CN-116456463-B - Intelligent reflection surface-assisted safety symbiotic radio system design method

Abstract

A design method of an intelligent reflection surface-assisted safety symbiotic radio system comprises the following steps of establishing a system and a signal model, designing a user side receiving scheme, jointly designing PT precoding vectors and RIS reflection coefficients, providing an optimization problem of minimizing PT transmitting power under the constraints of PU SNR and SUBER, converting the provided optimization problem, and solving the optimization problem by adopting an AO-based optimization algorithm and SDR technology. The method improves the prior RIS-assisted SR network, and by jointly designing PT precoding vectors and RIS phase shift coefficients, the transmitting power is minimized under the conditions of PU and SU performances and RIS constant modulus constraint, so that the performance of a wireless communication system is met, the overall power consumption is reduced, the communication of the wireless communication system is ensured, and higher safety is ensured compared with the prior art.

Inventors

• CAI SHU
• ZHANG JIE
• ZHANG JUN
• ZHANG QI
• CHENG YULUN

Assignees

• 南京邮电大学

Dates

Publication Date

20260505

Application Date

20230423

Claims (4)

1. 1. The intelligent reflection surface assisted safety symbiotic radio system design method is characterized by comprising the following steps of: step1, a system and a signal model are established, and a user side receiving scheme is designed; the system comprises a main transmitter PT, a reconfigurable intelligent surface RIS, a single antenna main user PU and Secondary user SU, wherein PT is provided with Root antenna and RIS is equipped with Independent passive reflection units, PT schedule transmission to PU Data symbols While RIS transmits to SU by means of reflected signals while assisting PT transmission Data symbols , And Is a symbol set; For the user terminal receiving scheme, the PU terminal adopts a maximum likelihood ML detector to decode the main information Sum and secondary information In step 1, for a user terminal receiving scheme, the SU terminal decodes the secondary information using a receiving scheme based on hypothesis testing : Step2, joint design of PT precoding vectors And RIS reflectance The optimization problem of minimizing PT transmitting power under the constraints of PU signal-to-noise ratio SNR and SU bit error rate BER is proposed; in step 2, PT precoding vectors are jointly designed And RIS reflectance The optimization problem of minimizing PT transmit power under PU SNR and SU BER constraints is presented as: Wherein the constraint first constraint is the SNR constraint of the PU, For a set PU SNR threshold, the second constraint is the BER constraint of the SU, To define the threshold for bit error rate, the third constraint is the unit constant modulus constraint of RIS, min represents the minimization operation, s.t. represents the constraint, Represent the first The reflection coefficient of the light is calculated, Representing the norm square; Step 3, converting the provided optimization problem and solving the problem by adopting an AO-based optimization algorithm and an SDR technology; converting the PU signal-to-noise ratio SNR constraint and the SU bit error rate BER constraint in the optimization problem, further converting the minimized PT transmitting power problem into two sub-problems respectively, and solving the optimization problem to obtain an approximate optimal solution; in step 3 Substituting the PU SNR constraint, converting the PU SNR constraint into: Wherein the method comprises the steps of , For the channel between the PT and the RIS, For the channel between the PT and the PU, For the channel between the RIS and the PU, Power being additive white gaussian noise; in step 3, the SU BER constraint is converted into: When (when) When the SU error rate constraint is: Wherein the method comprises the steps of And at this time , And Is a signal Gaussian distribution of (c) Is used to determine the parameters of the parameters, For the channel between the PT and the SU, Is the channel between RIS and SU; When (when) And (3) obtaining: Wherein the method comprises the steps of And at this time ; According to And The problem of minimizing PT transmitting power is respectively converted into the following two problems, the following two problems are caused Two sets of solutions, denoted as the following two optimization problems, respectively: Wherein arg min represents a minimization operation, The number of independent passive reflection units for RIS, then the objective function value When the final solution of the problem is Otherwise, be ; For the case where PT knows CSI, the problem of finding a heuristic solution, i.e. minimizing the transmit power, is expressed as: The method adopts an AO-based optimization algorithm and an SDR technology to solve, and comprises the following specific steps: Updating Solving the following optimization problem pair Updating: where tr denotes the trace of the matrix and rank denotes the rank of the matrix, relaxing the rank-1 constraint to The problem is converted into a convex semi-definite programming SDP problem, the problem is solved by an interior point method, and the original problem optimal solution is constructed by the relaxation problem solution through rank one decomposition because the original problem only comprises two inequality constraints ; Updating Updating by solving the following optimization problem : Converting SU BER constraint into objective function, and establishing SU receiving performance optimization problem under PU performance constraint, namely: Wherein the method comprises the steps of Order-making And utilize the equation The objective function is rewritten as: Wherein the method comprises the steps of Definition of The constraint is rewritten as: Wherein the method comprises the steps of ; Thus, the RIS reflectance optimization sub-problem is expressed as: Where max represents the optimization operation and diag represents the diagonal of the matrix, relaxing the rank-1 constraint to The relaxed problem is a convex SDP problem, the solution is carried out by an interior point method, and the approximate optimal solution of the original problem is obtained by a Gaussian randomization method based on the optimal solution of the relaxed problem.
2. 2. The method for designing an intelligent reflective surface assisted security co-occurrence radio system according to claim 1, wherein in step 1, the channel between PT and RIS is The channel between PT and PU is The channel between PT and SU is The channel between RIS and PU is The channel between RIS and SU is , Representing the complex domain, the channel is in Obeying quasi-static block fading for the coherence time and known at the PT end; the RIS reflectance is expressed as: Wherein the method comprises the steps of Is the first The reflection angle of the individual reflection units, The received signals at the PU and SU are then represented in turn as: Wherein, the Represents the hermite transpose; Transmitting a precoding vector for the PT; Is the RIS reflection coefficient correlation matrix; is the transmitted signal at PT, RIS passes Controlling the reflected channel parameters, thereby realizing symbol transmission; And Is zero in mean value and power is Additive white gaussian noise of (c).
3. 3. The method for designing an intelligent reflective surface assisted security co-occurrence radio system as defined in claim 2, wherein in step 1, the PU end decodes the main information using a maximum likelihood ML detector Sum and secondary information The method comprises the following steps: Wherein the method comprises the steps of Representing vectors Estimate of (1) Thereby obtaining PU decoding under ML scheme The average signal-to-noise ratio SNR of (a) is: 。
4. 4. The method for designing an intelligent reflection-assisted security co-occurrence radio system according to claim 3, wherein in step1, the SU-end decodes the secondary information using a reception scheme based on hypothesis testing : To introduce a hypothesis-based SU reception scheme, it is provided that the RIS modulates BPSK with binary phase shift keying, thereby According to Equal to 0 or 1, received signal Represented as And Two hypotheses, namely For unknown PU signals Approximating it at the SU end as a gaussian distribution with mean zero variance of 1, thereby obtaining Obeying gaussian distribution Wherein: Will be connected with The correlated received signal is represented as a vector When (1) When the two are independent of each other, Are also independent of each other, at this time ; In the case of the ML of the light, Is achieved by the following likelihood ratio test: Wherein the method comprises the steps of In order to receive the energy of the signal, Representing received signals Under the assumption that The probability density function PDF below, when the relative value is large based on the above test And when the BER closed solution is as follows: Wherein the method comprises the steps of , And According to the detection process, SU does not need demodulation 。

Description

Intelligent reflection surface-assisted safety symbiotic radio system design method Technical Field The invention relates to the technical field of wireless communication, in particular to an intelligent reflection surface-assisted safety symbiotic radio system design method. Background Energy efficiency (ENERGY EFFICIENCY, EE) and spectral efficiency (Spectrum efficiency, SE) are two key performance indicators of Sixth generation (6G) wireless communication networks due to the ultra-large-scale connectivity requirements that exist in future internet of things (Internet of Things, ioT) scenarios such as smart cities and factories. Symbiotic radios (Symbiotic radio, SR) based on reconfigurable smart surfaces (Reconfigurable intelligent surface, RIS) are a promising technology to achieve both high EE and SE. SR utilizes cognitive backscatter communications to achieve reciprocal spectrum sharing and highly reliable backscatter communications. The SR consists of two subsystems, a primary system and a secondary system. In the Primary system, the Primary transmitter (PRIMARY TRANSMITTER, PT) uses active Radio to transmit information to a Primary User (PU), while in the Secondary system, the RIS uses backscatter Radio as a Secondary transmitter (Secondary transmitter, ST) to transmit Radio Frequency (RF) signals to a Secondary User (SU) by periodically switching load impedance. In addition, RIS is an innovative technology, which can intelligently improve communication environment and enhance signal transmission. In recent years, research using RIS-assisted SR networks has received increasing attention, which not only improves the transmission performance of PUs but also enables SU communication. A common feature of the existing technology is that both PU and SU end use maximum likelihood detection (Maximum likelihood, ML) to receive information from Base Station (BS) and RIS, thus there is a certain requirement on the computational power of the receiving end. When the SU does not have sufficient computational power, the ML scheme cannot be used. Second, the ML scheme also requires that the received signal power of the SU be large enough to properly demodulate the main information, wasting transmit power when the main information is not what the SU needs. In addition, SU demodulating the master information may also cause potential information leakage of the PU, compromising its communication security. Disclosure of Invention Based on the background technology, the invention provides an intelligent reflection surface assisted safety symbiotic radio system design method, which improves the prior RIS assisted SR network, adopts a receiving method based on hypothesis test to only receive information from RIS at the SU end, and not only supports communication of RIS enabled SU, but also improves safety and energy efficiency of communication from PT to PU. The passive beamforming of the pre-coding vector of the PT and the RIS are jointly designed to minimize the PT transmit power under the QoS constraints of the PU and SU. The above-mentioned optimization problem is non-convex, and is solved by using an iterative algorithm based on alternating optimization (ALTERNATING OPTIMIZATION, AO) and a semi-definite relaxation technique (SEMIDEFINITE RELAXATION, SDR). The safety performance of the proposed system is verified by simulation results to be superior to that of the traditional communication scheme. An intelligent reflection surface assisted safety symbiotic radio system design method comprises the following steps: step1, a system and a signal model are established, and a user side receiving scheme is designed; The system comprises a main transmitter PT, a reconfigurable intelligent surface RIS, a single antenna main user PU and a secondary user SU, wherein the PT is provided with a root antenna and the RIS is provided with an independent passive reflection unit; For the user side receiving scheme, the PU side adopts a maximum likelihood ML detector to decode the main information and the secondary information, and in step 1, for the user side receiving scheme, the SU side adopts a receiving scheme based on hypothesis testing to decode the secondary information: Step 2, jointly designing PT precoding vectors and RIS reflection coefficients, and solving the optimization problem of minimizing PT transmitting power under the constraint of PU signal-to-noise ratio SNR and SU bit error rate BER; Step 3, converting the provided optimization problem and solving the problem by adopting an AO-based optimization algorithm and an SDR technology; and converting the PU signal-to-noise ratio SNR constraint and the SU bit error rate BER constraint in the optimization problem, further converting the minimized PT transmitting power problem into two sub-problems respectively, and solving the optimization problem to obtain an approximate optimal solution. The beneficial effects achieved by the invention are as follows: (1) The prior RIS-ass