information codebook, the perception information codebook comprising an Mth-level scale coefficient codebook and M wavelet coefficient codebooks, a jth wavelet coefficient codebook in the M wavelet coefficient codebooks corresponding to jth-level discrete wavelet transform, the jth wavelet coefficient codebook comprising part of wavelet coefficients obtained after the jth-level discrete wavelet transform, j=1, 2, …, M, M being a positive integer greater than or equal to 1; determining perception information, the perception information being obtained by performing M-level inverse discrete wavelet transform on the perception information codebook, the perception information comprising perception data of each position point in a perception space.

15. The method of claim 14, wherein, The jth wavelet coefficient codebook comprises wavelet coefficients greater than or equal to a first threshold value in the wavelet coefficients obtained after the jth-level discrete wavelet transform.

16. The method of claim 14 or 15, wherein: The jth wavelet coefficient codebook comprises indication information j and B j wavelet coefficients; wherein the indication information j indicates an index corresponding to the B j wavelet coefficients in a jth level wavelet space, and the jth level wavelet space is determined according to the perception space.

17. The method of claim 16, wherein, The indication information j includes the B j The indices of the wavelet coefficients in the j-th order wavelet space; or... The indication information j includes a value j, the value j is associated with the B j wavelet coefficient corresponding index in the jth level wavelet space.

18. The method of claim 17, wherein, The jth wavelet coefficient codebook further comprises second indication information, the second indication information indicating a number B of wavelet coefficients included in the jth wavelet coefficient codebook j .

19. The method of claim 17 or 18, wherein, In the case that the indication information j includes a numerical value j, the indication information j is carried in a first field, and the size of the first field is bits, C represents a permutation and combination operation, X is the total number of wavelet coefficients obtained after the jth level of discrete wavelet transform, and X is a positive integer greater than 1.

20. The method of claim 14, wherein, The Mth wavelet coefficient codebook of the M wavelet coefficient codebooks comprises B M indices of Mth level wavelet coefficients, the B M wavelet coefficients. The i-th wavelet coefficient codebook in the M wavelet coefficient codebooks comprises the i-th level B M wavelet coefficients corresponding to the index of the B i wavelet coefficients, i = 1, 2, …, M-1. wherein the B M index of the B M index of the B wavelet coefficient in the Mth level wavelet space determined according to the perceptual space.

21. The method according to any one of claims 17-20, characterized by, the perception space and the jth-level wavelet space are Y-dimensional spaces, j=1, 2, …, M, Y being a positive integer greater than 1; The maximum value of the index in the yth dimension of the jth level wavelet space is y = 1, 2,..., Y, Z y for the size of the perception space in the y-th dimension, represents upward rounding.

22. The method according to any one of claims 14-21, characterized by, The Mth-level scale factor codebook includes P scale factors; wherein: wherein Y is the dimension of the perceptual space and the Mth level scale space, P y,M is the total number of indexes of the yth dimension of the Mth level scale space, the Mth level scale space is determined according to the perceptual space, and ∏ represents a continuous multiplication.

23. The method of claim 22, wherein, wherein Z y is the size of the perception space in the yth dimension, represents upward rounding.

24. The method according to any one of claims 14-23, characterized by, determining perceptual information, comprising: determining a set of dyadic wavelet functions according to a set of base wavelet functions; performing M-level inverse discrete wavelet transform on the perceptual information codebook according to the set of dyadic wavelet functions and a set of dyadic scaling functions corresponding to the set of dyadic wavelet functions.

25. The method of claim 24, wherein, performing M-level discrete wavelet transform on the perceptual information according to the set of dyadic wavelet functions and a set of dyadic scaling functions corresponding to the set of dyadic wavelet functions, comprising: performing M-level inverse discrete wavelet transform on the M wavelet coefficient codebooks according to the set of dyadic scaling functions; performing M-level inverse discrete wavelet transform on the Mth-level scaling coefficient codebook according to the dyadic scaling function corresponding to the Mth-level scaling space in the set of dyadic scaling functions.

26. The method of claim 24 or 25, wherein, The method further comprises: sending third indication information and / or fourth indication information; wherein the third indication information indicates a set of base wavelet functions, the base wavelet function being a wavelet function in the set of base wavelet functions; or the third indication information indicates the base wavelet function; the fourth indication information indicates the number M of discrete wavelet transform levels.

27. A communications device, characterized by The communication device comprises a processor; the processor is configured to run a computer program or instructions, so that the communication device performs the method of any one of claims 1-13, or so that the communication device performs the method of any one of claims 14-26.

28. A computer-readable storage medium, characterized in that, The computer readable storage medium stores computer instructions or programs, when the computer instructions or programs are run on a computer, so that the method of any one of claims 1-13 is performed, or so that the method of any one of claims 14-26 is performed.

29. A computer program product, characterised in that, The computer program product comprises computer instructions; when part or all of the computer instructions are run on a computer, so that the method of any one of claims 1-13 is performed, or so that the method of any one of claims 14-26 is performed.

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