Information transmission methods, device, storage medium and program product

Abstract

Provided in the embodiments of the present disclosure are information transmission methods, a device, a storage medium and a program product. An information transmission method comprises: sending sensing measurement information to a sensing network element, the sensing measurement information comprising a quantized sensing measurement parameter, and the quantized sensing measurement parameter being obtained by performing quantization on the basis of a first quantization range configured by the sensing network element.

Description

Information transmission method, device, storage medium and program product

[0001] This application claims priority to Chinese Patent Application No. 202411301804.5, filed on September 14, 2024, the entire contents of which are incorporated herein by reference. TECHNICAL FIELD

[0002] The present disclosure relates to the technical field of communication, and in particular, to an information transmission method, device, storage medium and program product. BACKGROUND

[0003] With the continuous development of communication technology, a communication network can implement a sensing function. In addition to implementing the sensing function, the communication network can also implement measurement reporting, so as to perform various operations such as network optimization. SUMMARY

[0004] In one aspect, an information transmission method is provided. The information transmission method includes sending, to a sensing network element, sensing measurement information. The sensing measurement information includes a quantized sensing measurement parameter. The quantized sensing measurement parameter is obtained by quantizing based on a first quantization range configured by the sensing network element.

[0005] In another aspect, an information transmission method is provided. The information transmission method includes receiving sensing measurement information sent by a wireless node. The sensing measurement information includes a quantized sensing measurement parameter. The quantized sensing measurement parameter is obtained by quantizing based on a first quantization range configured by the sensing network element.

[0006] In yet another aspect, an information transmission apparatus is provided. The information transmission apparatus includes a sending unit. The sending unit is configured to send, to a sensing network element, sensing measurement information. The sensing measurement information includes a quantized sensing measurement parameter. The quantized sensing measurement parameter is obtained by quantizing based on a first quantization range configured by the sensing network element.

[0007] In yet another aspect, an information transmission apparatus is provided. The information transmission apparatus includes a receiving unit. The receiving unit is configured to receive sensing measurement information sent by a wireless node. The sensing measurement information includes a quantized sensing measurement parameter. The quantized sensing measurement parameter is obtained by quantizing based on a first quantization range configured by the sensing network element.

[0008] In yet another aspect, an electronic device is provided. The electronic device includes a memory and a processor. The memory is coupled to the processor. The memory is configured to store a computer program. The processor is configured to implement the information transmission method described above when executing the computer program.

[0009] In another aspect, a computer-readable storage medium is provided, and the computer-readable storage medium has stored thereon computer program instructions. The computer program instructions are executed by a processor to implement the information transmission method.

[0010] In another aspect, a computer program product is provided, and the computer program product includes computer program instructions. The computer program instructions are executed by a processor to implement the information transmission method. BRIEF DESCRIPTION OF DRAWINGS

[0011] In order to more clearly illustrate the technical solutions in the present disclosure, the following will briefly introduce the drawings needed to be used in some embodiments of the present disclosure. Obviously, the drawings described in the following are only some of the drawings of the present disclosure, and other drawings can also be obtained by those skilled in the art according to these drawings.

[0012] FIG. 1 is a communication system architecture diagram according to some embodiments of the present disclosure.

[0013] FIG. 2 is a flow diagram of an information transmission method according to some embodiments of the present disclosure.

[0014] FIG. 3 is a schematic diagram of a perception process according to some embodiments of the present disclosure.

[0015] FIG. 4A is a schematic diagram of a perception area range according to some embodiments of the present disclosure.

[0016] FIG. 4B is another schematic diagram of a perception area range according to some embodiments of the present disclosure.

[0017] FIG. 5 is another schematic diagram of a perception area range according to some embodiments of the present disclosure.

[0018] FIG. 6 is another schematic diagram of a perception area range according to some embodiments of the present disclosure.

[0019] FIG. 7 is another schematic diagram of a perception area range according to some embodiments of the present disclosure.

[0020] FIG. 8 is a flow diagram of another information transmission method according to some embodiments of the present disclosure.

[0021] FIG. 9 is a structural schematic diagram of a communication apparatus according to some embodiments of the present disclosure.

[0022] FIG. 10 is a structural schematic diagram of another communication apparatus according to some embodiments of the present disclosure.

[0023] FIG. 11 is a structural schematic diagram of another communication apparatus according to some embodiments of the present disclosure. DETAILED DESCRIPTION

[0024] The technical solutions in the present disclosure will be described clearly and completely in combination with the drawings in the present disclosure. Obviously, the described embodiments are only part of the embodiments of the present disclosure, rather than all the embodiments. Based on the embodiments in the present disclosure, all other embodiments obtained by those skilled in the art without creative work belong to the protection scope of the present disclosure.

[0025] It should be noted that in the present disclosure, the words such as "exemplary" or "for example" are used to describe examples, illustrations, or descriptions. Any embodiment or design scheme described in the present disclosure by the words such as "exemplary" or "for example" should not be interpreted as more preferred or more advantageous than other embodiments or design schemes. Rather, the words such as "exemplary" or "for example" are intended to present the relevant concept in a specific manner.

[0026] Hereinafter, the terms "first", "second", and the like are used only for descriptive purposes, and should not be construed as indicating or implying relative importance or implicitly indicating the number of the indicated technical features. Therefore, the features defined by the terms "first", "second", and the like can be explicitly or implicitly included one or more of the features.

[0027] In the description of the present disclosure, unless otherwise specified, " / " means "or", for example, A / B can mean A or B. "And / or" in this document is only used to describe the association relationship of the associated objects, which means that there can be three kinds of relationships, for example, A and / or B can mean: only A, only B, and A and B. In addition, "at least one" means one or more, and "multiple" means two or more.

[0028] With the continuous development of communication technology, the communication network can realize the function of perception. The perception process is similar to the positioning process. The perception process can include capability reporting, measurement configuration, and measurement reporting. In the measurement reporting, the traditional method is to quantize and report the measurement result based on the value range. However, this method has the problem of large perception overhead. In addition, in the measurement reporting, both the measurement value of the related parameter and the final measurement result can be reported. For example, the value range of the relative slot timing difference (RSTD) is -985024Tc to 985024Tc. For another example, the value range of the point coordinates is -90 to 90 degrees in latitude and -180 to 180 degrees in longitude. The granularity of the reported value is adjustable, and different k values can be selected to obtain the granularity 2 k . For example, the point coordinates can be reported by 24 bits or 32 bits.

[0029] To this end, the information transmission method provided in the embodiments of the present disclosure includes: a sensing function entity can receive sensing measurement information. The sensing measurement information includes a quantized sensing measurement parameter. Since the sensing measurement parameter belongs to a first quantization range, the sensing measurement parameter can be quantized based on the first quantization range. Compared with the quantization based on the maximum quantization range in the conventional method, the communication overhead of the quantized sensing measurement parameter based on the first quantization range is smaller, thereby reducing the overhead of measurement reporting.

[0030] The information transmission method provided in the embodiments of the present disclosure can be applied to systems of various communication modes. For example, the information transmission method provided in the embodiments of the present disclosure can be applied to systems including but not limited to: a long term evolution (LTE) system, various versions based on LTE evolution, a 5th generation mobile communication technology (5G) system, a future mobile communication network (for example, a 6G mobile communication network), or a multi-communication convergence system, and the like. In addition, the information transmission method provided in the embodiments of the present disclosure can also be applied to future-oriented communication systems and the like.

[0031] Exemplarily, the information transmission method described above can be applied to a communication system as shown in FIG. 1. As shown in FIG. 1, the communication system includes: a sensing function entity 101 and a wireless node 102.

[0032] The sensing function entity (SF) 101 and the wireless node 102 are in communication connection. The sensing function entity 101 can be a core network entity, a base station, or other network entities. The sensing function entity 101 can also be a terminal, an Internet of Things device, a base station, or other nodes with sensing capability.

[0033] In the embodiments of the present disclosure, the sensing function entity 101 can receive sensing measurement information sent by the wireless node 102. The sensing measurement information is used to indicate a quantized sensing measurement parameter, and the sensing measurement parameter belongs to a first quantization range. Compared with the conventional quantization based on the maximum quantization range, the communication overhead of the quantized sensing measurement parameter based on the first quantization range is smaller when reporting, thereby reducing the communication overhead of measurement reporting.

[0034] In some embodiments, the terminal can be a device with wireless transceiver function, which can be deployed on land (including indoor or outdoor, handheld, wearable or vehicle-mounted); can also be deployed on the water surface (such as ships, etc.); can also be deployed in the air (such as airplanes, balloons and satellites, etc.). The terminal can be a mobile phone, a tablet computer (Pad), a computer with wireless transceiver function, a virtual reality (VR) terminal, an augmented reality (AR) terminal, a wireless terminal in industrial control, a wireless terminal in self driving, a wireless terminal in remote medical, a wireless terminal in smart grid, a wireless terminal in transportation safety, a wireless terminal in smart city, a wireless terminal in smart home, etc. The embodiments of the present application do not limit the application scenarios. The terminal can also be called a user, a user equipment (UE), an access terminal, a UE unit, a UE station, a mobile station, a mobile station, a remote station, a remote terminal, a mobile device, a UE terminal, a wireless communication device, a UE agent or a UE apparatus, etc. The embodiments of the present application do not limit this.

[0035] In some embodiments, the base station can be a base station or an evolved base station (eNB or eNodeB) in long term evolution (LTE) or long term evolution advanced (LTEA), a base station device in a 5G network, or a base station in a future communication system, etc. The base station can include various macro base stations, micro base stations, home base stations, wireless remote devices, reconfigurable intelligent surfaces (RISs), routers, wireless fidelity (WIFI) devices, or various network side devices such as primary cells and secondary cells, etc.

[0036] It should be noted that FIG. 1 is only an exemplary framework diagram, the number of devices included in FIG. 1, the name of each device is not limited, and in addition to the devices shown in FIG. 1, the communication system can also include other devices, such as relay nodes, etc.

[0037] The application scenarios of the embodiments of the present disclosure are not limited. The system architecture and business scenarios described in the embodiments of the present disclosure are used to more clearly illustrate the technical solutions of the embodiments of the present disclosure, and do not constitute a limitation on the technical solutions provided by the embodiments of the present disclosure. It can be known by those skilled in the art that, with the evolution of network architecture and the appearance of new business scenarios, the technical solutions provided by the embodiments of the present disclosure are also applicable to similar technical problems.

[0038] The information transmission method provided by the embodiments of the present disclosure will be described in detail below with reference to the accompanying drawings.

[0039] The information transmission method provided by the embodiments of the present disclosure can be applied to the sensing network element 101 in the communication system shown in FIG. 1. FIG. 2 shows a flowchart of an information transmission method. As shown in FIG. 2, the information transmission method includes the following S201.

[0040] In S201, the wireless node transmits sensing measurement information.

[0041] The sensing measurement information includes quantized sensing measurement parameters. The quantized sensing measurement parameters are obtained by quantizing based on a first quantization range configured by the sensing network element. The first quantization range is smaller than a maximum quantization range corresponding to the sensing measurement parameters.

[0042] In the conventional method, since the quantized reporting of the sensing measurement parameters is based on the maximum quantization range, the reporting overhead is large. In this case, the quantization range of the sensing measurement parameters can be reduced, so that the number of bits required when the sensing measurement parameters are quantized is reduced, and the communication overhead when the quantized sensing measurement parameters are transmitted is smaller.

[0043] In addition, although the number of bits required for quantization is reduced, the number of quantization values corresponding to the quantization is also reduced, but since the value range corresponding to the perception measurement parameter is also reduced, that is, the range of the parameter value of the perception measurement parameter represented by the quantization value is also reduced, the quantization accuracy can be maintained during quantization, so that the value of the perception measurement parameter is represented by fewer bits, and the reporting overhead can be reduced while maintaining the reporting accuracy. Especially for wireless perception, since the target of interest of the perception service has certain speed, position, perception target relative channel state (RCS), etc. Characteristics, the value range of the related perception measurement parameter can be flexibly limited according to the service demand, thereby reducing the overhead required for quantization at the same quantization accuracy. It should be understood that the perception measurement information can include a plurality of perception measurement parameters, and part of the perception measurement parameters are quantized based on the first quantization range. In some embodiments, the wireless node can quantize based on the first quantization range configured by the perception network element, the quantization granularity of the perception measurement parameter, and the quantization bit number of the perception measurement parameter to obtain the quantized perception measurement parameter.

[0044] It should be noted that the reporting of the perception measurement information can be divided into active reporting of the wireless node and reporting in response to the perception measurement request of the perception network element. In the active reporting mode of the wireless node, the wireless node can report after meeting the corresponding threshold. The threshold can be determined based on the lower limit of the value range of the perception measurement parameter in the perception configuration information.

[0045] In an implementation manner, the perception measurement parameter includes original measurement data or data obtained by processing the original measurement data. That is, the perception measurement parameter can be original measurement data, or a parameter obtained by processing the original measurement data based on at least one processing process.

[0046] The original measurement data is also called perception original data, received signal or original channel information. For example, when the perception measurement parameter is original time domain channel information, the range and granularity of the time domain coordinates can be determined according to the perception configuration information (or measurement configuration), which also has the benefit of little reporting overhead. The measurement and reporting of the perception measurement information can be divided into active perception measurement and reporting of the wireless node, and the perception network element requesting the wireless node to perform perception measurement and reporting. In the active reporting mode of the wireless node, the wireless node reports when meeting the configured threshold. The threshold can be determined by the lower limit of the perception range in the perception configuration information.

[0047] The parameter obtained by processing based on at least one processing process can include the following preliminary measurement data, signal measurement data, and perception final result.

[0048] The preliminary measurement data, also referred to as the preliminary sensing data. The preliminary measurement data can include data that is preliminary processed from the raw measurement data, time delay spread spectrum, Doppler spectrum, micro-Doppler spectrum, angle spectrum, signal strength spectrum, and the like information quantified according to the sensing configuration information (which can also be referred to as the measurement configuration or measurement configuration information, configuration information, and the like). Unlike the sensing final result and the signal measurement data, which quantize a certain value, the object of the quantization is the coordinate value or scale of the spectrum line. This is applicable to various types of spectrum lines, and the quantized value becomes the coordinate value, which also has the benefit of reducing the reporting overhead.

[0049] The signal measurement data, also referred to as the sensing signal measurement data, is data processed from the preliminary measurement data, for example, data processed from the preliminary measurement data corresponding to the time delay, angle, Doppler, micro-Doppler, and the like information, so as to reduce the reporting overhead.

[0050] The sensing final result, which is the RCS, position, distance, speed, target number, and the like information quantified according to the measurement configuration, can reduce the reporting overhead. The position can be represented by the Cartesian coordinate method or the polar coordinate method.

[0051] In some embodiments, as shown in FIG. 3, the information transmission method further includes the following S301 and S302 in combination with FIG. 2.

[0052] In S301, the wireless node reports the sensing capability information to the sensing network element.

[0053] In some embodiments, the wireless node reporting the sensing capability can be active reporting or passive reporting, for example, in response to the sensing capability reporting request sent by the sensing network element. In this way, the wireless node can report its own sensing capability information to the sensing network element, so that the sensing network element can determine the wireless node used for sensing or the related configuration from the plurality of wireless nodes based on the sensing capability information.

[0054] The sensing capability information includes at least one of the following: maximum range of sensing measurement, minimum granularity of sensing measurement, supported sensing mode, sensing accuracy in each sensing mode, transceiving capability in each sensing mode, resource configuration capability. The following explains each information included in the sensing capability information.

[0055] Maximum range of sensing measurement: the maximum range of sensing measurement determined by the coverage capability or the measurement capability, for example, the range of the sensing measurement area, the sensing time delay or distance range, the sensing angle range, the sensing Doppler or speed range, the RCS range, the maximum number of sensing targets, and the like. The sensing measurement area range and the sensing distance range in the sensing capability can be related to the target RCS, for example, being a function of the target RCS or different RCSs corresponding to different values.

[0056] Minimum granularity of perception measurement: the minimum granularity of perception measurement determined by the measurement capability, e.g., the minimum granularity of perception position measurement, the minimum granularity of perception time delay or distance, the minimum granularity of perception angle, the minimum granularity of perception Doppler or velocity, etc. The minimum granularity of perception measurement in the perception capability can be related to the target RCS, e.g., is a function of the target RCS or different RCS corresponds to different values.

[0057] The maximum range of perception measurement and the minimum granularity of perception measurement can help the perception network element to determine whether to select a base station for perception and how to configure the quantization method to reduce the reporting overhead in combination with the perception task.

[0058] Supported perception mode: e.g., the base station supports the self-transmitting and self-receiving mode, the base station A is in the transmitting mode and the base station B is in the receiving mode, the terminal is in the transmitting mode and the base station is in the receiving mode, the base station is in the transmitting mode and the terminal is in the receiving mode, the terminal is in the self-transmitting and self-receiving mode (in the coverage range), the terminal A is in the transmitting mode and the terminal B is in the receiving mode (in the coverage range). In some embodiments, the perception measurement data to be reported is different in different perception modes.

[0059] Transmitting and receiving capability in each perception mode: the capability of “transmitting” and / or “receiving” in different perception modes.

[0060] Resource configuration capability: the resource configuration capability in the terminal self-transmitting and self-receiving mode (in the coverage range), the terminal A transmitting and terminal B receiving mode (in the coverage range).

[0061] Perception accuracy in each perception mode: e.g., perception distance, distance resolution, perceived velocity, velocity resolution, perception angle, angle resolution, perception time delay, etc.

[0062] In S302, the wireless node receives the perception configuration information sent by the perception network element.

[0063] In some embodiments, after receiving the perception capability information sent by the wireless node and determining the perception capability of the wireless node based on the perception capability information, the perception network element can select a suitable perception mode to perform the perception service required by the application function (AF) or terminal.

[0064] The perception configuration information is used to indicate at least one of the following: the first quantization range of the perception measurement parameter, the quantization granularity of the perception measurement parameter, and the number of quantization bits of the perception measurement parameter. The following explains each information indicated by the perception configuration information.

[0065] The first quantization range of the perception measurement parameter: the range of the perception area, the range of the perception time delay or distance, the range of the perception angle, the range of the perception Doppler or velocity, the range of the perception target RCS, the maximum number of perception targets, etc.

[0066] Quantization granularity of the sensing measurement parameter: the granularity of the sensing report, e.g., the quantization granularity of the sensing position measurement, the quantization granularity of the sensing time delay or distance, the quantization granularity of the sensing angle, the quantization granularity of the sensing Doppler or velocity, etc.

[0067] Quantization bit number of the sensing measurement parameter: the quantization bit number of the sensing report.

[0068] In an implementation, the above parameters can be included in the sensing configuration information in a permutation and combination manner. For example, the value range of the sensing measurement parameter + the quantization granularity, according to the two information, the quantization bit number of the sensing measurement parameter can be determined; or the value range of the sensing measurement parameter + the quantization bit number, according to the two parameters, the quantization granularity of the sensing measurement parameter can be determined; or the sensing reference value + the quantization granularity of the sensing measurement parameter + the quantization bit number, the sensing reference value is used to indicate the quantization range of the sensing measurement parameter, and can be the index of the quantization range of the sensing measurement parameter. In this way, all the information does not need to be included in the sensing configuration information, thereby saving the overhead. In addition, the information can be limited values, for example, the quantization granularity is the 2k times of Tc, and for example, the quantization bit number is an integer multiple of 8 bits, thereby further reducing the overhead.

[0069] In another implementation, the sensing configuration information can further include at least one of the following: the sensing mode supported by the wireless node, the cooperation device information, the transceiving capability under each sensing mode, the quality of service (QoS) requirement of the sensing (such as the sensing accuracy requirement, the time delay requirement, etc.), the reporting mode of the sensing measurement information, the configuration information of the wireless node sending the measurement signal, and the configuration information of the wireless node receiving the measurement signal.

[0070] The reporting mode of the sensing measurement information includes periodic reporting, event reporting, event triggered periodic reporting (for the wireless node needing to receive the sensing signal), etc.

[0071] The cooperation device information: the sensing network element provides corresponding other node information. The other node is the node cooperating in the execution of the sensing task.

[0072] The configuration information of the wireless node sending the measurement signal: the sensing network element recommends the configuration information of the wireless node sending the measurement signal according to the sensing mode.

[0073] The configuration information of the wireless node receiving the measurement signal: for the wireless node A sending the wireless node B receiving mode, the configuration information of indicating a certain wireless node as the receiving role.

[0074] It can be understood that, in the case of the wireless node being a UE, the range perceived by the UE is smaller, which is mainly used for small-range smart factory, human posture recognition, augmented reality (AR) and other application scenarios, limited by the computing power of the UE and the perception range of the UE. For such small-range large-granularity perception, a large amount of reporting overhead can be saved.

[0075] In some embodiments, the quantized perception measurement parameter is obtained based on a quantization interval to which a value of the perception measurement parameter belongs. The quantization interval is an interval obtained by dividing a first quantization range based on a quantization granularity of the perception measurement parameter.

[0076] After obtaining the value of the perception measurement parameter, the wireless node can determine the quantization interval to which the value of the perception measurement parameter belongs. Since the quantization interval is a quantization interval obtained by dividing the first quantization range based on the quantization granularity, the value range of the quantization interval is smaller, which can reduce the number of bits used for quantization, thereby reducing the reporting overhead when reporting. The quantization process of the perception measurement parameter is described below in various ways (ways one to seven).

[0077] In the case where the first quantization range includes an upper limit value and a lower limit value, the quantized perception measurement parameter Q satisfies the following formula:

[0078] Or

[0079] Wherein, S is the value of the perception measurement parameter, S0 is the lower limit value of the first quantization range, S1 is the upper limit value of the first quantization range, and Δ is the quantization granularity of the perception measurement parameter.

[0080] For RCS, distance, one-dimensional angle, speed, target data in the perception measurement parameter (for example, the above-mentioned perception final result), or scalar information such as time delay, one-dimensional angle, Doppler, and micro-Doppler in the above-mentioned signal measurement data, taking the time delay t as an example, in the case where the first quantization range includes an upper limit value t1 and a lower limit value t0 (for example, t0≤t<t1), the value of the quantized perception measurement parameter can be Or Wherein t1-t0 is n times of Δt, and n is an integer. Alternatively, the quantized perception measurement parameter can also be determined by a table:

[0081] Table 1

[0082] Wherein, t QFor the quantized value of the perception measurement parameter, Δt is the quantization granularity, and tΔ is the quantization interval based on Δt. For example, when the value of the perception measurement parameter belongs to t0+Δt≤t<t0+2Δt, the quantized value of the perception measurement parameter is 1. In the above manner, data outside the first quantization range is not quantized and fed back, and the number of quantized values is n. Further, n can be limited to 2 k , k is the number of quantization bits, and is a positive integer, which can be quantized by binary numbers.

[0083] In an implementation manner, for data outside the first quantization range, data greater than the first quantization range can be quantized to a first value, and data less than the first quantization range can be quantized to a second value. In some embodiments, the first value can be greater than the maximum value of the plurality of quantized values of the perception measurement parameter, and the second value can be less than the minimum value of the plurality of quantized values of the perception measurement parameter. For example, taking the time delay t as an example, the quantized value of the perception measurement parameter t Q satisfies the following formula:

[0084] Alternatively, the quantized value of the perception measurement parameter satisfies the following table:

[0085] Table 2

[0086] wherein t Q is the quantized value of the perception measurement parameter, tΔ is the quantization interval based on Δt, Δt is the quantization granularity, the first value is n+1, and the second value is 0. Alternatively, if 0 corresponds to t0≤t<t0+Δt and n-1 corresponds to t1-Δt≤t<t1, the first value can be a value greater than n-1, and the second value can be a value less than 0. At this time, the number of quantized values is n+2. Further, n can be limited to 2 k , k is a positive integer, which can be quantized by binary numbers.

[0087] In a second manner, when the absolute value of the value of the perception measurement parameter belongs to the first quantization range, the quantized perception measurement parameter satisfies the following formula:

[0088] wherein Q is the quantized perception measurement parameter, S is the value of the perception measurement parameter, S1 is the upper limit value of the first quantization range, S0 is the lower limit value of the first quantization range, Δ is the quantization granularity, and k is the number of quantization bits.

[0089] For the above scalar data, taking the speed v as an example, when the absolute value of the value of the sensing measurement parameter belongs to the first quantization range (for example, v0 ≤ |v| < v1), and the quantization bit number of the sensing parameter is k, the quantization granularity of the speed v can be Δv = (v1 - v0) / 2 k-1 , the value v of the quantized sensing measurement parameter Q satisfies the following formula:

[0090] It should be understood that when the quantization bit number is k and quantization is performed in binary, since the sensing measurement parameter can also have negative values, the first quantization range includes the third quantization range, for example, (-v1, -v0), and the fourth quantization range, for example, (v0, v1). Therefore, the total number of quantized values is 2 k values, and the first (or the last, the above formula is the first) 2 k-1 values can be used to represent the case where the value of the sensing measurement parameter is negative, and the last 2 k-1 values can be used to represent the case where the value of the sensing measurement parameter is negative.

[0091] Alternatively, the value of the quantized sensing measurement parameter satisfies the following table:

[0092] Table 3

[0093] where, v Q is the value of the quantized sensing measurement parameter, Δv is the quantization granularity, and v Δ is the quantization interval divided based on Δv. For example, when the sensing measurement parameter belongs to v0 + Δv ≤ v < v0 + 2Δv, the value of the quantized sensing measurement parameter is 0. The above method does not perform quantization and feedback on data outside the first quantization range, and the number of quantized values is n. Further, n can be limited to 2 k , k is the quantization bit number, which is a positive integer, and quantization can be performed using binary numbers.

[0094] In one implementation, the highest bit of v Q can be used to represent the positive or negative sign. For example, 0 represents the positive sign and 1 represents the negative sign, and the remaining bits v′ Q of v Q can be represented as or satisfy the following table:

[0095] Table

[0096] where, 0, 1…2 k-1 -1 are used to represent the case where the sensing measurement parameter is positive, and 2 k-1 ,…2k -1 is used to represent the case that the perceptual measurement parameter is negative.

[0097] It should be understood that for the parameters outside the first quantization range, the quantization method for the perceptual measurement parameters outside the first quantization range in the above manner one can be referred to, and the embodiments of the present disclosure will not be repeated.

[0098] In the third manner, in the case that the first quantization range includes a quantization range greater than or equal to a lower limit value, the quantized perceptual measurement parameter satisfies the following formula:

[0099] wherein Q is the quantized perceptual measurement parameter, S is the value of the perceptual measurement parameter, S0 is the lower limit value of the first quantization range, Δ is the quantization granularity of the perceptual measurement parameter, k is the quantization number of the perceptual measurement parameter, and k is a positive integer.

[0100] For the above scalar information, the first quantization range only includes the lower limit value without the upper limit value. Taking RCS as an example, σ≥σ0, the quantization granularity is Δσ, and the quantization number k. The quantized perceptual measurement parameter satisfies the following formula:

[0101] Alternatively, the quantized perceptual measurement parameter can satisfy the following table:

[0102] Table 5

[0103] It should be understood that when the quantization number is k, the number of quantized values is 2 k Therefore, 2 k -1 values can be used to represent the range of (σ0, σ0+(2 k -1)Δσ), and values outside this range are represented by a number greater than 2 k -1, for example, 2 k -1 in the above formula.

[0104] In the fourth manner, the perceptual measurement parameter is a first vector, the first quantization range includes a plurality of quantization ranges, and the first vector includes a plurality of elements corresponding to the plurality of quantization ranges. The quantized perceptual measurement parameter is a second vector obtained by quantizing each element included in the first vector. The quantization processing includes: dividing the quantization range corresponding to the element in the first vector to obtain a quantization interval based on the quantization granularity of the perceptual measurement parameter, and obtaining the quantization value corresponding to the element according to the quantization interval.

[0105] In some embodiments, the first quantization range is determined based on a center reference point, a quantization granularity, and a quantization number of the perceptual measurement parameter. It should be understood that the quantization granularity and the quantization number corresponding to the plurality of elements in the first vector can be the same or different.

[0106] In the case that the value of the perception measurement parameter is a vector value, since multiple elements are included in the vector value, the quantization can be performed according to the quantization range corresponding to each element by the above-mentioned manner 1 to manner 3, so as to realize the quantization of the vector. For example, as shown in FIG. 4A, four coordinates (x0, y0), (x0, y1), (x1, y0), (x1, y1) jointly constitute a region range. When representing the position information (x, y) in the region range, the perception network element can quantize x and y respectively. Δx and Δy are the quantization granularities of x and y respectively, k is the quantization bit number, and the center reference point is (O x , O y ) (for example, the center reference point can be the center of the region range, can be one of the four coordinates, or can be other coordinates), so that the quantization range corresponding to x is (O x -2 k-1 Δx, O x +2 k-1 Δx), and the quantization range corresponding to y is (O y -2 k-1 Δy, O y +2 k-1 Δy), then the quantized perception measurement parameter satisfies the following formula:

[0107] wherein x Q , y Q are two elements in the second vector, x, y are two elements included in the first vector, O x is an element in the center reference point corresponding to x, O y is an element in the center reference point corresponding to y, Δx is the quantization granularity corresponding to x, Δy is the quantization granularity corresponding to y, k is the quantization bit number of the perception measurement parameter, and k is a positive integer.

[0108] Alternatively, the quantized perception measurement parameter satisfies the following table:

[0109] Table 6

[0110] wherein x Δ is the quantization range corresponding to x, y Δ is the quantization range corresponding to y, x Q is the quantized value of x, and y Q is the quantized value of y. In some embodiments, Δx and Δy can be the same, and can be configured by one parameter, so as to reduce the overhead of configuration information.

[0111] It should be noted that the embodiments of the present disclosure can transmit the center reference point and the number of quantization bits and the quantization precision, and determine the quantization range through these parameters, so that the quantization range does not need to be transmitted, and the overhead can be saved. In some embodiments, the center reference point can be configured through the perception configuration information.

[0112] In an implementation manner, as shown in FIG. 4B, four polar coordinates (r0, θ0), (r0, θ1), (r1, θ0), (r1, θ1) constitute a region range. For position information (r, θ) in the region range, Δr is the quantization granularity corresponding to r, and Δθ is the quantization granularity corresponding to θ, and the wireless node can quantize the position information through the above-mentioned four manners. Correspondingly, both the three-dimensional Cartesian coordinates and the three-dimensional polar coordinates can be quantized through the above-mentioned four manners respectively, so as to solve the problem of reporting the vector value quantization.

[0113] In the fifth manner, in the case that the perception measurement parameter includes the position parameter, the position parameter is a first position vector, the perception region range includes a plurality of regions, each region corresponds to a reference point coordinate, the first quantization range includes a plurality of second quantization ranges, and each region corresponds to a second quantization range, the second quantization range is determined based on the reference point coordinate of the corresponding region and the size of the corresponding region. It should be understood that the second quantization range includes the quantization range of each element in the position vector.

[0114] In the case that the perception measurement parameter is the position parameter, since the perception region range to which the position parameter belongs can be a region range of irregular shape, the value range of an element in the position vector (or the position parameter) is different at different positions, for example, the value range of the horizontal coordinate is different at different vertical coordinates, therefore, if the same quantization range is used for an element, the quantization range will be too large and the quantization precision will be reduced. For example, in FIG. 5, the value range of the horizontal coordinate in the first row is different from the value range of the horizontal coordinate in the last row. Therefore, if the quantization ranges of all horizontal coordinates are the same, the quantization range of the horizontal coordinate in the first row is the quantization range of the horizontal coordinate in the last row, and for the horizontal coordinate in the first row, the quantization range of the horizontal coordinate in the last row is larger, so the quantization precision will be reduced when reporting.

[0115] In this case, the perception region range can be divided into M regions, for example, a plurality of rectangular units with the same size. The perception network element can configure the size (a, b) of the rectangular unit and the reference point coordinate (O xi ,O yi), i = 0, 1,..., M-1, quantization granularity A or quantization bit number k (quantization granularity and quantization bit number of the plurality of rectangular units can be the same), the number of rectangular units, etc. In this way, the wireless node can determine the second quantization range corresponding to the position parameter in the rectangular unit according to the size of the rectangular unit, the reference point coordinates (for example, the center or a certain corner), so that the position parameter in the rectangular unit can be quantized by the value range when quantizing. It should be understood that when the sizes of the plurality of rectangular units are the same, the sizes of the plurality of second value ranges are the same.

[0116] In an implementation manner, since the quantization bit number and the quantization granularity of the plurality of rectangular units can be the same, the number of quantization values corresponding to the plurality of rectangular units for quantizing the perception measurement parameter can be the same, the number of quantization values corresponding to the plurality of rectangular units is the same, and the sum of the number of quantization values corresponding to the plurality of regions is the first number. The first number (i.e., the number based on the quantization bit number) of quantization values corresponds to all rectangular units, that is, the number of quantization values corresponding to each rectangular unit is M is the number of rectangular units. For example, the reference point coordinates of the rectangular unit 1 are (O xi ,O yi ), the value range corresponding to x is (O xi ,O xi +a), and the value range corresponding to y is (O yi ,O yi +b). As shown by b in FIG. 5, the rectangular unit can be divided into a plurality of quantization intervals based on the reference point coordinates and the rectangular size, and the four vertices (x0, y0), (x0, y1), (x1, y0), (x1, y1) can represent the upper and lower limits of the second quantization range corresponding to the region, and Ax and Ay are the quantization granularities corresponding to x and y respectively.

[0117] In this way, the larger quantization range is divided into a plurality of smaller quantization ranges, and for the region with a smaller quantization range, the waste of the quantization range can be reduced, and the precision of quantization can be improved. In some embodiments, when quantization is performed based on the quantization range of the rectangular unit, the elements in the position parameter can be quantized respectively in combination with the quantization granularity and the quantization bit number. The reference point coordinates can be global coordinates or relative coordinates, for example, coordinates relative to the position of the wireless node.

[0118] Only one reference point coordinate can be configured, and the other reference point coordinates can be determined by the size of the rectangular unit. For example, one reference point coordinate (O x0 ,O y0 ) is configured, and the other reference point coordinates can be (O x0 +ma, O y0+ nb), m is the number of rectangular units in the horizontal coordinate, and n is the number of rectangular units in the vertical coordinate. The rectangular unit can be a square, and only one value can be configured when configuring the size.

[0119] In some embodiments, in the case where the first number of quantized values corresponds to one region, the perception measurement information further comprises an index of the region to which the perception measurement parameter corresponds, and the first number is the number of quantized values of the perception measurement parameter determined based on the number of quantization bits.

[0120] In the case where each region corresponds to the first number of quantized values, the multiple regions are used to represent the quantized values of the quantized perception measurement parameter, and the number of quantized values corresponding to each rectangular unit is 2 k Therefore, when reporting the quantized perception measurement parameter, there will be repeated quantized values. In this case, the index of the region to which the perception measurement parameter belongs can be added in the perception measurement information, so that the perception measurement parameter can be determined. In this way, since each region is quantized by the number of quantization bits, the quantization accuracy is higher.

[0121] It should be noted that, since the perception region range is an irregular region, part of the rectangular units in the multiple rectangular units do not belong to the perception region range, so that the quantization range corresponding to this part of the region is wasted. However, since the quantization range corresponding to each rectangular unit is a smaller quantization range divided based on the quantization range corresponding to the perception region range, the wasted quantization range is less.

[0122] In an implementation manner, the quantization granularity and the number of bits for quantization in the rectangular unit (for example, a rectangle or a cuboid) can be further limited to a specific value or a set of values. In this way, the quantization method in the rectangular unit can be fixed. At this time, the index of the ordered rectangular or cuboid unit can further determine which rectangular or cuboid unit is selected, so as to realize complete quantization. Although the quantization method in the rectangular or cuboid unit is fixed, the quantization method of the index of the rectangular or cuboid unit still needs to be determined by the configured quantization information.

[0123] It should be noted that the position parameter can not only be two-dimensional, but also three-dimensional, that is, the perception measurement configuration rectangular unit is a cuboid unit, and the size is (a, b, c). The position of the reference point of each ordered rectangular unit is (O xi , O yi , O zi ), i = 0, 1,..., M-1, and the quantization granularity Δ or the number of quantization bits k. The quantization granularity Δ or the number of quantization bits can be shared by the three dimensions (or elements), or can be for each of the three dimensions. The position of the reference point of each rectangular unit (O xi , Oyi O zi ) can be a point of a certain corner of a cuboid or a center point. The reference point position (O xi O yi O zi ) can be a global coordinate system or a relative coordinate system, for example, a position coordinate system relative to a base station or a UE. The reference point position (O xi O yi O zi ) can be in granularity (a, b, c), and the coordinates (O x0 O y0 O z0 ) of a reference point can be configured or specified, and the positions of other reference points can be expressed as actual coordinates (O x0 + ma, O y0 + nb, O z0 + lc). In addition, the number M of cuboids can also be configured. The cuboid unit in this embodiment can also be changed to a cube, and when the unit size is configured, only a needs to be configured. The cuboid can also be limited to a = b, and only a and c need to be configured for the unit size. In combination with the characteristics of actual perception, the xy plane and the z height can use different quantization granularities Δ or quantization bit numbers k, respectively. When measuring and reporting, the above two methods can be used, that is, the perception measurement information can be directly quantized according to the perception configuration information, or the perception measurement information can include the index of the cuboid unit and the quantization result (i.e., the quantized perception measurement parameter) in the cuboid.

[0124] Sixth, in the case of a non-regularly shaped area as the perception area range, in combination with the above-mentioned fifth, the plurality of rectangular units are rectangular units of different sizes. As shown in FIG. 6, the perception area range is divided into three rectangular units of different sizes. The perception network element can configure the size of each rectangular unit, the reference point coordinates, etc. in the perception measurement configuration. In some embodiments, as shown in FIG. 6, the vertices of a rectangular unit can include (x0, y0), (x0, y1), (x1, y0), (x1, y1), and the size of the rectangular unit can be configured by the vertices of two opposite sides.

[0125] Since the sizes of the plurality of rectangular units are different, the sizes of the first value ranges corresponding to the plurality of rectangular units are different. If the quantization bit numbers and the quantization granularities of the plurality of rectangular units are the same, the number of quantization values corresponding to the plurality of rectangular units is different, and the sum of the number of quantization values corresponding to the plurality of areas is the first number. In this way, the perception range is divided according to the rectangular units of different sizes, which is more flexible and more adaptive.

[0126] In some embodiments, the plurality of regions correspond to different quantization granularities, and the quantized values of the quantized perceptual measurement parameters are all the same, i.e., the number of quantized values corresponding to each rectangular unit is 2 k Therefore, when reporting the quantized perceptual measurement parameters, there are repeated quantized values. In this case, the region index to which the perceptual measurement parameter belongs can be added in the perceptual measurement information, so that the perceptual measurement parameter can be determined. In this way, since each region is quantized by the number of quantization bits, the quantization accuracy is higher.

[0127] It should be understood that the two quantization and reporting manners in Mode Six can refer to the two quantization and reporting manners in the above modes, and the embodiments of the present disclosure will not be described again.

[0128] In Mode Seven, the lower limit value of the value range corresponding to an element in the first position vector is determined based on the minimum value of the element in the plurality of reference point coordinates, and the upper limit value of the value range corresponding to the element in the first position vector is determined based on the maximum value of the element in the plurality of reference point coordinates.

[0129] In the case where the perceptual area range is a region in an irregular shape, as shown in FIG. 7, the perception network element can divide the perceptual area range into a plurality of polygons through the perceptual configuration information, and configure the vertices of each polygon as (P i ,Q i ), i = 0, 1,..., M-1, and M is the number of polygons. The vertex position (P i ,Q i ) can be a global coordinate system or a relative coordinate system, for example, a position coordinate system relative to a base station or a UE. When reporting, the wireless node can determine the quantization range of x and y according to the maximum and minimum values of (P i ,Q i ) in the configuration, and quantize x and y respectively in combination with the quantization granularity Δ or the number of quantization bits k.

[0130] In an implementation manner, in the above Mode Four, Mode Five, Mode Six, and Mode Seven, the position parameter can change from a two-dimensional vector to a three-dimensional vector, and at this time, the perceptual area range is also a three-dimensional space, and the rectangular unit is also a three-dimensional space. The quantization of the perceptual measurement parameter in the three-dimensional space can refer to the quantization of the two-dimensional perceptual measurement parameter described above, and the embodiments of the present disclosure will not be described again.

[0131] The information transmission method provided by the embodiments of the present disclosure can be applied to the perception network element 101 in the communication system shown in FIG. 1. FIG. 8 shows a flow diagram of another information transmission method. As shown in FIG. 8, the information transmission method comprises S801.

[0132] In S801, the sensing network element receives the sensing measurement information sent by the wireless node.

[0133] The sensing measurement information includes quantized sensing measurement parameters. The quantized sensing measurement parameters are quantized based on a first quantization range.

[0134] Since the sensing measurement parameters are quantized based on the first quantization range, the first quantization range is smaller than the maximum quantization range of the sensing measurement parameters, so that by reducing the quantization range of the sensing measurement parameters, the number of bits required for quantization is reduced, and the communication overhead is smaller when transmitting the quantized sensing measurement parameters.

[0135] In addition, although the number of bits required for quantization is reduced, the number of quantization values corresponding to the bits is also reduced, but since the value range corresponding to the sensing measurement parameters is also reduced, i.e. the range of parameter values of the sensing measurement parameters represented by the quantization values is also reduced, the quantization can keep the quantization accuracy unchanged, and the value of the sensing measurement parameters is represented by fewer bits, so that the reporting overhead can be reduced while maintaining the reporting accuracy. Especially for wireless sensing, since the target of interest of the sensing service has certain speed, position, RCS and other characteristics, the value range of the related sensing measurement parameters can be flexibly limited according to the service demand, so as to reduce the overhead required for quantization under the same quantization accuracy.

[0136] It should be noted that the quantization and reporting method of the sensing measurement parameters can refer to the above-mentioned content of the wireless node side, and the embodiments of the present disclosure will not be repeated here.

[0137] It can be understood that the information transmission device includes hardware structures and / or software modules corresponding to the execution of each function in order to realize the above functions. Those skilled in the art should easily realize that the algorithm steps of each example described in combination with the embodiments of the present disclosure can be realized in the form of hardware or a combination of hardware and computer software. Whether a certain function is executed in hardware or computer software driven hardware depends on the specific application of the technical solution and the design constraints. Professional technicians can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of the present disclosure.

[0138] The embodiments of the present disclosure can divide the functional modules of the information transmission device according to the above-mentioned method embodiments. For example, each functional module can be divided according to each function, or two or more functions can be integrated into one functional module. The integrated module can be realized in the form of hardware or in the form of software. It should be noted that the division of the modules in the embodiments of the present disclosure is illustrative, and is only a logical functional division. In actual implementation, another division mode can be used. The following will be described taking the division of each functional module according to each function as an example.

[0139] FIG. 9 is a structural schematic diagram of a communication device according to an embodiment of the present disclosure. The communication device can execute the information transmission method provided by the above-mentioned method embodiments. As shown in FIG. 9, the communication device includes a sending unit 901. The sending unit 901 is configured to send sensing measurement information to a sensing network element. The sensing measurement information includes quantized sensing measurement parameters. The quantized sensing measurement parameters are obtained by quantization based on a first quantization range configured by the sensing network element.

[0140] In an implementation mode, the communication device further includes a receiving unit 902. The receiving unit 902 is configured to receive sensing configuration information sent by the sensing network element. The sensing configuration information is used to indicate at least one of the following: the first quantization range of the sensing measurement parameter, the quantization granularity of the sensing measurement parameter, and the number of quantization bits of the sensing measurement parameter.

[0141] In an implementation mode, the sending unit 901 is further configured to report sensing capability information to the sensing network element. The sensing capability information includes at least one of the following: a maximum range of sensing measurement, a minimum granularity of sensing measurement, a supported sensing mode, a sensing accuracy in each sensing mode, a transceiving capability in each sensing mode, and a resource configuration capability.

[0142] In an implementation mode, the sensing measurement parameter includes original measurement data or data obtained by processing the original measurement data.

[0143] In an implementation mode, the quantized sensing measurement parameter is obtained based on a quantization interval to which a value of the sensing measurement parameter belongs. The quantization interval is an interval obtained by dividing the first quantization range based on a quantization granularity of the sensing measurement parameter.

[0144] In an implementation mode, in a case where the first quantization range includes an upper limit value and a lower limit value, the quantized sensing measurement parameter Q satisfies the following formula:

[0145] Or

[0146] wherein S is a value of the perception measurement parameter, S0 is a lower limit value of the first quantization range, S1 is an upper limit value of the first quantization range, and Δ is a quantization granularity of the perception measurement parameter.

[0147] In an implementation, in a case where an absolute value of the value of the perception measurement parameter belongs to the first quantization range, the quantized perception measurement parameter satisfies the following formula:

[0148] wherein Q is the quantized perception measurement parameter, S is the value of the perception measurement parameter, S1 is the upper limit value of the first quantization range, S0 is the lower limit value of the first quantization range, Δ is the quantization granularity, and k is a quantization bit number of the perception measurement parameter, k being a positive integer.

[0149] In an implementation, in a case where the first quantization range includes a quantization range greater than or equal to the lower limit value, the quantized perception measurement parameter satisfies the following formula:

[0150] wherein Q is the quantized perception measurement parameter, S is the value of the perception measurement parameter, S0 is the lower limit value of the first quantization range, Δ is the quantization granularity of the perception measurement parameter, and k is the quantization bit number of the perception measurement parameter, k being a positive integer.

[0151] In an implementation, the perception measurement parameter is a first vector, the first quantization range includes a plurality of quantization ranges, and the first vector includes a plurality of elements corresponding to the plurality of quantization ranges; and the quantized perception measurement parameter is a second vector obtained by performing quantization processing on each element included in the first vector. The quantization processing includes: dividing a quantization range corresponding to an element in the first vector to obtain a quantization interval based on a quantization granularity of the perception measurement parameter, and obtaining a quantization value corresponding to the element according to the quantization interval.

[0152] In an implementation, the first quantization range is determined based on a center reference point, a quantization granularity, and a quantization bit number of the perception measurement parameter.

[0153] In an implementation, the quantized perception measurement parameter satisfies the following formula:

[0154] wherein x Q , y Q are two elements in the second vector, x and y are two elements included in the first vector, O x is an element in a center reference point corresponding to x, O y is an element in a center reference point corresponding to y, Δx is a quantization granularity corresponding to x, Δy is a quantization granularity corresponding to y, and k is a quantization bit number of the perception measurement parameter, k being a positive integer.

[0155] In an implementation manner, the perception measurement parameter comprises a position parameter, the position parameter is a first position vector, the perception area range comprises a plurality of areas, each area corresponds to a reference point coordinate, the first quantization range comprises a plurality of second quantization ranges, one area corresponds to one second quantization range, and the second quantization range is determined based on the reference point coordinate of the corresponding area and the size of the corresponding area.

[0156] In an implementation manner, the first number of quantized values corresponds to one area, and the perception measurement information further comprises an index of the area corresponding to the perception measurement parameter. The first number is a number of quantized values of the perception measurement parameter determined based on the number of quantization bits.

[0157] In an implementation manner, the number of quantized values corresponding to each area in the plurality of areas is the same or different.

[0158] In an implementation manner, a lower limit value of a value range corresponding to an element in the first position vector is determined based on a minimum value of the element in the plurality of reference point coordinates, and an upper limit value of the value range corresponding to the element in the first position vector is determined based on a maximum value of the element in the plurality of reference point coordinates.

[0159] FIG. 10 is a structural schematic diagram of another communication apparatus according to an embodiment of the present disclosure. The communication apparatus can perform the information transmission method provided by the above-mentioned method embodiments. As shown in FIG. 10, the communication apparatus comprises a receiving unit 1001. The receiving unit 1001 is configured to receive perception measurement information sent by a wireless node. The perception measurement information comprises quantized perception measurement parameters. The quantized perception measurement parameters are obtained by quantization based on a first quantization range configured by a perception network element.

[0160] In an implementation manner, the communication apparatus further comprises a sending unit 1002. The sending unit 1002 is configured to send perception configuration information to the wireless node. The perception configuration information is used to indicate at least one of the following: a quantization range of the perception measurement parameter, a quantization granularity of the perception measurement parameter, and a number of quantization bits of the perception measurement parameter.

[0161] In an implementation manner, the receiving unit 1001 is configured to receive perception capability information reported by the wireless node. The perception capability information comprises at least one of the following: a maximum range of perception measurement, a minimum granularity of perception measurement, a supported perception mode, a perception accuracy in each perception mode, a transceiving capability in each perception mode, and a resource configuration capability.

[0162] In an implementation manner, the perception measurement parameter comprises original measurement data or data obtained by processing the original measurement data.

[0163] In an implementation, the quantized perception measurement parameter is obtained based on a quantization interval to which a value of the perception measurement parameter belongs. The quantization interval is obtained by dividing the first quantization range based on a quantization granularity of the perception measurement parameter.

[0164] In an implementation, when the first quantization range includes an upper limit value and a lower limit value, the quantized perception measurement parameter Q satisfies the following formula:

[0165] Or

[0166] wherein S is the value of the perception measurement parameter, S0 is the lower limit value of the first quantization range, S1 is the upper limit value of the first quantization range, and Δ is the quantization granularity of the perception measurement parameter.

[0167] In an implementation, when the absolute value of the value of the perception measurement parameter belongs to the first quantization range, the quantized perception measurement parameter satisfies the following formula:

[0168] wherein Q is the quantized perception measurement parameter, S is the value of the perception measurement parameter, S1 is the upper limit value of the first quantization range, S0 is the lower limit value of the first quantization range, Δ is the quantization granularity, k is the quantization bit number, and k is a positive integer.

[0169] In an implementation, when the first quantization range includes a quantization range greater than or equal to the lower limit value, the quantized perception measurement parameter satisfies the following formula:

[0170] wherein Q is the quantized perception measurement parameter, S is the value of the perception measurement parameter, S0 is the lower limit value of the first quantization range, Δ is the quantization granularity of the perception measurement parameter, k is the quantization bit number of the perception measurement parameter, and k is a positive integer.

[0171] In an implementation, the perception measurement parameter is a first vector, the first quantization range includes a plurality of quantization ranges, and the first vector includes a plurality of elements corresponding to the plurality of quantization ranges; the quantized perception measurement parameter is a second vector obtained by performing quantization processing on each element included in the first vector. The quantization processing includes: dividing the quantization range corresponding to the element in the first vector based on the quantization granularity of the perception measurement parameter to obtain a quantization interval, and obtaining a quantization value corresponding to the element according to the quantization interval.

[0172] In an implementation, the first quantization range is determined based on a center reference point, a quantization granularity, and a quantization bit number of the perception measurement parameter.

[0173] In an implementation, the quantized perception measurement parameter satisfies the following formula:

[0174] wherein x Q , y Q are two elements in the second vector, x, y are two elements included in the first vector, O x is an element in the central reference point corresponding to x, O y is an element in the central reference point corresponding to y, Δx is the quantization granularity corresponding to x, Δy is the quantization granularity corresponding to y, k is the number of quantization bits of the perceptual measurement parameter, and k is a positive integer.

[0175] In an implementation, in a case where the perceptual measurement parameter includes a position parameter, the position parameter is a first position vector, the perceptual area range includes a plurality of areas, each area corresponds to a reference point coordinate, the first quantization range includes a plurality of second quantization ranges, and each area corresponds to a second quantization range, the second quantization range is determined based on the reference point coordinate of the corresponding area and the size of the corresponding area.

[0176] In an implementation, in a case where the first number of quantization values corresponds to one area, the perceptual measurement information further includes an index of the area corresponding to the perceptual measurement parameter. The first number is the number of quantization values used for quantizing the perceptual measurement parameter, which is determined based on the number of quantization bits.

[0177] In an implementation, the number of quantization values corresponding to each area in the plurality of areas is the same or different.

[0178] In an implementation, the lower limit value of the value range corresponding to an element in the first position vector is determined based on the minimum value of the elements in the plurality of reference point coordinates; and the upper limit value of the value range corresponding to the element in the first position vector is determined based on the maximum value of the elements in the plurality of reference point coordinates.

[0179] In a case where the functions of the above integrated modules are implemented in the form of hardware, the embodiments of the present disclosure provide another structure of the communication apparatus involved in the above embodiments. As shown in FIG. 11, the communication apparatus 110 includes a processor 1102 and a bus 1104. In some embodiments, the communication apparatus can further include a memory 1101. In some embodiments, the communication apparatus can further include a communication interface 1103.

[0180] The processor 1102 can be a central processing unit, an application-specific processor, a digital signal processor, an application-specific integrated circuit, a field programmable gate array, or other programmable logic device, transistor logic device, hardware component, or any combination thereof. The processor 1102 can implement or execute various exemplary logical blocks, modules, and circuits described in connection with the embodiments of the present disclosure. The processor 1102 can also be a combination of computing components, such as a combination of one or more microprocessors, a combination of a DSP and a microprocessor, and the like.

[0181] The communication interface 1103 is configured to connect with other devices through a communication network. The communication network can be an Ethernet, a wireless access network, a wireless local area network (WLAN), and the like.

[0182] The memory 1101 can be a read-only memory (ROM) or other type of static storage device that can store static information and instructions, a random access memory (RAM) or other type of dynamic storage device that can store information and instructions, an electrically erasable programmable read-only memory (EEPROM), a magnetic disk storage medium, or other magnetic storage device, or any other medium that can be used to carry or store desired program code in the form of instructions or data structures and that can be accessed by a computer, but is not limited thereto.

[0183] As an implementation manner, the memory 1101 can exist independently of the processor 1102, and the memory 1101 can be connected with the processor 1102 through the bus 1104, and used to store instructions or program codes. When the processor 1102 invokes and executes the instructions or program codes stored in the memory 1101, the information transmission method provided by the embodiments of the present disclosure can be implemented.

[0184] In another implementation manner, the memory 1101 can also be integrated with the processor 1102.

[0185] The bus 1104 can be an extended industry standard architecture (EISA) bus, etc. The bus 1104 can be divided into an address bus, a data bus, a control bus, etc. For ease of representation, only one thick line is shown in FIG. 11, but this does not mean that there is only one bus or only one type of bus.

[0186] Some embodiments of the present disclosure provide a computer readable storage medium (for example, a non-transitory computer readable storage medium) having stored computer program instructions. The computer program instructions, when run on a computer, cause the computer to perform the information transmission method described in any of the above embodiments.

[0187] Exemplarily, the above computer readable storage medium can include, but is not limited to, a magnetic storage device (for example, a hard disk, a floppy disk, or a magnetic tape, etc.), an optical disc (for example, a compact disk (CD), a digital versatile disk (DVD), etc.), a smart card, and a flash memory device (for example, an erasable programmable read-only memory (EPROM), a card, a stick, or a key drive, etc.). The various computer readable storage media described in the present disclosure can represent one or more devices and / or other machine readable storage media for storing information. The term "machine readable storage medium" can include, but is not limited to, a wireless channel and various other media capable of storing, containing, and / or carrying instructions and / or data.

[0188] The embodiments of the present disclosure provide a computer program product containing instructions, which, when run on a computer, cause the computer to perform the information transmission method described in any of the above embodiments.

[0189] The above is only a specific implementation of the present disclosure, but the protection scope of the present disclosure is not limited thereto. Any change or replacement within the technical scope disclosed in the present disclosure should be covered within the protection scope of the present disclosure. Therefore, the protection scope of the present disclosure should be subject to the protection scope of the claims.

Claims

1. An information transmission method applied to a wireless node, comprising: sending, to a sensing network element, sensing measurement information, the sensing measurement information comprising quantized sensing measurement parameters, the quantized sensing measurement parameters being quantized based on a first quantization range configured by the sensing network element.

2. The method of claim 1, further comprising: receiving sensing configuration information sent by the sensing network element, the sensing configuration information being used to indicate at least one of the following: the first quantization range of the sensing measurement parameter, a quantization granularity of the sensing measurement parameter, a number of quantization bits of the sensing measurement parameter.

3. The method of claim 2, further comprising: reporting, to the sensing network element, sensing capability information, the sensing capability information comprising at least one of the following: a maximum range of sensing measurement, a minimum granularity of sensing measurement, a supported sensing mode, a sensing accuracy in each sensing mode, a transceiving capability in each sensing mode, a resource configuration capability.

4. The method of claim 1, wherein, The sensing measurement parameter comprises raw measurement data or data processed based on the raw measurement data.

5. The method of claim 1, wherein, The quantized sensing measurement parameter is further quantized based on a quantization granularity of the sensing measurement parameter and a number of quantization bits of the sensing measurement parameter.

6. The method of claim 1, wherein, The quantized sensing measurement parameter is obtained based on a quantization interval to which a value of the sensing measurement parameter belongs, the quantization interval being obtained by dividing the first quantization range based on the quantization granularity of the sensing measurement parameter.

7. The method of claim 6, wherein, In the case that the first quantization range comprises an upper limit value and a lower limit value, the quantized perceptual measurement parameter Q satisfies the following formula: or Wherein, S is the value of the sensing measurement parameter, S0 is the lower limit value of the first quantization range, S1 is the upper limit value of the first quantization range, and Δ is the quantization granularity of the sensing measurement parameter.

8. The method of claim 6, wherein, In case the absolute value of the value of the perceptual measurement parameter is attributed to the first quantization range, the quantized perceptual measurement parameter fulfils the following formula: Wherein, Q is the quantized sensing measurement parameter, S is the value of the sensing measurement parameter, S1 is the upper limit value of the first quantization range, S0 is the lower limit value of the first quantization range, Δ is the quantization granularity, k is the number of quantization bits, and k is a positive integer.

9. The method of claim 6, wherein, In the case where the first quantization range includes a quantization range greater than or equal to a lower limit value, the quantized perceptual measurement parameter satisfies the following formula: Wherein, Q is the quantized sensing measurement parameter, S is the value of the sensing measurement parameter, S0 is the lower limit value of the first quantization range, Δ is the quantization granularity of the sensing measurement parameter, and k is the number of quantization bits of the sensing measurement parameter, k being a positive integer.

10. The method of claim 6, wherein, The sensing measurement parameter is a first vector, the first quantization range comprises a plurality of quantization ranges, and the first vector comprises a plurality of elements corresponding to the plurality of quantization ranges. The quantized sensing measurement parameter is a second vector obtained by quantizing each element in the plurality of elements included in the first vector, the quantization processing comprising: dividing a quantization range corresponding to each element in the plurality of elements in the first vector to obtain a quantization interval based on the quantization granularity of the sensing measurement parameter, and obtaining a quantization value corresponding to the corresponding element according to the quantization interval.

11. The method of claim 10, wherein, The first quantization range is determined based on a center reference point, the quantization granularity, and the number of quantization bits of the sensing measurement parameter.

12. The method of claim 10, wherein, The quantized perceptual measurement parameter satisfies the following equation: wherein x Q , y Q are two elements in the second vector, x, y are two elements included in the first vector, O x is an element in the center reference point corresponding to x, O y is an element in the center reference point corresponding to y, Δx is the quantization granularity corresponding to x, Δy is the quantization granularity corresponding to y, k is the quantization bit number of the perception measurement parameter, and k is a positive integer.

13. The method of claim 10, wherein, In a case that the perception measurement parameter comprises a position parameter, the position parameter is a first position vector, the perception area range comprises a plurality of areas, each of the plurality of areas corresponds to a reference point coordinate, the first quantization range comprises a plurality of second quantization ranges, and in a case that one area corresponds to one second quantization range, the second quantization range is determined based on the reference point coordinate of the corresponding area and the size of the corresponding area.

14. The method of claim 10, wherein, In a case that the first number of quantized values corresponds to one area, the perception measurement information further comprises an index of the area corresponding to the perception measurement parameter, and the first number is a number of quantized values of the perception measurement parameter determined based on the number of quantization bits.

15. The method of claim 13, wherein, The number of quantized values corresponding to each of the plurality of areas is the same or different.

16. The method of claim 13, wherein, A lower limit value of a value range corresponding to an element in the first position vector is determined based on a minimum value of a corresponding element in a plurality of reference point coordinates, and an upper limit value of the value range corresponding to the element in the first position vector is determined based on a maximum value of the corresponding element in the plurality of reference point coordinates.

17. An information transmission method applied to a perception network element, comprising: receiving perception measurement information sent by a wireless node, the perception measurement information comprising quantized perception measurement parameters, the quantized perception measurement parameters being obtained based on a first quantization range configured by the perception network element.

18. The method of claim 17, further comprising: sending perception configuration information to the wireless node, the perception configuration information being used to indicate at least one of the following: a quantization range of the perception measurement parameter, a quantization granularity of the perception measurement parameter, and a number of quantization bits of the perception measurement parameter.

19. The method of claim 18, further comprising: receiving perception capability information reported by the wireless node, the perception capability information comprising at least one of the following: a maximum range of perception measurement, a minimum granularity of perception measurement, a supported perception mode, a perception accuracy in each perception mode, a transceiving capability in each perception mode, and a resource configuration capability.

20. The method of claim 17, wherein, The perception measurement parameter comprises original measurement data or data processed based on the original measurement data.

21. The method of claim 17, wherein, The quantized perception measurement parameter is further quantized based on a quantization granularity of the perception measurement parameter and a number of quantization bits of the perception measurement parameter.

22. The method of claim 17, wherein, The quantized perception measurement parameter is obtained based on a quantization interval to which a value of the perception measurement parameter belongs, and the quantization interval is an interval obtained by dividing the first quantization range based on the quantization granularity of the perception measurement parameter.

23. The method of claim 22, wherein, In the case that the first quantization range comprises an upper limit value and a lower limit value, the quantized perceptual measurement parameter Q satisfies the following formula: or wherein S is the value of the perception measurement parameter, S0 is a lower limit value of the first quantization range, S1 is an upper limit value of the first quantization range, and Δ is the quantization granularity of the perception measurement parameter.

24. The method of claim 22, wherein, In case the absolute value of the value of the perceptual measurement parameter is attributed to the first quantization range, the quantized perceptual measurement parameter fulfils the following formula: wherein Q is the quantized perception measurement parameter, S is the value of the perception measurement parameter, S1 is the upper limit value of the first quantization range, S0 is the lower limit value of the first quantization range, Δ is the quantization granularity, k is the number of quantization bits, and k is a positive integer.

25. The method of claim 22, wherein, In the case where the first quantization range includes a quantization range greater than or equal to a lower limit value, the quantized perceptual measurement parameter satisfies the following formula: Q = floor (S / Δ), k = 0, 1, 2, …, kmax-1, wherein Q is the quantized perception measurement parameter, S is a value of the perception measurement parameter, S0 is a lower limit value of the first quantization range, Δ is a quantization granularity of the perception measurement parameter, k is a quantization bit number of the perception measurement parameter, and k is a positive integer.

26. The method of claim 22, wherein, The perception measurement parameter is a first vector, and the first quantization range includes a plurality of quantization ranges, and the first vector includes a plurality of elements corresponding to the plurality of quantization ranges. The quantized perception measurement parameter is a second vector obtained by performing quantization processing on each element of the plurality of elements included in the first vector, and the quantization processing includes: dividing a quantization range corresponding to an element in the first vector to obtain a quantization interval based on a quantization granularity of the perception measurement parameter, and obtaining a quantization value corresponding to the corresponding element according to the quantization interval.

27. The method of claim 26, wherein, The first quantization range is determined based on a center reference point, the quantization granularity, and the quantization bit number of the perception measurement parameter.

28. The method of claim 26, wherein, The quantized perceptual measurement parameter satisfies the following equation: wherein x Q , y Q are two elements in the second vector, x, y are two elements included in the first vector, O x is an element in the center reference point corresponding to x, O y is an element in the center reference point corresponding to y, Δx is the quantization granularity corresponding to x, Δy is the quantization granularity corresponding to y, k is the quantization bit number of the perception measurement parameter, and k is a positive integer.

29. The method of claim 26, wherein, In a case where the perception measurement parameter includes a position parameter, the position parameter is a first position vector, a perception area range includes a plurality of areas, each area of the plurality of areas corresponds to a reference point coordinate, and the first quantization range includes a plurality of second quantization ranges, in a case where one area corresponds to one second quantization range, the second quantization range is determined based on a reference point coordinate of the corresponding area and a size of the corresponding area.

30. The method of claim 26, wherein, In a case where a first number of quantization values corresponds to one area, the perception measurement information further includes an index of the area corresponding to the perception measurement parameter, and the first number is a number of quantization values of the perception measurement parameter determined based on the quantization bit number.

31. The method of claim 29, wherein, The number of quantization values corresponding to each area of the plurality of areas is the same or different.

32. The method of claim 29, wherein, A lower limit value of a value range corresponding to an element in the first position vector is determined based on a minimum value of the corresponding element in a plurality of reference point coordinates, and an upper limit value of the value range corresponding to the element in the first position vector is determined based on a maximum value of the corresponding element in the plurality of reference point coordinates.

33. An electronic device, comprising: A memory and a processor; wherein the memory is coupled with the processor; the memory is used to store instructions executable by the processor; and the processor executes the instructions to perform the method in any one of claims 1-32.

34. A computer readable storage medium, wherein, The computer readable storage medium stores computer instructions, and when the computer instructions run on a computer, the computer executes the method in any one of claims 1-32.

35. A computer program product, wherein, The computer program product includes computer program instructions, and the computer program instructions are executed by a processor to implement the method in any one of claims 1-32.

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