System Modeling And Performance Optimization Of A Novel Wireless Network Based On Reconfigurable Intelligent Surface

As the development phase of the next generation wireless network,the sixth generation(6G)communication network has the characteristics of faster speed,larger scale and higher reliability than the fifth generation(5G)communication network.However,the energy consumption and hardware costs caused by the large number of nodes and active antennas in the network have become urgent problems to be solved in the 6G communication network.As one of the key technologies for 6G network research,reconfigurable intelligent surface(RIS),which is composed of a large number of low-cost,programmable,and easy-to-deploy electromagnetic passive components,can effectively solve the above problems.At the same time,by controlling the adjustable components on the RIS,the phase,amplitude and other parameters of the incident signal on the RIS surface can be dynamically adjusted to realize a reconfigurable wireless environment,which can improve the efficiency of signal reception at the receiving point and improving the communication channel to reduce the signal loss in the network.Therefore,some previous researches have applied the RIS to Massive multiple input and multiple output(Massive MIMO)networks,wireless powered communication networks(WPCN),integrated sensing and communication(ISAC)networks.However,on the one hand,most of the RIS deployed in the communication channel were reflective-ony RIS,which only achieved the half-space coverage and limited the practical application of the RIS.On the other hand,with the increase of the number of active antennas in the Massive MIMO network,the high energy consumption in the traditional fully-digital transmitter has become a urgent factor that limits the development.Therefore,aiming at the problems in the typical application scenarios of RIS,the thesis innovatively establishes the novel system models,namely the simultaneously transmissive and reflective reconfigurable intelligent surface(STAR-RIS)based WPCN,and the intelligent transmissive surface(ITS)aided transmitted in Massive MIMO network and ISAC systems.At the same time,by designing variables such as time allocation,transmitter beamforming,and phase shift parameters of the RIS,this thesis focuses on the network performance optimization with the help of the new system design.The main contributions of the thesis are as follows:1.Aiming at the problem of half-space coverage caused by the reflective-only RIS in WPCN,the thesis is the first to adopt the STAR-RIS with the time splitting(TS)working mode and establish a new WPCN system model with multi sensor node groups and full space coverage with the help of STAR-RIS.By establishing the sum throughput maximization problem based on the time variables allocated to nodes and the phase shifts of the STAR-RIS,it can verify the improvement of the STAR-RIS in the efficiency of the energy transmission and information transmission.In order to solve the proposed nonconvex optimization problem,the thesis further proposes a low-complexity optimization method based on Lagrangian duality and two-level iterative algorithm to simplify the objective function,which can obtain the closed-form solution of the time allocation variables.Also,Majorization-Minimization(MM)and complex circular manifolds(CCM)are used to optimize the phase shifts of STAR-RIS in the wireless energy transmission phase.Finally,by comparing with the simulation results of the benchmark schemes,it can verify the accuracy of the proposed scheme and the improvement of the sum throughput.2.Aiming at the problem of excessive energy consumption in traditional fullydigital transmitters,the thesis adopts ITS-aided transmitter as an effective alternative.At the same time,in order to suppress the high sidelobes in the transmit beam,the thesis innovatively introduces a cost function based on least squares and applied to the ITS-aided transmitter.The proposed cost function is minimized by jointly controlling the digital beamforming vector of the base station(BS)and the phase shifts of the ITS,which thereby suppresses sidelobes and optimizing the mainlobes of the transmit beam to make it point to the receiving user.In order to solve the proposed minimization problem,the thesis adopts a effective algorithm based on alternating iterative optimization(AO)to decouple the variables,while the Lagrangian dual method and the alternating direction method of multipliers(ADMM)algorithm are utilized to design the closed-form solution of the digital beamforming vector at the BS and obtain the optimal phase shifts of the ITS,respectively.Finally,the improvement of the proposed algorithm on the transmit beam is verified by comparing the simulation results with the benchmark schemes.3.Combining the characteristics of low energy consumption in the ITS aided transmitter and the advantages of the intelligent reflective surface(IRS)assisted communication channel,the thesis is the first to establish a novel system model in the multi-user Massive MIMO network with the help of the ITS aided transmitter and IRS.The proposed new system design can effectively solve the problems of high energy consumption and high cost in traditional fully-digital transmitters,and IRS can improve the communication channel between the transmitter and the receiving nodes.By jointly controlling the beamforming vector at the BS and the passive phase shifts of the ITS and IRS,the proposed novel scheme can maximize the weighted sum rate(WSR)and the energy efficiency(EE).To solve the proposed non-convex optimization problem,a low-complexity algorithm is proposed in which the Lagrangian dual transformation,AO algorithm and quadratic transformation method are used to simplify the objective function.The phase shifts of ITS and IRS and the digital beamforming vector in WSR problem are designed by ADMM algorithm and bisection search method,respectively.Finally,the simulation results are compared with various benchmark schemes to verify the advantages of the proposed algorithm in terms of WSR and EE.4.In order to better design the fusion transmission signal that combines sensing and communication signals into one,and enhance the signal transmission from the transmitter to the sensing and communication target,the thesis is the first to establish the novel system model in the ISAC with the help of the ITS aided transmitter and IRS,which can effectively design the fusion transmission signal and improve transmission channels.By jointly controlling the digital beamforming vector of the BS and the passive phase shifts of the ITS and IRS,the thesis establishes the problem of maximizing the beam pattern gain of the sensing signal sent by the IRS while ensuring that the signal reception of the communication user meets the basic requirements.In order to solve the proposed optimization problem,an algorithm based on penalty factor,Lagrangian dual,successive convex approximation(SCA),and element-by-element iterative optimization is used to jointly optimize the digital beamforming vector at the BS and the phase shifts of the ITS and IRS.Finally,the simulation results are compared with various benchmark schemes to verify the improvement brought by the proposed algorithm.