RIS-assisted communication perception computing integrated data processing method, device and medium

Abstract

The present invention discloses a RIS-assisted communication perception computing integrated efficient data processing method, device and medium. In a 6G network environment, a user equipment UE collects environmental data and generates a transmission signal. The transmission signal is transmitted to a base station BS via a uniform planar array RIS. In this process, data processing is completed, and the processed data is fused at the BS. The received signal at the BS includes a signal for calculation and a perception signal. The frequency response of the received signal is derived, and the pilot vectors received by different subcarriers are used to detect the channel parameters, thereby minimizing the calculation distortion while ensuring the perception signal rate requirements and restoring the parameters. The method of the present invention sets RIS in a 6G network environment to reduce the interference of obstacles to the signal, effectively improve energy consumption and channel quality, minimize calculation distortion as the optimization goal, and improve data processing efficiency.

Description

Technical Field

[0001] The present invention relates to a RIS-assisted communication-awareness-computing-integrated efficient data processing method, device and medium, belonging to the technical field of communication-awareness integration. Background Art

[0002] 6G will make the vision of all things sensing, all things connected, and all things intelligent a reality. At the same time, with the further development of technologies such as large-scale antenna arrays, new multiple access, and full spectrum, as well as the enabling of technologies such as reconfigurable intelligent super surfaces and artificial intelligence, the integration of wireless communication and perception has become an important development direction. The integrated communication and perception technology will use wireless signals to achieve perception functions such as positioning, detection, imaging, and recognition of targets, obtain information about the surrounding physical environment, tap into communication capabilities, and enhance user experience. Through endogenous integrated spectrum resource sharing, hardware architecture design, air interface design, multi-point collaboration, and all-round information interaction, it can achieve green energy saving while achieving communication and perception capabilities, improve spectrum efficiency and perception accuracy, and ultimately achieve performance improvement for the entire network. Applications in 6G networks require ultra-high perception accuracy, ultra-low computing latency, and ultra-high-speed communication between a large number of IoT devices. Cellular IoT is transforming from a data-centric network to a computing-centric network. The traditional method of transmitting first and then computing is no longer suitable for massive data computing of IoT devices due to excessive latency and low spectrum efficiency.

[0003] The high complexity and hardware costs required for 6G networks, as well as the increased energy consumption, remain key issues. In addition, signal propagation is inherently random and largely uncontrollable. For these reasons, smart reflective surfaces (RIS) can reconfigure the wireless propagation environment through software-controlled reflections. RIS is a plane composed of a large number of low-cost passive reflective elements placed between base stations and users. Since each element can independently change the phase, amplitude, and even frequency of the incident signal, smart reflective surfaces can be used to enable users to better receive the signals sent by the base station. Summary of the invention

[0004] In order to overcome the deficiencies in the prior art, the present invention provides a RIS-assisted communication-awareness-computing integrated efficient data processing method, device and medium to solve the interference of obstacles on signals, energy consumption problems and delays in massive data processing in the prior art.

[0005] To achieve the above purpose, the technical solution adopted by the present invention is as follows:

[0006] A RIS-assisted communication perception computing integrated efficient data processing method. In a 6G network environment, K user equipment UEs collect environmental data and generate transmission signals. The transmission signals are transmitted via N rThe uniform planar array RIS formed by the units is transmitted to the N b antennas.

[0007] Further, the K UEs collect environmental data and generate a transmission signal, specifically:

[0008] K UEs collect environmental data and record the calculation symbol vector generated by the L non-uniform parameter information to be calculated and the perception symbol vector generated from the J non-uniform parameter information perceived from the surrounding Among them, d k,l is the lth non-uniform parameter information recorded by the kth UE, s' k,j is the jth non-uniform parameter information sensed by the kth UE from the surroundings, l = 1, 2, ..., L, j = 1, 2, ..., J;

[0009] Use Euclidean norm preprocessing to calculate the symbolic vector d k , get the calculated signal sent by the kth UE Then generate the transmission signal of the kth UE in, For k The transmit beamforming vector of for s' k,j The transmit beamforming vector of .

[0010] Furthermore, the transmission signal is transmitted to the BS via the RIS, and the transmission path includes a UE to RIS unit path and a RIS to BS antenna path:

[0011] The channel impulse response of a single UE to the rth unit of RIS via P incident paths is expressed as:

[0012]

[0013] Among them, δ(.) represents the Delta function; represents the equivalent complex path gain of the pth incident path from UE to RIS; is the phase difference between the incident paths of the UE-RIS unit, φ p and ψ p are the elevation and azimuth angles of arrival (AOA) at the RIS along the pth incident path, respectively. d represents the antenna spacing of the BS. p∈{0,...,P-1}, r∈{0,...,N r -1} represents the rth unit of RIS and r=iN y +o,i∈{0,…,N x -1},o∈{0,…,N y-1} indicates the unit index along the horizontal and vertical directions, respectively, r divided by N y The remainder λ c Indicates the carrier wavelength; is the delay difference of the pth path from the UE to the rth unit of the RIS, represents the delay of UE from the pth path to the first RIS unit, c represents the speed of light; f c Indicates the carrier frequency;

[0014] The channel impulse response from the rth RIS unit to the bth BS antenna is expressed as:

[0015]

[0016] in, is the phase difference between the RIS unit and the BS antenna leaving the path, θ b is the arrival angle AOA of the BS, φ r and ψ r are the elevation and azimuth of the departure angle at RIS, respectively; is the delay difference from the rth unit of RIS to the bth antenna of BS, g RB is the complex path gain from RIS to BS.

[0017] Furthermore, the received signal at the BS includes a calculation signal And the perception signal y':

[0018]

[0019] in, is the beamforming matrix of the calculated signal received at the BS; n is the additive white Gaussian noise; g RB is the complex path gain from RIS to BS; is the equivalent complex path gain, is the channel impulse response from UE to the rth unit at RIS The Fourier transform form of Indicates that based on φ at RIS p and ψ p Array steering vector of is the channel impulse response from the rth RIS unit to the bth BS antenna The Fourier transform form of represents the antenna array steering vector at the BS, Indicates that based on φ at RIS r and ψ r The array steering vector of u k,jis the sensing signal beamforming vector received by the j-th sensing symbol of the k-th UE at the BS.

[0020] Furthermore, the following optimization problem is constructed and the optimal W is obtained by solving it: k 、v k,j , Z and u k,j , in order to minimize computational distortion while ensuring perceptual efficiency:

[0021]

[0022] stlog2{1+Γ k,j )≥r k,j

[0023]

[0024] |f H (φ,ψ,τ)y| 2 <∈

[0025] in, Indicates computational distortion; r k,j represents the minimum achievable rate required for the jth perceived signal at the kth UE; P max,k represents the maximum transmit power budget of the kth UE; ∈ is the stop criterion threshold; represents the pilot vectors received by different subcarriers, represents the cascaded complex path gain, represents the pilot vector received by different subcarriers, and n represents additive white Gaussian noise.

[0026] Furthermore, the optimization problem is first divided into two sub-problems using the alternative optimization AO method, and the alternative optimization is stopped until the objective function value of the optimization problem approaches a fixed point in the iteration; then the problem obtained by the alternative optimization is transformed into a convex problem through semi-definite relaxation SDR, and finally the Newton orthogonal matching pursuit NOMP algorithm and the optimization tool CVX are used to solve the transformed convex problem.

[0027] The present invention also provides a computer-readable storage medium storing one or more programs, wherein the one or more programs include instructions, which, when executed by a computing device, cause the computing device to perform the steps of the method described above.

[0028] The present invention also provides an electronic device, comprising one or more processors, one or more memories and one or more programs, wherein the one or more programs are stored in the one or more memories and are configured to be executed by the one or more processors, and the one or more programs include steps for executing the method as described above.

[0029] Beneficial effects of the present invention:

[0030] 1. This method sets RIS between the user equipment UE and the base station BS to reduce the interference of obstacles on the signal and enhance the signal strength. The corresponding signal transmission power does not need to be increased compared with the previous one.

[0031] 2. Utilize the superposition characteristics of wireless multiple access channels to reduce the delay of massive data processing;

[0032] 3. To clarify the channel characteristics and provide the channel state information (CSI) required for demodulation, consider channel estimation. Derive the frequency response of the received signal and use pilot symbols to detect channel parameters. Optimize from the perspective of minimizing computational distortion while ensuring the perceived signal rate requirements and recovery parameters to improve the overall performance of the communication, perception and computing integrated system. BRIEF DESCRIPTION OF THE DRAWINGS

[0033] Figure 1 This is a system architecture diagram for RIS-assisted communication, perception, computing and efficient data processing. DETAILED DESCRIPTION

[0034] In order to facilitate the understanding of those skilled in the art, the present invention is further described below in conjunction with embodiments and drawings. The contents mentioned in the implementation modes are not intended to limit the present invention.

[0035] The present invention provides a RIS-assisted communication-awareness-computing integrated efficient data processing method, such as Figure 1 In the 6G network environment, the base station (BS) is equipped with N b The direct path from UE to BS is blocked by obstacles such as buildings and trees, and the N r The uniform planar array RIS is formed by RIS units. The signal is transmitted to the BS through the RIS-assisted MIMO channel. During this process, the data is processed and fused at the BS. The setting of RIS reduces the interference of obstacles on the signal, effectively improves energy consumption and channel quality, and takes minimizing computational distortion as the optimization goal while ensuring the perceived signal rate requirements and recovery parameters. The optimization problem is solved through semi-definite relaxation (SDR), Newton orthogonal matching pursuit (NOMP) and optimization tool CVX, which improves data processing efficiency.

[0036] The specific steps of a RIS-assisted communication-awareness-computing integrated efficient data processing method are as follows:

[0037] Step 1: K UEs collect environmental data through sensor devices, record the L non-uniform parameter information to be calculated, and generate a calculation symbol vector and generate the computational symbol vector from the J non-uniform parameter information perceived from the surroundings The symbol vector is calculated by Euclidean norm preprocessing to obtain the calculated signal sent by the kth UE Then generate the send signal in, For k The transmit beamforming vector, v k,j for s' k,j The transmit beamforming vector, v k,j for s' k The transmit beamforming vector The elements in W k s k To calculate the signal, To perceive the signal;

[0038] Specifically, the UE includes but is not limited to: cellular mobile users, robots, and Internet of Things devices.

[0039] Specifically, the sensing signals include but are not limited to: signals extracted from power grid sensors, material composition sensors, environmental sensors, and vehicle-mounted sensors.

[0040] Specifically, the content to be calculated includes, but is not limited to: parameter calculation required for equipment status evaluation, life prediction, intelligent transportation system, climate monitoring, etc. in intelligent production and control of factories.

[0041] Step 2: The transmitted signal is transmitted to the BS via the RIS-assisted MIMO channel. The signal received at the BS includes the signal used for calculation And the perception signal y':

[0042] Calculating Signals

[0043] Perceiving signals

[0044] in, Indicates a channel that uses RIS assistance.

[0045] Specifically, the system adopts Orthogonal Frequency Division Multiplexing (OFDM) technology, and RIS consists of N x ×N y The present invention only considers the RIS-assisted path, including the UE-RIS path and the RIS-BS antenna path. The BS and RIS are located in an environment with limited local scattering. Based on the angle of arrival / angle of departure (AoA / AoD) and the delay τ, the phase difference and delay difference between the received signals of the UE-RIS unit and the RIS unit-BS antenna are obtained. According to the obtained phase difference, delay difference and complex path gain g, the UE-RIS path channel and RIS-BS antenna path channel

[0046] The channel impulse response of a single UE to the rth unit at the RIS via P incident paths is expressed as:

[0047]

[0048] Among them, δ(.) represents the Delta function, is the phase difference between the signals received by the UE-RIS unit, expressed as Among them, φ p and ψ p are the AOA elevation and azimuth angles of arrival along the pth path at the RIS, d represents the antenna spacing, p∈{0,...,P-1} represents the multipath channel from UE to RIS consisting of P incident paths, r∈{0,...,N r -1} represents the rth unit in RIS and r=iN y +o, where i∈{0,...,N x -1},o∈{0,…,N y -1} are the horizontal and vertical indices of the unit, respectively, from which we can deduce r divided by N y The remainder o=(r)N y and i = (r - (r) N y ) / N y ,λ c Indicates the carrier wavelength. is the delay difference of the pth path of the rth unit of UE-RIS, expressed as Where c represents the speed of light.

[0049] The channel from the rth RIS unit to the bth BS antenna is expressed as:

[0050]

[0051] in, is the phase difference between the RIS unit and the BS antenna receiving signal, expressed as Among them, θ b is the arrival angle AOA of the BS, φ r and ψ r are the departure angle elevation and azimuth at RIS respectively. is the delay difference from the rth unit of RIS to the bth antenna of BS, expressed as Among them, f c Indicates the carrier frequency.

[0052] Specifically, the RIS-assisted channel is divided into UE-RIS units and RIS unit-BS antenna is the diagonal matrix representing the RIS operation, represents the RIS phase shift vector at the mth OFDM pilot symbol, ρ m,r represents the phase shift of the rth RIS element at the mth pilot symbol, and during each pilot symbol, ρ m Assumed to be constant.

[0053] The signal used for calculation in the BS received signal is expressed as:

[0054]

[0055] in, is the received signal beamforming matrix; g RB is the complex path gain from RIS to BS; is the equivalent complex path gain, is the complex path gain of the pth path from UE to RIS; is the channel from UE to the rth unit at RIS The Fourier transform form of represents the array steering vector at RIS; is the channel from the rth RIS unit to the bth BS antenna The Fourier transform form of represents the array steering vector at the BS.

[0056] The perceived signal in the BS's received signal is expressed as:

[0057]

[0058] Among them, u k,j is the sensing signal beamforming vector received by the j-th sensing symbol of the k-th UE at the BS.

[0059] Step 3: Derive the frequency response of the received signal and use the pilot vector y received from different subcarriers to detect the channel parameters, thereby minimizing the computational distortion while ensuring the perceived signal rate requirement and recovery parameters. This optimization problem is solved by semi-definite relaxation (SDR), Newton orthogonal matching pursuit (NOMP) and the optimization tool CVX.

[0060] Specifically, the received signal obtained by the BS at the pilot symbol for calculation after the RIS is introduced for transmission assistance As well as the perception signal y' received by the BS and the pilot vector y received by different subcarriers, in order to minimize the calculation distortion while ensuring the perception signal rate requirement and the recovery parameters, the optimization problem is expressed as:

[0061]

[0062] stlog2(1+Γ k,j )≥r k,j

[0063]

[0064] |f H (φ,ψ,τ)y| 2 <∈

[0065] in, is the calculated distortion expressed as the MSE function for the receive beam and the transmit beam; r k,j represents the minimum achievable rate required for the jth perceived signal at the kth UE; P max,k represents the maximum transmit power budget of the kth UE; ∈ is the stop criterion threshold; represents the pilot vector received by different subcarriers, and n represents the corresponding noise vector.

[0066] This problem is NP-hard and non-convex. We first divide it into two sub-problems using the surrogate optimization (AO) method, and stop the surrogate optimization until the objective function value of the original problem approaches a fixed point in the iteration. Then, we transform the problem obtained by surrogate optimization into a convex problem through semi-definite relaxation (SDR), and finally solve the transformed convex problem using Newton orthogonal matching pursuit (NOMP) and the optimization tool CVX.

[0067] Based on the same technical solution, the present invention also discloses a computer-readable storage medium storing one or more programs, wherein the one or more programs include instructions, and when the instructions are executed by a computing device, the computing device executes the steps of the above method.

[0068] Based on the same technical solution, the present invention also discloses an electronic device, comprising one or more processors, one or more memories and one or more programs, wherein the one or more programs are stored in the one or more memories and are configured to be executed by the one or more processors, and the one or more programs include steps for executing the above method.

[0069] Those skilled in the art will appreciate that embodiments of the present invention may be provided as methods, systems, or computer program products. Therefore, the present invention may take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware. Moreover, the present invention may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0070] The present invention is described with reference to flowcharts and / or block diagrams of methods, devices (systems), and computer program products according to embodiments of the present invention. It should be understood that each process and / or block in the flowchart and / or block diagram, as well as the combination of processes and / or blocks in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0071] These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0072] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process. Figure 1 A process or multiple processes and / or boxes Figure 1 Steps for specifying functions in a box or boxes

[0073] The above is only a specific embodiment of the present invention, but the protection scope of the present invention is not limited thereto. Any person skilled in the art can easily think of changes or substitutions within the technical scope disclosed by the present invention, which should be included in the protection scope of the present invention. Therefore, the protection scope of the present invention should be based on the protection scope of the claims.

Claims

1. A RIS-assisted communication-awareness-computing integrated efficient data processing method, characterized in that: In a 6G network environment, K user equipments UE collect environmental data and generate transmission signals, which are transmitted via N r The uniform planar array RIS formed by the units is transmitted to the N b A base station BS with antennas; The K UEs collect environmental data and generate transmission signals, specifically: K UEs collect environmental data and record the calculation symbol vector generated by the L non-uniform parameter information to be calculated and the perception symbol vector generated from the J non-uniform parameter information perceived from the surrounding Among them, d k，l is the lth non-uniform parameter information recorded by the kth UE, s′ k，j is the j-th non-uniform parameter information sensed by the k-th UE from the surroundings, l=1, 2, ..., L, j=1, 2, ..., J; Use Euclidean norm preprocessing to calculate the symbolic vector d k , get the calculated signal sent by the kth UE Then generate the transmission signal of the kth UE in, For k The transmit beamforming vector of s′ k，j The transmit beamforming vector of The transmission signal is transmitted to the BS via the RIS, and the transmission path includes a UE to RIS unit path and a RIS to BS antenna path: The channel impulse response of a single UE to the rth unit of RIS via P incident paths is expressed as: Among them, δ(.) represents the Delta function; represents the equivalent complex path gain of the pth incident path from UE to RIS; is the phase difference between the incident paths of the UE-RIS unit, φ p and ψ p are the AOA elevation and azimuth angles of arrival along the pth incident path at the RIS, respectively, d represents the antenna spacing of the BS, p∈{0,...,P-1], r∈{0,...,N r -1] represents the rth unit of RIS and r = iN y +o,i∈{0,...,N x -1],o∈{0,...,N y -1} indicates the unit index along the horizontal and vertical directions, respectively, r divided by N y The remainder λ c Indicates the carrier wavelength; is the delay difference of the pth path from the UE to the rth unit of the RIS, represents the delay of UE from the pth path to the first RIS unit, c represents the speed of light; f c Indicates the carrier frequency; The channel impulse response from the rth RIS unit to the bth BS antenna is expressed as: in, is the phase difference between the RIS unit and the BS antenna leaving the path, θ b is the arrival angle AOA of the BS, φ r and ψ r are the elevation and azimuth of the departure angle at RIS, respectively; is the delay difference from the rth unit of RIS to the bth antenna of BS, g RB is the complex path gain from RIS to BS; The received signal at the BS includes the calculated signal And the perception signal y′: in, is the beamforming matrix of the calculated signal received at the BS; n is the additive white Gaussian noise; g RB is the complex path gain from RIS to BS; is the equivalent complex path gain, is the channel impulse response from UE to the rth unit at RIS The Fourier transform form of Indicates that based on φ at RIS p and ψ p Array steering vector of is the channel impulse response from the rth RIS unit to the bth BS antenna The Fourier transform form of represents the antenna array steering vector at the BS, Indicates that based on φ at RIS r and ψ r The array steering vector of u k，j is the sensing signal beamforming vector received by the j-th sensing symbol of the k-th UE at the BS.

2. A RIS-assisted communication-awareness-computing-integrated efficient data processing method as claimed in claim 1, characterized in that: Construct the following optimization problem and solve it to get the optimal W k 、v k，j , Z and u k，j , in order to minimize computational distortion while ensuring perceptual efficiency: in, Indicates computational distortion; r k，j represents the minimum achievable rate required for the jth perceived signal at the kth UE; P max，k represents the maximum transmit power budget of the kth UE; ∈ is the stop criterion threshold; represents the cascaded complex path gain, represents the pilot vector received by different subcarriers, and n represents additive white Gaussian noise.

3. The RIS-assisted communication-awareness-computing integrated efficient data processing method according to claim 2, characterized in that: First, the optimization problem is divided into two sub-problems using the substitution optimization AO method; then the problem obtained by substitution optimization is transformed into a convex problem through semi-positive definite relaxation SDR, and finally the Newton orthogonal matching pursuit NOMP algorithm and the optimization tool CVX are used to solve the transformed convex problem.

4. A computer-readable storage medium storing one or more programs, wherein the one or more programs include instructions, characterized in that: When the instructions are executed by a computing device, the computing device is caused to perform the steps of the method according to any one of claims 1 to 3.

5. An electronic device, characterized in that: The method comprises one or more processors, one or more memories and one or more programs, wherein the one or more programs are stored in the one or more memories and are configured to be executed by the one or more processors, and the one or more programs include steps for executing the method as claimed in any one of claims 1 to 3.

Images