CN116436500A

CN116436500A - Channel data processing or de-processing method and device, terminal and network equipment

Info

Publication number: CN116436500A
Application number: CN202111679674.5A
Authority: CN
Inventors: 周化雨; 马大为; 陈咪咪; 潘振岗
Original assignee: Spreadtrum Communications Shanghai Co Ltd
Current assignee: Spreadtrum Communications Shanghai Co Ltd
Priority date: 2021-12-31
Filing date: 2021-12-31
Publication date: 2023-07-14
Also published as: WO2023125240A1

Abstract

The application discloses a channel data processing or anti-processing method and device, a terminal and network equipment; the method comprises the following steps: acquiring first channel data; processing the first channel data to obtain second channel data; correspondingly, acquiring second channel data; and carrying out inverse processing on the second channel data to obtain first channel data. In the process of directly feeding back (or reporting) channel data to the CSI feedback architecture through the AI model, in order to adapt the AI model for image processing, the situation that the AI model cannot process the channel data or the AI model is low in processing efficiency due to the fact that the elements in the channel data input into the AI model are out of range is avoided, and the terminal needs to process the acquired first channel data, so that the second channel data meets the requirements of the AI model adapted to image processing, and the AI model can successfully process the input second channel data or achieve higher processing efficiency.

Description

Channel data processing or de-processing method and device, terminal and network equipment

Technical Field

The present invention relates to the field of communications technologies, and in particular, to a method and apparatus for processing or de-processing channel data, a terminal, and a network device.

Background

In wireless communication system evolution, the use of artificial intelligence (artificial intelligence, AI) convergence with the physical layer has been explored. Among them, AI may include Machine Learning (ML), deep Learning (DL), and the like. Introducing AI into the physical layer algorithm can solve some problems which are difficult to solve by the traditional modeling method, such as some nonlinear problems, parameters which are too complex, and the like. The AI algorithm can bypass the traditional modeling approach and establish a solution to some problems through training of large amounts of data. With the maturation of AI algorithms and the maturation of hardware suitable for AI algorithms, the introduction of AI in physical layer algorithms is attracting more and more attention.

As a typical application, AI may be introduced in channel state information (Channel State Information, CSI) feedback. In the scenario of introducing AI in CSI feedback, the terminal may directly feedback (or report) the precoding matrix or channel data through an AI neural network (may be simply referred to as an AI model), i.e., the terminal directly feeds back the precoding matrix or channel matrix to the CSI feedback framework (including an overall feedback mechanism such as CQI, PMI, RI, CRI (or SSBRI)). The AI model may include convolutional neural networks (convolutional neural network, CNN), deep neural networks (deep neural network, DNN), and the like.

In some scenarios, the direct feedback precoding matrix or channel data has a larger amount of information than the codebook-based feedback, such as amplitude information (the eigenvectors have no amplitude information), is more suitable for multi-user multiple-input multiple-output (MU-MIMO), etc.

Since most AI models are used for image processing and the pixels in the image are one or a set of gray values, the image input to the AI model is a real number greater than or equal to zero. However, when a precoding matrix or a channel matrix estimated by a terminal through a reference signal, each element in the precoding matrix or the channel matrix may be complex-valued, and even though the precoding matrix or the channel matrix is divided into real part data and imaginary part data, elements within the real part data or the imaginary part data may still have positive or negative values. Therefore, in directly feeding back the precoding matrix or the channel matrix to the CSI feedback architecture through the AI model, in order to adapt the AI model for image processing, the channel data to be fed back (or reported) needs to be processed.

Disclosure of Invention

In a first aspect, a method for processing channel data according to the present application includes:

Acquiring first channel data;

and processing the first channel data to obtain second channel data.

Therefore, in the process of directly feeding back (or reporting) channel data to the CSI feedback architecture through the AI model, in order to adapt to the AI model for image processing, it is avoided that the AI model cannot process the channel data or the AI model is low in processing efficiency due to the existence of out-of-range elements in the channel data input to the AI model, and the terminal in the embodiment of the present application needs to process the channel data (i.e., the first channel data) to be fed back (or reported), so that the processed channel data (i.e., the second channel data) meets the requirements of the AI model adapted to image processing, thereby being beneficial to ensuring that the AI model can successfully process the input processed channel data or achieve higher processing efficiency.

In a second aspect, a method for back processing channel data according to the present application includes:

acquiring second channel data;

and carrying out inverse processing on the second channel data to obtain first channel data.

It can be seen that, in the process of directly feeding back channel data to the CSI feedback architecture through the AI model, since the terminal needs to process the fed back (or reported) channel data before feeding back (or reporting) in order to adapt to the AI model for image processing, when the network device acquires the processed channel data (i.e., the second channel data), the network device needs to process the processed channel data back to obtain the first channel data, so that the network device performs related operations through the first channel data, for example, the network device calculates the CQI through the first channel data, calculates the corresponding SINR through the first channel data, and the corresponding MCS through the MCS to schedule the terminal through the MCS, etc.

In a third aspect, the present application is a channel data processing apparatus, where the apparatus includes a processing unit, where the processing unit is configured to:

acquiring first channel data;

and processing the first channel data to obtain second channel data.

In a fourth aspect, the present application provides a channel data inverse processing apparatus, where the apparatus includes a processing unit, where the processing unit is configured to:

acquiring second channel data;

In a fifth aspect, the steps in the method designed in the first aspect are applied to a terminal.

In a sixth aspect, the steps in the method designed in the second aspect are applied in a network device.

A seventh aspect is a terminal of the present application, comprising a processor, a memory and a computer program or instructions stored on the memory, wherein the processor executes the computer program or instructions to implement the steps in the method designed in the first aspect.

An eighth aspect is a network device of the present application, comprising a processor, a memory and a computer program or instructions stored on the memory, wherein the processor executes the computer program or instructions to implement the steps in the method designed in the second aspect.

A ninth aspect is a chip of the present application, including a processor, where the processor performs the steps in the method designed in the first aspect or the second aspect.

In a tenth aspect, the present application is a chip module, including a transceiver component and a chip, where the chip includes a processor, and the processor executes the steps in the method designed in the first aspect or the second aspect.

An eleventh aspect is a computer readable storage medium according to the present application, where the computer readable storage medium has stored thereon a computer program or instructions, which when executed by a processor, implement the steps in the method designed in the first or second aspect.

A twelfth aspect is a computer program product of the present application, comprising a computer program or instructions which, when executed by a processor, implement the steps in the method devised in the first or second aspect described above.

Drawings

In order to more clearly illustrate the technical solutions in the embodiments of the present application, the drawings used in the description of the embodiments or the prior art will be briefly described below.

Fig. 1 is a schematic architecture diagram of a wireless communication system according to an embodiment of the present application;

FIG. 2 is a flow chart of a channel data processing and de-processing method according to an embodiment of the present application;

FIG. 3 is a block diagram of functional units of a channel data processing apparatus according to an embodiment of the present application;

fig. 4 is a functional unit block diagram of a channel data preprocessing device according to an embodiment of the present application;

fig. 5 is a schematic structural diagram of a terminal according to an embodiment of the present application;

fig. 6 is a schematic structural diagram of a network device according to an embodiment of the present application.

Detailed Description

In order to better understand the technical solutions of the present application, the following describes the technical solutions of the embodiments of the present application with reference to the drawings in the embodiments of the present application. It will be apparent that the embodiments described are some, but not all, of the embodiments of the present application. All other embodiments, which can be made by one of ordinary skill in the art without undue burden for the embodiments herein, are intended to be within the scope of the present application.

It should be understood that the terms "first," "second," and the like, as used in embodiments of the present application, are used for distinguishing between different objects and not for describing a particular sequential order. Furthermore, the terms "comprise" and "have," as well as any variations thereof, are intended to cover a non-exclusive inclusion. For example, a process, method, software, article, or apparatus that comprises a list of steps or elements is not limited to only those listed steps or elements but may include other steps or elements not listed or inherent to such process, method, article, or apparatus.

Reference in the specification to "an embodiment" means that a particular feature, structure, or characteristic described in connection with the embodiment may be included in at least one embodiment of the application. The appearances of such phrases in various places in the specification are not necessarily all referring to the same embodiment, nor are separate or alternative embodiments mutually exclusive of other embodiments. Those of skill in the art will explicitly and implicitly appreciate that the embodiments described herein may be combined with other embodiments.

The term "at least one" in the embodiments of the present application refers to one or more, and the term "a plurality" refers to two or more.

In the embodiment of the present application, "and/or" describes the association relationship of the association object, which indicates that three relationships may exist, for example, a and/or B may indicate the following three cases: a is present alone, while A and B are present together, and B is present alone. Wherein A, B can be singular or plural. The character "/" may indicate that the context-dependent object is an "or" relationship. In addition, the symbol "/" may also denote a divisor, i.e. performing a division operation.

The expression "at least one item(s)" or the like below in the embodiments of the present application refers to any combination of these items, including any combination of single item(s) or plural item(s). For example, at least one (one) of a, b or c may represent the following seven cases: a, b, c, a and b, a and c, b and c, a, b and c. Wherein each of a, b, c may be an element or a set comprising one or more elements.

It should be noted that, the "connection" in the embodiments of the present application refers to various connection manners such as direct connection or indirect connection, so as to implement communication between devices, which is not limited in any way. The "network" and the "system" appearing in the embodiments of the present application express the same concept, and the communication system is a communication network.

The technical solution of the embodiment of the present application may be applied to various wireless communication systems, for example: global system for mobile communications (Global System of Mobile communication, GSM), code division multiple access (Code Division Multiple Access, CDMA) system, wideband code division multiple access (Wideband Code Division Multiple Access, WCDMA) system, general packet Radio service (General Packet Radio Service, GPRS), long term evolution (Long Term Evolution, LTE) system, advanced long term evolution (Advanced Long Term Evolution, LTE-a) system, new Radio (NR) system, evolved system of NR system, LTE-based Access to Unlicensed Spectrum, LTE-U) system on unlicensed spectrum, NR (NR-based Access to Unlicensed Spectrum, NR-U) system on unlicensed spectrum, non-terrestrial communication network (Non-Terrestrial Networks, NTN) system, universal mobile communication system (Universal Mobile Telecommunication System, UMTS), wireless local area network (Wireless Local Area Networks, WLAN), wireless fidelity (Wireless Fidelity, wiFi), generation 6 (6 th-Generation, 6G) communication system, or other communication system, etc.

It should be noted that, the number of connections supported by the conventional wireless communication system is limited and easy to implement. However, with the development of communication technology, the wireless communication system may support not only a conventional wireless communication system but also, for example, a device-to-device (D2D) communication, a machine-to-machine (machine to machine, M2M) communication, a machine type communication (machine type communication, MTC), an inter-vehicle (vehicle to vehicle, V2V) communication, an internet of vehicles (vehicle to everything, V2X) communication, a narrowband internet of things (narrow band internet of things, NB-IoT) communication, and the like, and thus the technical solution of the embodiment of the present application may also be applied to the above wireless communication system.

Alternatively, the wireless communication system of the embodiment of the present application may be applied to beamforming (beamforming), carrier aggregation (carrier aggregation, CA), dual connectivity (dual connectivity, DC), or independent (SA) deployment scenarios, and the like.

Alternatively, the wireless communication system of the embodiments of the present application may be applied to unlicensed spectrum. Wherein unlicensed spectrum may also be considered shared spectrum. Alternatively, the wireless communication system in the present embodiment may be applied to licensed spectrum. Wherein licensed spectrum may also be considered as an unshared spectrum.

Since the embodiments of the present application describe various embodiments in connection with a terminal and a network device, the terminal and the network device involved will be specifically described below.

Specifically, the terminal may be a User Equipment (UE), a remote terminal (remote UE), a relay device (relay UE), an access terminal, a subscriber unit, a subscriber station, a mobile station, a remote station, a mobile device, a user terminal, a smart terminal, a wireless communication device, a user agent, or a user equipment. The relay device is a terminal capable of providing a relay service to other terminals (including a remote terminal). In addition, the terminal may also be a cellular phone, a cordless phone, a session initiation protocol (session initiation protocol, SIP) phone, a wireless local loop (wireless local loop, WLL) station, a personal digital assistant (personal digital assistant, PDA), a handheld device with wireless communication function, a computing device or other processing device connected to a wireless modem, an in-vehicle device, a wearable device, a terminal in a next generation communication system (e.g., NR communication system, 6G communication system) or a terminal in a future evolved public land mobile network (public land mobile network, PLMN), etc., without particular limitation.

Further, the terminal may be deployed on land, including indoors or outdoors, hand-held, wearable or vehicle-mounted; can be deployed on the water surface (such as ships, etc.); but also may be deployed in the air (e.g., aircraft, balloons, satellites, etc.).

Further, the terminal may be a mobile phone (mobile phone), a tablet computer (Pad), a computer with a wireless transceiving function, a Virtual Reality (VR) terminal device, an augmented reality (augmented reality, AR) terminal device, a wireless terminal device in industrial control (industrial control), a wireless terminal device in unmanned automatic driving, a wireless terminal device in remote medical (remote medical) treatment, a wireless terminal device in smart grid (smart grid), a wireless terminal device in transportation security (transportation safety), a wireless terminal device in smart city (smart city), or a wireless terminal device in smart home (smart home), etc.

In particular, the network device may be a device for communication with the terminal, which is responsible for radio resource management (radio resource management, RRM) on the air interface side, quality of service (quality of service, qoS) management, data compression and encryption, data transceiving, and the like. The network device may be a Base Station (BS) in a communication system or a device deployed in a radio access network (radio access network, RAN) for providing wireless communication functions. For example, a base station (base transceiver station, BTS) in a GSM or CDMA communication system, a Node B (NB) in a WCDMA communication system, an evolved node B (evolutional node B, eNB or eNodeB) in an LTE communication system, a next generation evolved node B (next generation evolved node B, ng-eNB) in an NR communication system, a next generation node B (next generation node B, gNB) in an NR communication system, a Master Node (MN) in a dual-link architecture, a second node or Secondary Node (SN) in a dual-link architecture, and the like are not particularly limited thereto.

Further, the network device may be other devices in a Core Network (CN), such as an access and mobility management function (access and mobility management function, AMF), a user planning function (user plan function, UPF), etc.; but also Access Points (APs) in a wireless local area network (wireless local area network, WLAN), relay stations, communication devices in a future evolved PLMN network, communication devices in an NTN network, etc.

Further, the network device may comprise means, such as a system-on-chip, with the capability to provide wireless communication for the terminal. By way of example, the system-on-chip may include a chip, and may include other discrete devices.

Further, the network device may communicate with an internet protocol (Internet Protocol, IP) network. Such as the internet, a private IP network or other data network, etc.

It should be noted that in some network deployments, the network device may be a separate node to implement all the functions of the base station, which may include a Centralized Unit (CU) and a Distributed Unit (DU), such as a gNB-CU and a gNB-DU; an active antenna unit (active antenna unit, AAU) may also be included. Wherein a CU may implement part of the functionality of the network device and a DU may also implement part of the functionality of the network device. For example, a CU is responsible for handling non-real-time protocols and services, implementing the functions of a radio resource control (radio resource control, RRC) layer, a service data adaptation (service data adaptation protocol, SDAP) layer, and a packet data convergence (packet data convergence protocol, PDCP) layer. The DUs are responsible for handling physical layer protocols and real-time services, implementing the functions of the radio link control (radio link control, RLC), medium access control (medium access control, MAC) and Physical (PHY) layers. In addition, the AAU can realize partial physical layer processing function, radio frequency processing and related functions of the active antenna. Since the information of the RRC layer eventually becomes or is converted from the information of the PHY layer, in this network deployment, higher layer signaling (e.g., RRC layer signaling) may be considered to be transmitted by the DU or transmitted by both the DU and the AAU. It is understood that the network device may include at least one of CU, DU, AAU. In addition, the CU may be divided into network devices in an access network (radio access network, RAN), or may be divided into network devices in a core network, which is not particularly limited.

Further, the network device may have a mobile nature, e.g., the network device may be a mobile device. Alternatively, the network device may be a satellite, a balloon station. For example, the satellite may be a Low Earth Orbit (LEO) satellite, a medium earth orbit (medium earth orbit, MEO) satellite, a geosynchronous orbit (geostationary earth orbit, GEO) satellite, a high elliptical orbit (high elliptical orbit, HEO) satellite, or the like. Alternatively, the network device may be a base station disposed on land, in a water area, or the like.

Further, the network device may serve a cell, and terminals within the cell may communicate with the network device via transmission resources (e.g., spectrum resources). The cells may include macro cells (macro cells), small cells (small cells), urban cells (metro cells), micro cells (micro cells), pico cells (pico cells), femto cells (femto cells), and the like.

In connection with the above description, an exemplary description of a wireless communication system according to an embodiment of the present application is provided below.

Exemplary, the wireless communication system of the embodiments of the present application, please refer to fig. 1. Wireless communication system 10 may include network device 110 and terminal 120, and network device 110 may be a device that performs communication with terminal 120. At the same time, network device 110 may provide communication coverage for a particular geographic area and may communicate with terminals 120 located within that coverage area.

Optionally, the wireless communication system 10 may further include a plurality of network devices, and each network device may include a certain number of terminals within a coverage area thereof, which is not specifically limited herein.

Optionally, the wireless communication system 10 may further include a network controller, a mobility management entity, and other network entities, which are not specifically limited herein.

Alternatively, the communication between the network device and the terminal in the wireless communication system 10, and between the terminal and the terminal may be wireless communication or wired communication, and is not particularly limited herein.

The following describes relevant matters related to the embodiments of the present application.

1. Multiple input multiple output (Multiple Input Multiple Output, MIMO)

The MIMO technology has the advantages of high frequency spectrum efficiency, large system capacity and the like. Wherein, the MIMO signal model can be expressed as:

r＝Hs+n；

wherein r represents a received signal vector; h represents a channel matrix for the MIMO channel; s represents a transmission signal vector; n represents an additive noise vector.

In the precoding system, the transmitter can optimize the spatial characteristics of the transmission signals according to the channel matrix, so that the spatial distribution characteristics of the transmission signals are matched with the channel matrix, and the dependence on the receiver algorithm can be effectively reduced.

The precoding may employ linear or nonlinear methods. For reasons of complexity, etc., only linear precoding is generally considered in current wireless communication systems. After precoding, the MIMO signal model can be expressed as:

r＝HWs+n；

where W represents the precoding matrix.

2. Channel state information (Channel State Information, CSI) feedback (feedback) or reporting (report)

Protocol standards set by the third generation partnership project (3rd generation partnership project,3GPP) have been studied for channel state information (Channel State Information, CSI). The CSI is channel state information that the terminal is configured to feed back downlink channel quality to the network device, so that the network device selects an appropriate modulation and coding strategy (modulation and coding Scheme, MCS) for downlink data transmission, reduces a block error rate (BLER) of downlink data transmission, and performs corresponding beam management, mobility management, adaptation tracking, rate matching, and other processes.

The CSI feedback may include at least one of a channel state information reference signal resource indicator (CSIreference signalresource indicator, CRI), a Rank Indicator (RI), a precoding matrix indicator (precoding matrix indicator, PMI), a channel quality indicator (channel quality indicator, CQI), a synchronization signal block resource indicator (SS/PBCH block resource indicator, SSBRI), a Layer Indicator (LI), and the like.

CRI (or SSBRI) may represent a set of CSI-RS (or SSB) resources recommended (or selected) by a terminal. Wherein one CSI-RS (or SSB) resource set may represent one beam or antenna direction.

The CQI may represent how good the terminal feeds back the current radio channel quality to the network device. The terminal needs to calculate the CQI and report the maximum CQI index. The CQI index may cause the terminal to receive a PDSCH transport block with a modulation format, target code rate, and transport block size at a block error rate (transport block error probability) of no more than 0.1, the PDSCH transport block corresponding to the CQI index and occupying CSI reference resources.

The RI may represent the number of layers recommended (or selected) by the terminal, and the number of layers may determine which codebook. Wherein each layer number corresponds to a codebook, and a codebook is composed of one or more codewords. For example, a codebook with a layer number of 2 or a codebook with a layer number of 1. In addition, in the MIMO technology, the number of layers may be used to represent the number of transmission links between a transmitting end and a receiving end.

The PMI may represent an index of a codeword in a codebook recommended (or selected) by the terminal. Wherein one codeword corresponds to one precoding matrix. The RI and PMI may collectively represent the number of layers and precoding matrix recommended by the UE.

The terminal may perform downlink channel estimation/measurement according to a downlink reference signal (e.g., CSI-RS) to obtain a channel matrix. In codebook-based precoding, the terminal may select the precoding matrix from the codebook that best matches the channel matrix according to some optimization criterion, and feed back its index to the network device through a feedback link. Meanwhile, the terminal can calculate the channel quality after using the PMI according to the recommended PMI and report the CQI. In the process of calculating the PMI and the CQI, the terminal needs to consider the self receiving processing algorithm.

In the downlink transmission process, the network device uses the PMI reported by the terminal as a reference to pre-encode data. When the precoding matrix used by the network device in the downlink is inconsistent with the PMI reported by the terminal, in order to ensure that the terminal can acquire the equivalent channel after precoding and coherently demodulate the downlink data, the network device needs to indicate the precoding matrix adopted by the network device in the downlink control information (downlink control information, DCI).

The number of layers and the precoding matrix recommended (or selected) by the terminal reflect the eigenvectors of the channel matrix. Thus, the terminal can derive the number of layers and the precoding matrix through the channel matrix.

In addition, when the terminal calculates the CQI, a PMI/RI combination can be selected to correspond to a precoding matrix. Under the assumption of the precoding matrix, the terminal needs to calculate the current signal-to-interference-and-noise ratio (signal to interference and noise ratio, SINR) from the estimated channel matrix, the covariance matrix of the interference noise. The SINR may also be referred to as post-equalizer SINR (post-equalizer SINR) because its corresponding SINR calculation takes into account the effects of the equalizer, which may also be referred to as a MIMO receiver.

Alternatively, under the assumption of the precoding matrix, the terminal needs to calculate the current SINR through the estimated channel matrix, covariance matrix of interference noise, and decoder. This SINR may also be referred to as post-decoder SINR (post-decoder SINR) because its corresponding SINR calculation takes into account the effects of the equalizer and decoder.

Thus, the CQI calculated by the terminal according to the selected (or recommended) PMI, RI and CRI (or SSBRI) will likely correspond to one SINR. Meanwhile, the terminal may feed back (or report) the calculated CQI to the network device.

The network device can reversely push the SINR after obtaining the CQI, and can process the SINR according to the PMI and the RI (corresponding to the precoding matrix) reported by the terminal (or independently selected) and process the SINR in the downlink transmission, for example, the network device can increase or decrease the SINR in an empirical mode, and select a proper modulation coding format to schedule the terminal.

3. CSI feedback and artificial intelligence (artificial intelligence, AI)

In wireless communication system evolution, the use of artificial intelligence in combination with physical layers has been explored. Among them, AI may include Machine Learning (ML), deep Learning (DL), and the like. Introducing AI into the physical layer algorithm can solve some problems which are difficult to solve by the traditional modeling method, such as some nonlinear problems, parameters which are too complex, and the like. The AI algorithm can bypass the traditional modeling approach and establish a solution to some problems through training of large amounts of data. With the maturation of AI algorithms and the maturation of hardware suitable for AI algorithms, the introduction of AI in physical layer algorithms is attracting more and more attention.

As a typical application, AI may be introduced in CSI feedback. In the scenario of introducing AI in CSI feedback, the terminal may directly feedback (or report) the precoding matrix or the channel matrix through an AI neural network (may be simply referred to as an AI model), that is, the terminal directly feeds back the precoding matrix or the channel matrix to the CSI feedback framework (including an overall feedback mechanism such as CQI, PMI, RI, CRI (or SSBRI)). The AI model may include convolutional neural networks, deep neural networks, and the like.

In some scenarios, the direct feedback precoding matrix or channel matrix has a larger amount of information than the codebook-based feedback, such as amplitude information (eigenvectors have no amplitude information), is more suitable for multi-user multiple-input multiple-output (MU-MIMO), etc.

In the process of directly feeding back a precoding matrix or a channel matrix to a CSI feedback architecture through an AI model, the precoding matrix or the channel matrix is processed at a terminal side, and then the terminal side inputs the AI model for compression, quantization and coding to obtain coding information;

on the network equipment side, the encoded information is decoded and dequantized, then input into an AI model for decompression, and then processed to obtain a precoding matrix or a channel matrix.

In addition, the precoding matrix or the channel matrix in the embodiments of the present application may be a precoding matrix or a channel matrix before compression, or may be a precoding matrix or a channel matrix after decompression, which is not limited in particular.

Since most AI models are used for image processing and the pixels in the image are one or a set of gray values, the image input to the AI model is a real number greater than or equal to zero. However, when a precoding matrix or a channel matrix estimated by a terminal through a reference signal, each element of the precoding matrix or the channel matrix may be complex-valued, and even though the precoding matrix or the channel matrix is divided into a real part and an imaginary part, the real part or the imaginary part may still have a positive or a negative. Therefore, in directly feeding back the precoding matrix or the channel matrix to the CSI feedback architecture through the AI model, in order to adapt the AI model for image processing, the precoding matrix or the channel matrix to be fed back (or reported) needs to be processed.

The following describes in detail the channel data processing and inverse processing method according to the embodiments of the present application with reference to the accompanying drawings.

Fig. 2 is a schematic flow chart of a channel data processing and de-processing method according to an embodiment of the present application, including the following steps:

s210, the terminal acquires the first channel data.

It should be noted that, in the embodiment of the present application, the channel data may be a precoding matrix or a channel matrix itself, or may be data after the channel matrix or the precoding matrix is processed, for example, data after the channel matrix or the precoding matrix is sequenced, etc.

S220, the terminal processes the first channel data to obtain second channel data.

S230, the network equipment acquires second channel data.

S240, the network equipment carries out inverse processing on the second channel data to obtain first channel data.

It should be noted that, in the embodiments of the present application, a scenario of introducing AI in CSI feedback needs to be analyzed. Therefore, the terminal may directly feed back (or report) the precoding matrix or the channel matrix through the AI model instead of the codebook-based feedback.

Since most AI models are used for image processing and the pixels in the image are one or a set of gray values, the image input to the AI model is a real number greater than or equal to zero. However, when the terminal estimates channel data by the reference signal, each element in the channel data may be complex-valued.

In one way, the channel data may be divided into real and imaginary data, with elements within the real or imaginary data still possibly being positive or negative.

Alternatively, the channel data may be divided into amplitude data and phase data, the elements within the amplitude data or phase data still possibly being positive or negative.

In the process of directly feeding back (or reporting) channel data to the CSI feedback architecture through the AI model, in order to adapt the AI model for image processing, the problem that the AI model cannot process the channel data or the AI model is low in processing efficiency due to the fact that the elements in the channel data input to the AI model are out of range is avoided.

For example, a possible flow for a terminal to directly feed back (or report) channel data through the AI model is described as follows:

Firstly, a terminal can perform downlink channel estimation/measurement through downlink signals (such as CSI-RS, SSB or PBCH DMRS and the like) to obtain first channel data, and then process the first channel data to obtain second channel data;

secondly, the terminal inputs the second channel data into an AI model to obtain compression information corresponding to the second channel data;

then, the terminal sends the compressed information to a quantizer and an encoder, and sends the compressed information to the network device through a Channel State Information (CSI) feedback (or reporting) process on a physical uplink channel (such as a Physical Uplink Shared Channel (PUSCH) and a Physical Uplink Control Channel (PUCCH)) after the quantization and the encoding are completed;

finally, the network device decodes, dequantizes and inputs the AI model to obtain second channel data through the reverse flow, and then carries out inverse processing on the second channel data to obtain first channel data, so that the network device can execute related operations through the first channel data, for example, the network device calculates CQI through the first channel data, calculates corresponding SINR and corresponding MCS through the first channel data, so as to schedule the terminal through the MCS, and the like.

In summary, in the process of directly feeding back channel data to the CSI feedback architecture through the AI model, the terminal needs to process the channel data to be fed back (or reported), and the network device needs to process the obtained processed channel data. The manner of how the first channel data is processed and how the second channel data is processed in reverse is described in detail below.

Mode one:

because at least one of the element in the first channel data, the real part of the element in the first channel data, and the imaginary part of the element in the first channel data may be less than or equal to a preset value (e.g., zero), the embodiment of the present application may perform the translation processing on the real part of the element and/or the imaginary part of the element, the amplitude of the element, and/or the phase of the element, so that the real part of the element and/or the imaginary part of the element may be greater than or equal to a preset value (e.g., zero), so as to be beneficial to ensure that the AI model is successfully processed when the AI model is input to the AI model for processing.

For the terminal, the terminal needs to subtract the shift amount from at least one of the element in the first channel data, the real part of the element in the first channel data, the imaginary part of the element in the first channel data, the amplitude of the element in the first channel data, and the phase of the element in the first channel data.

It will be appreciated that there may be the following ways for the terminal:

1) The terminal subtracts the translation amount from the elements in the first channel data; the translation amount is used for carrying out translation processing on elements in the first channel data so that the elements are larger than or equal to a preset value;

2) The terminal subtracts the shift amount from the real part of the element in the first channel data; the translation amount is used for carrying out translation processing on the real part of the element in the first channel data so as to be larger than or equal to a preset value;

3) The terminal subtracts the shift amount from the imaginary part of the element in the first channel data; the shift amount is used for carrying out shift processing on the imaginary part of the element in the first channel data so as to be larger than or equal to a preset value;

4) The terminal subtracts the shift amount from the real part and the imaginary part of the element in the first channel data; the translation amount is used for carrying out translation processing on the real part and the imaginary part of the element in the first channel data so as to be larger than or equal to a preset value;

5) The terminal subtracts the translation amount from the amplitude of the element in the first channel data; the translation amount is used for carrying out translation processing on the amplitude of the element in the first channel data so as to be larger than or equal to a preset value;

6) The terminal subtracts the shift amount from the phase of the element in the first channel data; the shift amount is used for carrying out shift processing on the phases of elements in the first channel data so as to be larger than or equal to a preset value;

7) The terminal subtracts the shift amount from the real part and the imaginary part of the element in the first channel data; the translation amount is used for carrying out translation processing on the amplitude and the phase of the element in the first channel data so as to be larger than or equal to a preset value;

Etc.; this is not particularly limited.

For the network device, the network device needs to add a shift amount to at least one of the element in the second channel data, the real part of the element in the second channel data, the imaginary part of the element in the second channel data, the amplitude of the element in the second channel data, the phase of the element in the second channel data.

It will be appreciated that there may be the following ways for a network device:

1) The network device adds a translation amount to the elements in the second channel data; the translation amount is used for carrying out translation processing on elements in the first channel data so that the elements are larger than or equal to a preset value;

2) The network device adding a translation amount to the real part of the element within the second channel data; the translation amount is used for carrying out translation processing on the real part of the element in the first channel data so as to be larger than or equal to a preset value;

3) The network device adds a shift amount to the imaginary part of the element in the second channel data; the shift amount is used for carrying out shift processing on the imaginary part of the element in the first channel data so as to be larger than or equal to a preset value;

4) The network device adds a shift amount to the real part and the imaginary part of the element in the second channel data; the translation amount is used for carrying out translation processing on the real part and the imaginary part of the element in the first channel data so as to be larger than or equal to a preset value;

5) The network device adds a translation amount to the amplitude of the element within the second channel data; the translation amount is used for carrying out translation processing on the amplitude of the element in the first channel data so as to be larger than or equal to a preset value;

6) The network device adds a shift amount to the phase of the element in the second channel data; the shift amount is used for carrying out shift processing on the phases of elements in the first channel data so as to be larger than or equal to a preset value;

7) The network device adds a shift amount to the amplitude and phase of the elements within the second channel data; the translation amount is used for carrying out translation processing on the real part and the imaginary part of the element in the first channel data so as to be larger than or equal to a preset value;

etc.; this is not particularly limited.

In addition, for translational amounts, embodiments of the present application may exist as follows:

1) The translation amount may be m;

wherein the m may be used to represent a minimum value of at least one of all elements within the first channel data, a modulus of all elements within the first channel data, a real part of all elements within the first channel data, an imaginary part of all elements within the first channel data, an amplitude of all elements within the first channel data, and a phase of all elements within the first channel data.

For example, the terminal may subtract the minimum value of all elements in the first channel rectangle from the element to be greater than or equal to a preset value. For the network device, the network device needs to add the minimum value in all the elements in the first channel rectangle to the elements of the second channel data to ensure that the first channel data is recovered.

Similarly, the terminal may subtract the minimum value in the modulus of all the elements in the first channel rectangle from the element to be greater than or equal to a preset value.

Whereas for a network device, the network device needs to add the minimum value in the modulus of all elements within the first channel rectangle to the elements of the second channel data to ensure that the first channel data is recovered. The modulus of an element is a measure of the element, including, but not limited to, amplitude value, phase value, power value, maximum absolute value of real part and imaginary part, and the like.

Similarly, the terminal may subtract the minimum value of the real parts of all the elements in the first channel rectangle from the real part of the element to be greater than or equal to a preset value. Whereas for a network device, the network device needs to add the minimum of the real parts of the elements of the second channel data to the real parts of all elements within the first channel rectangle to ensure that the first channel data is recovered.

Similarly, the terminal may subtract the minimum value in the imaginary parts of all the elements in the first channel rectangle from the imaginary part of the element to make it greater than or equal to a preset value. For the network device, the minimum value of the imaginary parts of all the elements in the first channel rectangle is added to the imaginary parts of the elements of the second channel data, so as to ensure that the first channel data is recovered.

Similarly, the terminal may subtract the minimum value of the magnitudes of all the elements in the first channel rectangle from the real part of the element to be greater than or equal to a preset value. Whereas for a network device, the network device needs to add the minimum of the magnitudes of the elements of the second channel data to the magnitudes of all the elements within the first channel rectangle to ensure that the first channel data is recovered.

Similarly, the terminal may subtract the minimum value of the phases of all the elements in the first channel rectangle from the imaginary part of the element to be greater than or equal to a preset value. For the network device, the network device needs to add the minimum value of the phases of all the elements in the first channel rectangle to the phase of the elements of the second channel data to ensure that the first channel data is recovered.

2) The translation amount may be a quantized value of m;

It should be noted that, based on the above description, since the first channel data acquired by the terminal may be subjected to quantization processing before being input into the AI model, elements in the first channel data, real parts of the elements in the first channel data, and/or imaginary parts of the elements in the first channel data, amplitudes of the elements in the first channel data, and/or phases of the elements in the first channel data may be subjected to quantization processing, the amount of translation used when the first channel data is subjected to translation processing needs to be subjected to quantization processing in order to improve processing accuracy.

In addition, for the terminal, in order to implement that the terminal processes the first channel data with a shift amount to obtain the second channel data, in the case that the terminal performs downlink channel estimation/measurement according to a downlink signal (such as CSI-RS, SSB, or PBCH DMRS, etc.) to obtain the first channel data, the terminal may directly obtain the shift amount from a minimum value of at least one of all elements, modes of all elements, real parts of all elements, imaginary parts of all elements, amplitudes of all elements, and phases of all elements in the first channel data.

For the network device, in order to implement that the network device performs inverse processing on the second channel data by using the translation amount to obtain the first channel data, the terminal may report (or feed back) the translation amount to the network device while reporting (or feeding back) the second signal matrix to the network device. For example, the terminal reports the second channel data and the shift amount through a CSI feedback (or reporting) process.

Mode two:

because at least one of the element in the first channel data, the real part of the element in the first channel data, the imaginary part of the element in the first channel data, the amplitude of the element in the first channel data, and the phase of the element in the first channel data may be greater than or equal to a preset threshold (these may be translated as described above, or may not be translated as described above), the embodiments of the present application may perform scaling processing on the real part of the element and/or the imaginary part of the element, the amplitude of the element, and/or the phase of the element so that the real part of the element and/or the imaginary part of the element, the amplitude of the element are greater than or equal to a preset threshold, so as to be beneficial to improving the processing efficiency of the AI model when the AI model is input for processing.

The preset threshold may be configured by a network device, preconfigured, specified by a protocol, etc., which is not particularly limited. For example, the preset threshold may be 1.

For the terminal, dividing at least one of an element in the first channel data, a real part of the element in the first channel data, an imaginary part of the element in the first channel data, an amplitude of the element in the first channel data, and a phase of the element in the first channel data by a stretch amount.

It will be appreciated that there may be the following ways for the terminal:

1) The terminal divides elements in the first channel data by the expansion amount; the expansion and contraction amount is used for carrying out expansion and contraction processing on elements in the first channel data so that the value is smaller than a preset threshold;

2) The terminal divides the real part of the element in the first channel data by the expansion amount; the method comprises the steps that the expansion and contraction amount is used for carrying out expansion and contraction processing on the real part of an element in first channel data so that the real part of the element in the first channel data is smaller than or equal to a preset threshold;

3) Dividing the imaginary part of the element in the first channel data by the expansion amount by the terminal; the method comprises the steps of performing expansion and contraction processing on an imaginary part of an element in first channel data to enable the imaginary part to be smaller than or equal to a preset threshold;

4) Dividing the real part and the imaginary part of the element in the first channel data by the expansion amount by the terminal; the method comprises the steps that the expansion quantity is used for carrying out expansion processing on the real part and the imaginary part of an element in first channel data so as to be smaller than or equal to a preset threshold;

5) The terminal divides the amplitude of the element in the first channel data by the expansion and contraction amount; the method comprises the steps of performing expansion and contraction processing on the amplitude of elements in first channel data to enable the amplitude to be smaller than or equal to a preset threshold;

6) The terminal divides the phase of the element in the first channel data by the expansion and contraction amount; the method comprises the steps of performing expansion and contraction processing on phases of elements in first channel data to enable the phases to be smaller than or equal to a preset threshold;

7) The terminal divides the amplitude and the phase of the elements in the first channel data by the expansion and contraction amount; the method comprises the steps of performing scaling processing on the amplitude and the phase of elements in first channel data to enable the amplitude and the phase to be smaller than or equal to a preset threshold;

etc.; this is not particularly limited.

For the network device, the network device needs to multiply at least one of an element in the second channel data, a real part of the element in the second channel data, an imaginary part of the element in the second channel data, an amplitude of the element in the second channel data, and a phase of the element in the second channel data by a stretching amount.

It will be appreciated that there may be the following ways for the terminal:

1) The network device multiplies the element in the first channel data by the expansion amount; the expansion and contraction amount is used for carrying out expansion and contraction processing on elements in the first channel data so that the expansion and contraction amount is smaller than or equal to a preset threshold;

2) The network device multiplies the real part of the element in the first channel data by the amount of scalability; the method comprises the steps that the expansion and contraction amount is used for carrying out expansion and contraction processing on the real part of an element in first channel data so that the real part of the element in the first channel data is smaller than or equal to a preset threshold;

3) The network device multiplies the imaginary part of the element in the first channel data by the amount of stretch; the method comprises the steps of performing expansion and contraction processing on an imaginary part of an element in first channel data to enable the imaginary part to be smaller than or equal to a preset threshold;

4) The network device multiplies the real part and the imaginary part of the element in the first channel data by the expansion amount; the method comprises the steps that the expansion quantity is used for carrying out expansion processing on the real part and the imaginary part of an element in first channel data so as to be smaller than or equal to a preset threshold;

5) The network device multiplies the amplitude of the element in the first channel data by the expansion amount; the method comprises the steps of performing expansion and contraction processing on the amplitude of elements in first channel data to enable the amplitude to be smaller than or equal to a preset threshold;

6) The network device multiplies the phase of the element in the first channel data by the amount of scalability; the method comprises the steps of performing expansion and contraction processing on phases of elements in first channel data to enable the phases to be smaller than or equal to a preset threshold;

7) The network device multiplies the amplitude and the phase of the element in the first channel data by the expansion amount; the method comprises the steps of performing scaling processing on the amplitude and the phase of elements in first channel data to enable the amplitude and the phase to be smaller than or equal to a preset threshold;

etc.; this is not particularly limited.

For the amount of telescoping, embodiments of the present application may exist as follows:

1) The amount of telescoping may be the difference between M and M.

Wherein the M may be used to represent a maximum value of at least one of all elements within the first channel data, a modulus of all elements within the first channel data, a real part of all elements within the first channel data, an imaginary part of all elements within the first channel data, an amplitude of all elements within the first channel data, a phase of all elements within the first channel data; the m may be used to represent a minimum value of at least one of all elements within the first channel data, a modulus of all elements within the first channel data, a real part of all elements within the first channel data, an imaginary part of all elements within the first channel data, an amplitude of all elements within the first channel data, and a phase of all elements within the first channel data.

For example, the terminal may divide the element by the difference between the maximum value and the minimum value among all the elements within the first channel rectangle to be less than or equal to a preset threshold. For the network device, the network device needs to multiply the element of the second channel data by the difference between the maximum value and the minimum value in all the elements in the first channel rectangle to ensure that the first channel data is recovered.

Similarly, the terminal may divide the element by the difference between the maximum value and the minimum value in the modes of all the elements in the first channel rectangle to be less than or equal to a preset threshold. For the network device, the network device needs to multiply the element of the corresponding second channel data by the difference between the maximum value and the minimum value in the modes of all the elements in the first channel rectangle to ensure that the first channel data is recovered.

Similarly, the terminal may divide the real part of the element by the difference between the maximum value and the minimum value of the real parts of all elements in the first channel rectangle to be less than or equal to a preset threshold. For the network device, the network device needs to multiply the real parts of the elements of the corresponding second channel data by the difference between the maximum and minimum values of the real parts of all the elements in the first channel rectangle to ensure that the first channel data is recovered.

Similarly, the terminal may divide the imaginary part of the element by the difference between the maximum value and the minimum value in the imaginary parts of all elements in the first channel rectangle to be less than or equal to a preset threshold. For the network device, the network device needs to multiply the imaginary parts of the elements of the corresponding second channel data by the difference between the maximum value and the minimum value in the imaginary parts of all the elements in the first channel rectangle to ensure that the first channel data is recovered.

Similarly, the terminal may divide the amplitude of the element by the difference between the maximum value and the minimum value of the amplitudes of all the elements in the first channel rectangle to be less than or equal to a preset threshold. For the network device, the network device needs to multiply the amplitude of the element of the second channel data by the difference between the maximum value and the minimum value of the amplitudes of all the elements in the first channel rectangle to ensure that the first channel data is recovered.

Similarly, the terminal may divide the phase of the element by the difference between the maximum value and the minimum value of the phases of all the elements in the first channel rectangle to be less than or equal to a preset threshold. For the network device, the network device needs to multiply the phase of the element of the second channel data by the difference between the maximum value and the minimum value of the phases of all the elements in the first channel rectangle to ensure that the first channel data is recovered.

2) The amount of scaling may be a quantized value of the difference between M and M.

It should be noted that, based on the above description, since the first channel data acquired by the terminal may undergo quantization processing before the AI model is input, elements in the first channel data, real parts of the elements in the first channel data and/or imaginary parts of the elements in the first channel data, amplitudes of the elements in the first channel data and/or phases of the elements in the first channel data may undergo quantization processing, and thus the amount of translation used when the first channel data is subjected to expansion and contraction processing needs to undergo quantization processing in order to improve processing accuracy.

3) The amount of scaling may be one of a norm of the first channel data, an average of power of all elements within the first channel data, and an average of squares of all elements within the first channel data.

For example, the terminal may divide the element by a norm of the first channel data to have a value less than a preset threshold. For the network device, the network device needs to multiply the elements of the second channel matrix by the norms of the first channel data to ensure that the first channel data is recovered.

Similarly, the terminal may divide the element by the average value of the powers of all the elements in the first channel data, so that the value thereof is smaller than a preset threshold. For the network device, the network device needs to multiply the elements of the second channel data by the average of the power of all the elements within the first channel data to ensure that the first channel data is recovered.

Similarly, the terminal may divide the element by the average of the squares of all the modes of all the elements in the first channel data to have an amplitude less than the predetermined threshold. For the network device, the network device needs to multiply the elements of the second channel data by the average of the squares of the modes of all elements within the first channel data to ensure that the first channel data is recovered.

4) The scaling amount is one of reference signal received power RSRP, reference signal received quality RSRQ, and reference signal strength indication RSSI.

It should be noted that one of RSRP, RSRQ, RSSI may be obtained by the terminal performing downlink channel estimation/measurement from a downlink reference signal (e.g., CSI-RS).

In addition, for the terminal, in order to implement that the terminal processes the first channel data with the amount of scaling to obtain the second channel data, in the case that the terminal performs downlink channel estimation/measurement according to a downlink reference signal (e.g., CSI-RS) to obtain the first channel data, the terminal may directly obtain the amount of scaling from within a maximum value and a minimum value of at least one of all elements, real parts of all elements, imaginary parts of all elements, amplitudes of all elements, phases of all elements in the first channel data, or from one of a norm of the first channel data, an average value of power of all elements in the first channel data, an average value of a square of a modulus of all elements in the first channel data, or from one of RSRP, RSRQ, RSSI that the downlink reference signal performs downlink channel estimation/measurement to obtain.

For the network device, in order to implement that the network device performs inverse processing on the second channel data by using the scaling amount to obtain the first channel data, the terminal may report (or feed back) the second signal matrix to the network device and at the same time report the scaling amount to the network device. For example, the terminal reports the second channel data and the shift amount through a CSI feedback (or reporting) process.

Mode three:

as can be seen from the above-mentioned "first mode" and "second mode", since at least one of the element in the first channel data, the real part of the element in the first channel data, the imaginary part of the element in the first channel data, the amplitude of the element in the first channel data, and the phase of the element in the first channel data may have a value less than or equal to a preset value (e.g., zero), the embodiment of the present application may perform the translation processing on the real part of the element and/or the imaginary part of the element, the amplitude of the element, and/or the phase of the element to make the real part of the element and/or the imaginary part of the element greater than or equal to a preset value, and then perform the expansion processing to make the real part of the element and the phase of the element less than or equal to a preset threshold, thereby not only being beneficial to ensuring successful processing of the AI model when the AI model is input to perform the processing, but also beneficial to improving the processing efficiency of the AI model.

For the terminal, the shift amount is subtracted from at least one of the element in the first channel data, the real part of the element in the first channel data, the imaginary part of the element in the first channel data, the amplitude of the element in the first channel data, and the phase of the element in the first channel data, and divided by the stretch amount.

It will be appreciated that there may be the following ways for the terminal:

1) The terminal subtracts the translation amount from the elements in the first channel data and divides the translation amount by the expansion amount; the translation amount is used for carrying out translation processing on elements in the first channel data so that the elements are larger than or equal to a preset value; the expansion and contraction amount is used for carrying out expansion and contraction processing on elements in the first channel data so as to be smaller than or equal to a preset threshold;

2) The terminal subtracts the translation amount from the real part of the element in the first channel data and divides the translation amount by the expansion amount; the translation amount is used for carrying out translation processing on the real part of the element in the first channel data so as to be larger than or equal to a preset value; the scaling amount is used for scaling the real part of the element in the first channel data so as to be smaller than or equal to a preset threshold;

3) The terminal subtracts the translation amount from the imaginary part of the element in the first channel data and divides the translation amount by the expansion amount; the translation amount is used for carrying out translation processing on at least one of the imaginary parts of the elements in the first channel data so as to be larger than or equal to a preset value; the expansion and contraction amount is used for carrying out expansion and contraction processing on the imaginary parts of elements in the first channel data so as to be smaller than or equal to a preset threshold;

4) The terminal subtracts the translation amount from the real part and the imaginary part of the element in the first channel data and divides the translation amount by the expansion amount; the translation amount is used for carrying out translation processing on the real part and the imaginary part of the element in the first channel data so as to be larger than or equal to a preset value; the scaling amount is used for scaling the real part and the imaginary part of the element in the first channel data so as to be smaller than or equal to a preset threshold;

5) The terminal subtracts the translation amount from the amplitude of the element in the first channel data and divides the translation amount by the expansion amount; the translation amount is used for carrying out translation processing on the amplitude of the element in the first channel data so as to be larger than or equal to a preset value; the expansion and contraction amount is used for carrying out expansion and contraction processing on the amplitude of the element in the first channel data so as to be smaller than or equal to a preset threshold;

6) The terminal subtracts the translation amount from the phase of the element in the first channel data and divides the translation amount by the expansion amount; the translation amount is used for carrying out translation processing on at least one of phases of elements in the first channel data so as to be larger than or equal to a preset value; the expansion and contraction amount is used for carrying out expansion and contraction processing on the phases of elements in the first channel data so as to be smaller than or equal to a preset threshold;

7) The terminal subtracts the translation amount from the amplitude and the phase of the elements in the first channel data and divides the translation amount by the expansion amount; the translation amount is used for carrying out translation processing on the amplitude and the phase of the element in the first channel data so as to be larger than or equal to a preset value; the expansion and contraction amount is used for carrying out expansion and contraction processing on the amplitude and the phase of the element in the first channel data so as to be smaller than or equal to a preset threshold;

etc.; this is not particularly limited.

For the network device, multiplying at least one of an element within the second channel data, a real part of the element within the second channel data, an imaginary part of the element within the second channel data, an amplitude of the element within the second channel data, and a phase of the element within the second channel data by a scaling amount, plus a translation amount.

1) The network equipment multiplies the elements in the second channel data by the expansion amount and then adds the translation amount; the expansion and contraction amount is used for carrying out expansion and contraction processing on elements in the first channel data so that the expansion and contraction amount is smaller than or equal to a preset threshold; the translation amount is used for carrying out translation processing on elements in the first channel data so as to be larger than or equal to a preset value;

2) The network device multiplies the real part of the element in the second channel data by the expansion amount and then adds the translation amount; the method comprises the steps that the expansion and contraction amount is used for carrying out expansion and contraction processing on the real part of an element in first channel data so that the real part of the element in the first channel data is smaller than or equal to a preset threshold; the shift amount is used for carrying out shift processing on the real part of the element in the first channel data so as to be larger than or equal to a preset value;

3) The network equipment multiplies the imaginary part of the element in the second channel data by the expansion amount and adds the translation amount; the method comprises the steps of performing expansion and contraction processing on an imaginary part of an element in first channel data to enable the imaginary part to be smaller than or equal to a preset threshold; the shift amount is used for carrying out shift processing on at least one of the imaginary parts of the elements in the first channel data so as to be larger than or equal to a preset value;

4) The network equipment multiplies the real part and the imaginary part of the element in the second channel data by the expansion amount and adds the translation amount; the method comprises the steps that the expansion quantity is used for carrying out expansion processing on the real part and the imaginary part of an element in first channel data so as to be smaller than or equal to a preset threshold; the shift amount is used for carrying out shift processing on the real part and the imaginary part of the element in the first channel data so as to be larger than or equal to a preset value;

5) The network device multiplies the amplitude of the element in the second channel data by the expansion amount and then adds the translation amount; the method comprises the steps of performing expansion and contraction processing on the amplitude of elements in first channel data to enable the amplitude to be smaller than or equal to a preset threshold; the translation amount is used for carrying out translation processing on the amplitude of the element in the first channel data so as to be larger than or equal to a preset value;

6) The network device multiplies the phase of the element in the second channel data by the stretching amount and adds the shifting amount; the method comprises the steps of performing expansion and contraction processing on phases of elements in first channel data to enable the phases to be smaller than or equal to a preset threshold; the shift amount is used for carrying out shift processing on at least one of phases of elements in the first channel data so as to be larger than or equal to a preset value;

7) The network device multiplies the amplitude and the phase of the elements in the second channel data by the expansion and contraction amount and adds the translation amount; the method comprises the steps of performing scaling processing on the amplitude and the phase of elements in first channel data to enable the amplitude and the phase to be smaller than or equal to a preset threshold; the translation amount is used for carrying out translation processing on the amplitude and the phase of the element in the first channel data so as to be larger than or equal to a preset value;

Etc.; this is not particularly limited.

The description of the "translation amount" is the same as that in the above "mode one", and will not be repeated here; the description of the "expansion amount" is identical to that of the above-described "mode two", and will not be repeated.

Mode four:

as can be seen from the foregoing "mode one", "mode two", and "mode three", since at least one of the element in the first channel data, the real part of the element in the first channel data, the imaginary part of the element in the first channel data, the amplitude of the element in the first channel data, and the phase of the element in the first channel data may have a value less than or equal to a preset value (e.g., zero), the embodiment of the present application may perform the translation processing on the real part of the element and/or the imaginary part of the element, the amplitude of the element, and/or the phase of the element to make the real part of the element and/or the imaginary part of the element greater than or equal to a preset value, and then perform the expansion processing to make the real part of the element and the amplitude of the element less than or equal to a preset threshold, thereby not only being beneficial to ensuring that the AI model is successfully processed when the AI model is input to perform the processing, but also beneficial to improving the processing efficiency of the AI model.

The above-mentioned processing is an overall processing, such as panning and/or scaling, of the first channel data. Yet another approach (i.e., "mode four") may be to partially process the first channel data. This can affect only a part of the data and no corresponding back-processing is required on the network device side.

The partial processing may include truncation (i.e., discarding data whose modulus, real, imaginary, amplitude, or phase is less than or equal to a predetermined value as low order bits (least significant bit, LSB). This allows smaller data to be set to zero or close to zero, reducing the amount of unimportant information.

The partial processing may include saturation (i.e., discarding data whose modulus, real, imaginary, magnitude, or phase is greater than or equal to a predetermined threshold as high order bits (most significant bit, MSB). Thus, larger data can be reduced, and overlarge fluctuation of the data is avoided. At least one of the elements within the first channel data, the real part of the elements within the first channel data, the imaginary part of the elements within the first channel data, the amplitude of the elements within the first channel data, the phase of the elements within the first channel data is truncated and/or saturated for the terminal.

It will be appreciated that there may be the following ways for the terminal:

1) The terminal cuts and/or saturates the elements in the first channel data;

2) The terminal truncates and/or saturates the real part of the element in the first channel data;

3) The terminal cuts and/or saturates the imaginary part of the element in the first channel data;

4) The terminal cuts and/or saturates the real part and the imaginary part of the element in the first channel data;

5) The terminal cuts and/or saturates the amplitude of the element in the first channel data;

6) The terminal truncates and/or saturates the phases of the elements in the first channel data;

7) The terminal truncates and/or saturates the amplitude and phase of the elements in the first channel data;

etc.; this is not particularly limited.

The specific implementation manner may be known in combination with the manner of the foregoing "manner one", "manner two" and "manner three", and will not be described in detail.

Mode five:

The above-mentioned processing is an overall processing, such as panning and/or scaling, of the first channel data. Yet another way (i.e., "way five") may be to partially process the first channel data. This may affect only a portion of the data.

The partial processing may include data deletion, i.e., deleting data whose modulus, real part, imaginary part, amplitude, or phase is less than or equal to a preset value (not input to the AI model for compression), equivalent to reducing the size of the data input to the AI model for compression. Thus, smaller data can be not input into the AI model for compression, and the unimportant information amount is reduced. A typical example is that there may be insignificant transmission paths (paths) in the channel matrix that may be deleted before being input to the AI model for compression.

For the terminal, deletion is performed for at least one of an element in the first channel data, a real part of the element in the first channel data, an imaginary part of the element in the first channel data, an amplitude of the element in the first channel data, and a phase of the element in the first channel data.

It will be appreciated that there may be the following ways for the terminal:

1) The terminal deletes the element (according to the module size) in the first channel data;

2) The terminal deletes the real part (according to the real part size) of the element in the first channel data;

3) The terminal deletes the imaginary part (according to the size of the imaginary part) of the element in the first channel data;

4) The terminal deletes the real part and the imaginary part (according to the sizes of the real part and the imaginary part) of the elements in the first channel data;

5) The terminal deletes the amplitude (according to the amplitude) of the element in the first channel data;

6) The terminal deletes the phase (according to the phase size) of the element in the first channel data;

7) The terminal deletes the amplitude and the phase (according to the amplitude and the phase) of the element in the first channel data;

etc.; this is not particularly limited.

Since the terminal makes data, the terminal needs to tell the network device the location (element location) of the deleted data. That is, the terminal feeds back (or reports) the position (element position) of the deleted data.

For the network device, the restoration is performed for at least one of an element within the second channel data, a real part of the element within the second channel data, an imaginary part of the element within the second channel data, an amplitude of the element within the second channel data, and a phase of the element within the second channel data.

1) The network device restores (in its modulo size) the elements within the second channel data;

2) The network device restores the real part (according to the real part size) of the element in the second channel data;

3) The network device restores the imaginary part (according to the size of the imaginary part) of the element in the second channel data;

4) The network device restores the real part and the imaginary part (according to the sizes of the real part and the imaginary part) of the elements in the second channel data;

5) The network device restores the amplitude (according to the amplitude) of the element in the second channel data;

6) The network device restores the phase (according to the phase size) of the element in the second channel data;

7) The network device restores the amplitude and phase (in terms of their amplitude and phase magnitudes) of the elements within the second channel data;

etc.; this is not particularly limited.

The network device restores the position of the deleted data according to the position (element position) of the deleted data fed back (or reported) by the terminal.

The specific implementation manner may be known in combination with the manner of the foregoing "manner one", "manner two", "manner three" and "manner four", which are not described herein.

The foregoing description of the embodiments of the present application has been presented primarily from a method-side perspective. It will be appreciated that the terminal or network device, in order to implement the above-described functions, includes corresponding hardware structures and/or software modules that perform the respective functions. Those of skill in the art will readily appreciate that the elements and algorithm steps of the examples described in connection with the embodiments disclosed herein may be implemented as hardware or combinations of hardware and computer software. Whether a function is implemented as hardware or computer software driven hardware depends upon the particular application and design constraints imposed on the solution. Those skilled in the art may implement the described functionality using different approaches for each particular application, but such implementation is not to be considered as outside the scope of this application.

The embodiment of the application can divide the functional units of the terminal or the network equipment according to the method. For example, each functional unit may be divided corresponding to each function, or two or more functions may be integrated in one processing unit. The integrated units described above may be implemented either in hardware or in software program modules. It should be noted that, in the embodiment of the present application, the division of the units is schematic, but only one logic function is divided, and another division manner may be implemented in actual implementation.

In the case of using integrated units, fig. 3 is a block diagram of functional units of a channel data processing apparatus according to an embodiment of the present application. The channel data processing apparatus 300 includes: a processing unit 302 and a communication unit 303. The processing unit 302 is used for controlling and managing the operation of the channel data processing device 300. For example, the processing unit 302 is configured to support the channel data processing device 300 to perform the steps performed by the terminal in fig. 2 and other processes for the technical solutions described herein. The communication unit 303 is used to support communication between the channel data processing apparatus 300 and other devices in the wireless communication system. The channel data processing device 300 may further comprise a storage unit 301 for storing a computer program or instructions to be executed by the channel data processing device 300.

It should be noted that the channel data processing apparatus 300 may be a chip or a chip module.

The processing unit 302 may be a processor or a controller, and may be, for example, a central processing unit (central processing unit, CPU), a general purpose processor, a digital signal processor (digital signal processor, DSP), an application-specific integrated circuit (ASIC), a field programmable gate array (field programmable gate array, FPGA), or other programmable logic device, a transistor logic device, a hardware component, or any combination thereof. Which may implement or perform the various exemplary logical blocks, modules, and circuits described in connection with the present disclosure. The processing unit 302 may also be a combination implementing computing functionality, e.g., comprising one or more microprocessor combinations, a combination of a DSP and a microprocessor, etc. The communication unit 303 may be a communication interface, a transceiver, a transceiving circuit, etc., and the storage unit 301 may be a memory. When the processing unit 302 is a processor, the communication unit 303 is a communication interface, and the storage unit 301 is a memory, the channel data processing apparatus 300 according to the embodiment of the present application may be a terminal shown in fig. 5.

In particular implementation, the processing unit 302 is configured to perform any step performed by the terminal in the above method embodiment, and when performing data transmission such as sending, the communication unit 303 is optionally invoked to complete a corresponding operation. The following is a detailed description.

The processing unit 302 is configured to: acquiring first channel data; and processing the first channel data to obtain second channel data.

As can be seen, in the process of directly feeding back (or reporting) channel data to the CSI feedback architecture through the AI model, in order to adapt the AI model for image processing, it is avoided that the AI model cannot process the channel data or the AI model is low in processing efficiency due to the existence of out-of-range elements in the channel data input to the AI model, and the channel data processing apparatus 300 in this embodiment of the present application needs to process the channel data (i.e., the first channel data) to be fed back (or reported), so that the processed channel data (i.e., the second channel data) meets the requirements of the AI model adapted to image processing, thereby being beneficial to ensuring that the AI model can successfully process the input processed channel data or achieve higher processing efficiency.

It should be noted that, the specific implementation of each operation in the embodiment shown in fig. 3 may be described in detail in the method embodiment shown in fig. 2, which is not described in detail herein.

In some possible implementations, in processing the first channel data, the processing unit 302 is configured to:

the amount of translation is subtracted from at least one of the elements within the first channel data, the real part of the elements within the first channel data, and the imaginary part of the elements within the first channel data.

dividing at least one of an element in the first channel data, a real part of the element in the first channel data, and an imaginary part of the element in the first channel data by a scaling amount.

the shift amount is subtracted from at least one of the element in the first channel data, the real part of the element in the first channel data, and the imaginary part of the element in the first channel data, and divided by the stretch amount.

In some possible implementations, the amount of translation is m;

m is used to represent a minimum value of at least one of all elements within the first channel data, a modulus of all elements within the first channel data, a real part of all elements within the first channel data, and an imaginary part of all elements within the first channel data.

In some possible implementations, the translation is a quantized value of m;

m is used to represent a minimum value of at least one of all elements within the first channel data, a modulus of all elements within the first channel data, a real part of all elements within the first channel data, and all imaginary parts of elements within the first channel data.

In some possible implementations, the amount of telescoping is the difference between M and M;

m is used to represent a maximum value of at least one of all elements in the first channel data, a modulus of all elements in the first channel data, a real part of all elements in the first channel data, and an imaginary part of all elements in the first channel data;

In some possible implementations, the amount of scaling is a quantized value of the difference between M and M;

m is used to represent a maximum value of at least one of all elements in the first channel data, a modulus of all elements in the first channel data, a real part of all elements in the first channel data, and an imaginary part of all elements in the first channel data.

In some possible implementations, the amount of scaling is one of a norm of the first channel data, an average of power of all elements within the first channel data, and an average of square magnitudes of all elements within the first channel data.

In some possible implementations, the amount of scaling is one of reference signal received power RSRP, reference signal received quality RSRQ, reference signal strength indication RSSI.

In some possible implementations, the processing unit 302 is further configured to: and reporting the translation amount or the expansion amount.

In some possible implementations, the processing unit 302 is configured to report the translation amount or the expansion amount:

and reporting the translation amount or the expansion amount through a Channel State Information (CSI) feedback process.

In the case of using integrated units, fig. 4 is a block diagram showing functional units of a channel data preprocessing apparatus according to an embodiment of the present application. The channel data preprocessing apparatus 400 includes: a processing unit 402 and a communication unit 403. The processing unit 402 is configured to control and manage the actions of the channel data preprocessing apparatus 400, for example, the processing unit 402 is configured to support the channel data preprocessing apparatus 400 to perform steps performed by the network device in fig. 2 and other processes for the technical solution described in the present application. The communication unit 403 is used to support communication between the channel data preprocessing apparatus 400 and other devices in the wireless communication system. The channel data preprocessing apparatus 400 may further include a storage unit 401 for storing a computer program or instructions executed by the channel data preprocessing apparatus 400.

It should be noted that the channel data preprocessing apparatus 400 may be a chip or a chip module.

The processing unit 402 may be a processor or controller, for example, CPU, DSP, ASIC, FPGA or other programmable logic device, transistor logic device, hardware component, or any combination thereof. Which may implement or perform the various exemplary logical blocks, modules, and circuits described in connection with the present disclosure. The processing unit 402 may also be a combination implementing computing functions, e.g., comprising one or more microprocessor combinations, a combination of a DSP and a microprocessor, etc. The communication unit 403 may be a communication interface, a transceiver circuit, or the like, and the storage unit 401 may be a memory. When the processing unit 402 is a processor, the communication unit 403 is a communication interface, and the storage unit 401 is a memory, the channel data post-processing apparatus 400 according to the embodiment of the present application may be a network device shown in fig. 6.

In particular implementations, the processing unit 402 is configured to perform any of the steps performed by the network device in the above-described method embodiments, and when performing data transmission such as sending, optionally invokes the communication unit 403 to complete the corresponding operation. The following is a detailed description.

The processing unit 402 is configured to: acquiring second channel data; and carrying out inverse processing on the second channel data to obtain first channel data.

It can be seen that, in the process of directly feeding back the channel data to the CSI feedback architecture through the AI model, since the terminal needs to process the fed back (or reported) channel data before feeding back (or reporting) in order to adapt to the AI model for image processing, when the channel data post-processing apparatus 400 acquires the processed channel data (i.e., the second channel data), the channel data post-processing apparatus 400 needs to perform post-processing on the processed channel data to obtain the first channel data, so that the channel data post-processing apparatus 400 performs related operations through the first channel data, for example, the network device calculates the CQI through the first channel data, calculates the corresponding SINR through the first channel data and the corresponding MCS so as to schedule the terminal through the MCS, and so on.

It should be noted that, the specific implementation of each operation in the embodiment shown in fig. 4 may be described in detail in the method embodiment shown in fig. 3, which is not described in detail herein.

In some possible implementations, in terms of the inverse processing of the second channel data, the processing unit 402 is configured to:

The shift amount is added to at least one of the element in the second channel data, the real part of the element in the second channel data, and the imaginary part of the element in the second channel data.

multiplying at least one of the elements in the second channel data, the real part of the elements in the second channel data, and the imaginary part of the elements in the second channel data by a scaling amount.

at least one of the elements in the second channel data, the real part of the elements in the second channel data, and the imaginary part of the elements in the second channel data is multiplied by a scaling amount, and then by a translation amount.

In some possible implementations, the amount of translation is m;

m is used to represent a minimum value of at least one of an element within the first channel data, a modulus of all elements within the first channel data, a real part of an element within the first channel data, and an imaginary part of an element within the first channel data.

Shifting the quantized value of m in some possible implementations;

m is used to represent a maximum value of at least one of an element in the first channel data, a modulus of all elements in the first channel data, a real part of an element in the first channel data, and an imaginary part of an element in the first channel data.

m is used to represent a minimum value of at least one of an element within the first channel data, a real part of the element within the first channel data, and an imaginary part of the element within the first channel data.

In some possible implementations, the amount of scaling is one of a norm of the first channel data, an average of power of the elements within the first channel data, and an average of a square of magnitude of the elements within the first channel data.

In some possible implementations, the amount of translation is reported.

In some possible implementations, the amount of translation is reported as:

the translation is reported by a Channel State Information (CSI) feedback process.

In some possible implementations, the amount of telescoping is reported.

In some possible implementations, the amount of scalability is obtained by reporting, including:

the telescoping amount is reported by the CSI feedback process.

Referring to fig. 5, fig. 5 is a schematic structural diagram of a terminal according to an embodiment of the present application. Wherein the terminal 500 comprises a processor 510, a memory 520 and a communication bus for connecting the processor 510 and the memory 520.

Memory 520 includes, but is not limited to, random access memory (random access memory, RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM), or portable read-only memory (compact disc read-only memory, CD-ROM), and memory 520 is used to store program code and data for execution by terminal 500.

The terminal 500 may also include a communication interface for receiving and transmitting data.

Processor 510 may be one or more CPUs, which may be a single core CPU or a multi-core CPU in the case where processor 510 is a single CPU.

The processor 510 in the terminal 500 is adapted to execute a computer program or instructions 521 stored in the memory 520 to carry out the steps of: acquiring first channel data; and processing the first channel data to obtain second channel data.

As can be seen, in the process of directly feeding back (or reporting) channel data to the CSI feedback architecture through the AI model, in order to adapt to the AI model for image processing, it is avoided that the AI model cannot process the channel data or the AI model is low in processing efficiency due to the existence of out-of-range elements in the channel data input to the AI model, and the terminal 500 in this embodiment of the present application needs to process the channel data (i.e., the first channel data) to be fed back (or reported), so that the processed channel data (i.e., the second channel data) meets the requirements of the AI model adapted to image processing, thereby being beneficial to ensuring that the AI model can successfully process the input processed channel data or achieve higher processing efficiency. It should be noted that, the specific implementation of each operation may be described in the foregoing method embodiment shown in fig. 2, and the terminal 500 may be used to execute the method on the terminal side in the foregoing method embodiment of the present application, which is not described herein in detail.

In some possible implementations, in processing the first channel data, the processor 510 is configured to execute a computer program or instructions 521 stored in the memory 520 to implement the steps of:

In some possible implementations, the amount of translation is m;

In some possible implementations, the translation is a quantized value of m;

In some possible implementations, the processor 510 is further configured to execute a computer program or instructions 521 stored in the memory 520 to implement the steps of: and reporting the translation amount or the expansion amount.

In some possible implementations, in terms of reporting the amount of translation or the amount of expansion, the processor 510 is configured to execute a computer program or instructions 521 stored in the memory 520 to implement the steps of:

Referring to fig. 6, fig. 6 is a schematic structural diagram of a network device according to an embodiment of the present application. Wherein the network device 600 comprises a processor 610, a memory 620 and a communication bus for connecting the processor 610, the memory 620.

Memory 620 includes, but is not limited to, RAM, ROM, EPROM or CD-ROM, which memory 620 is used to store related instructions and data.

The network device 600 may also include a communication interface for receiving and transmitting data.

The processor 610 may be one or more CPUs, and in the case where the processor 610 is one CPU, the CPU may be a single core CPU or a multi-core CPU.

The processor 610 in the network device 600 is configured to execute a computer program or instructions 621 stored in the memory 620 to implement the steps of: acquiring second channel data; and carrying out inverse processing on the second channel data to obtain first channel data.

It can be seen that, in the process of directly feeding back the channel data to the CSI feedback architecture through the AI model, since the terminal needs to process the fed back (or reported) channel data before feeding back (or reporting) in order to adapt to the AI model for image processing, when the network device 600 acquires the processed channel data (i.e., the second channel data), the network device 600 needs to process the processed channel data back to obtain the first channel data, so that the network device 600 performs related operations through the first channel data, for example, the network device 600 calculates the CQI through the first channel data, calculates the corresponding SINR and the corresponding MCS through the first channel data, so as to schedule the terminal through the MCS, and so on.

It should be noted that, the specific implementation of each operation may be described in the foregoing method embodiment shown in fig. 2, and the network device 600 may be used to execute the method on the network device side in the foregoing method embodiment of the present application, which is not described herein in detail.

In some possible implementations, in terms of reprocessing the second channel data, the processor 610 is configured to execute a computer program or instructions 621 stored in the memory 620 to perform the steps of:

In some possible implementations, the amount of translation is m;

Shifting the quantized value of m in some possible implementations;

In some possible implementations, the amount of translation is reported.

In some possible implementations, the amount of translation is reported as:

In some possible implementations, the amount of telescoping is reported.

the telescoping amount is reported by the CSI feedback process.

The embodiment of the application also provides a chip, which comprises a processor, a memory and a computer program or instructions stored on the memory, wherein the processor executes the computer program or instructions to realize the steps described in the embodiment of the method.

The embodiment of the application also provides a chip module, which comprises a transceiver component and a chip, wherein the chip comprises a processor, a memory and a computer program or instructions stored on the memory, and the processor executes the computer program or instructions to realize the steps described in the embodiment of the method.

Embodiments of the present application also provide a computer-readable storage medium having stored thereon a computer program or instructions which, when executed by a processor, implement the steps described in the method embodiments above.

Embodiments of the present application also provide a computer program product comprising a computer program or instructions which, when executed by a processor, implement the steps described in the method embodiments above. The computer program product may be a software installation package.

For the above embodiments, for simplicity of description, the same is denoted as a series of combinations of actions. It will be appreciated by those skilled in the art that the present application is not limited by the illustrated ordering of acts, as some steps may be performed in other order or concurrently in embodiments of the present application. In addition, those skilled in the art will appreciate that the embodiments described in the specification are presently preferred embodiments, and that the acts, steps, modules, units, etc. that are referred to are not necessarily required in the embodiments of the application.

In the foregoing embodiments, the descriptions of the embodiments of the present application are focused on each embodiment, and for a portion of one embodiment that is not described in detail, reference may be made to the related descriptions of other embodiments.

Those of skill in the art will appreciate that the functions of the methods, steps, or associated modules/units described in the embodiments of the present application may be implemented, in whole or in part, in software, hardware, firmware, or any combination thereof. When implemented in software, may be implemented in whole or in part in the form of a computer program product, or in the form of computer program instructions executed by a processor. Wherein the computer program product comprises at least one computer program instruction, which may be comprised of corresponding software modules, which may be stored in RAM, flash memory, ROM, EPROM, EEPROM, registers, hard disk, a removable disk, a compact disk read-only memory (CD-ROM), or any other form of storage medium known in the art. The computer program instructions may be stored in a computer-readable storage medium or transmitted from one computer-readable storage medium to another. For example, the computer program instructions may be transmitted from one website, computer, server, or data center to another website, computer, server, or data center, by wire or wirelessly. The computer readable storage medium may be any available medium that can be accessed by a computer or a data storage device such as a server, data center, etc. that contains an integration of one or more available media. The usable medium may be a magnetic medium (e.g., floppy disk, hard disk, magnetic tape), optical medium, or semiconductor medium (e.g., SSD), etc.

The respective means or products described in the above embodiments include respective modules/units, which may be software modules/units, may be hardware modules/units, or may be partly software modules/units, and partly hardware modules/units. For example, for each device or product applied to or integrated on a chip, each module/unit contained in the device or product may be implemented by hardware such as a circuit; alternatively, a part of the modules/units contained therein may be implemented in a software program running on a processor integrated within a chip, and another part (if any) of the modules/units may be implemented in hardware such as a circuit. The same applies to each device or product applied to or integrated with the chip module, or each device or product applied to or integrated with the terminal.

The foregoing detailed description of the embodiments of the present application has further been presented for the purposes of illustration, description, and illustration, it should be understood that the foregoing description is merely illustrative of the embodiments of the present application and is not intended to limit the scope of the embodiments of the present application. Any modification, equivalent replacement, improvement, etc. made on the basis of the technical solution of the embodiments of the present application should be included in the protection scope of the embodiments of the present application.

Claims

1. A method of channel data processing, comprising:

acquiring first channel data;

and processing the first channel data to obtain second channel data.

2. The method of claim 1, wherein said processing said first channel data comprises:

3. The method of claim 1, wherein said processing said first channel data comprises:

4. The method of claim 1, wherein said processing said first channel data comprises:

and subtracting a translation amount from at least one of the element in the first channel data, the real part of the element in the first channel data and the imaginary part of the element in the first channel data, and dividing the translation amount by a telescoping amount.

5. The method of claim 2 or 4, wherein the translation amount is m;

the m is used to represent a minimum value of at least one of all elements within the first channel data, a modulus of all elements within the first channel data, a real part of all elements within the first channel data, and an imaginary part of all elements within the first channel data.

6. The method according to claim 2 or 4, characterized in that the translation is a quantized value of m;

the m is used to represent a minimum value of at least one of all elements within the first channel data, a modulus of all elements within the first channel data, a real part of all elements within the first channel data, and all imaginary parts of elements within the first channel data.

7. The method according to claim 3 or 4, wherein the amount of telescoping is the difference between M and M;

the M is used to represent a maximum value of at least one of all elements within the first channel data, a modulus of all elements within the first channel data, a real part of all elements within the first channel data, and an imaginary part of all elements within the first channel data;

8. The method according to claim 3 or 4, characterized in that the amount of telescoping is a quantized value of the difference between M and M;

9. The method of claim 3 or 4, wherein the amount of scaling is one of a norm of the first channel data, an average of power of all elements within the first channel data, and an average of square magnitudes of all elements within the first channel data.

10. The method of claim 3 or 4 wherein the amount of scaling is one of reference signal received power, RSRP, reference signal received quality, RSRQ, reference signal strength indication, RSSI.

11. A method according to claim 2 or 3, further comprising:

reporting the translation amount or the expansion amount.

12. The method of claim 11, wherein the reporting the amount of translation or the amount of telescoping comprises:

13. A channel data de-processing method, comprising:

acquiring second channel data;

14. The method of claim 13, wherein said de-processing said second channel data comprises:

a shift amount is added to at least one of the element in the second channel data, the real part of the element in the second channel data, and the imaginary part of the element in the second channel data.

15. The method of claim 13, wherein said de-processing said second channel data comprises:

Multiplying at least one of the element in the second channel data, the real part of the element in the second channel data, and the imaginary part of the element in the second channel data by a scaling amount.

16. The method of claim 13, wherein said de-processing said second channel data comprises:

multiplying at least one of the element in the second channel data, the real part of the element in the second channel data, and the imaginary part of the element in the second channel data by a scaling amount, and adding a translation amount.

17. The method of claim 14 or 16, wherein the translation amount is m;

the m is used to represent a minimum value of at least one of an element within the first channel data, a modulus of all elements within the first channel data, a real part of an element within the first channel data, and an imaginary part of an element within the first channel data.

18. The method according to claim 14 or 16, characterized in that the translation is a quantized value of m;

19. The method according to claim 15 or 16, wherein the amount of telescoping is the difference between M and M;

the M is used for representing a maximum value of at least one of an element in the first channel data, a modulus of all elements in the first channel data, a real part of the element in the first channel data, and an imaginary part of the element in the first channel data;

the m is used to represent a minimum value of at least one of an element within the first channel data, a real part of the element within the first channel data, and an imaginary part of the element within the first channel data.

20. The method according to claim 15 or 16, wherein the amount of scaling is a quantized value of the difference between M and M;

21. The method of claim 15 or 16, wherein the amount of scaling is one of a norm of the first channel data, an average of power of elements within the first channel data, and an average of square magnitudes of elements within the first channel data.

22. The method according to claim 15 or 16, wherein the scaling amount is one of a reference signal received power, RSRP, a reference signal received quality, RSRQ, and a reference signal strength indication, RSSI.

23. The method of any one of claims 14, 16-18, wherein the amount of translation is reported.

24. The method of claim 23, wherein the translation is reported, comprising:

25. The method of any one of claims 15, 16, 19-22, wherein the amount of telescoping is reported.

26. The method of claim 25, wherein the amount of telescoping is reported, comprising:

the expansion and contraction amount is reported through a CSI feedback process.

27. A channel data processing apparatus, the apparatus comprising a processing unit configured to:

Acquiring first channel data;

and processing the first channel data to obtain second channel data.

28. A channel data de-processing apparatus, the apparatus comprising a processing unit configured to:

acquiring second channel data;

29. A terminal comprising a processor, a memory and a computer program or instructions stored on the memory, characterized in that the processor executes the computer program or instructions to carry out the steps of the method according to any one of claims 1-12.

30. A network device comprising a processor, a memory and a computer program or instructions stored on the memory, wherein the processor executes the computer program or instructions to implement the steps of the method of any one of claims 13-26.

31. A computer readable storage medium, characterized in that it has stored thereon a computer program or instructions which, when executed by a processor, implement the steps of the method of any of claims 1-26.

32. A chip comprising a processor, wherein the processor performs the steps of the method of any one of claims 1-12, 13-26.