Research On Beamforming Design And Algorithm For Reconfigurable Intelligent Surface Enhanced MIMO Symbiotic Radio Systems

With the continuous increase of Internet of Things(IoT)devices,and the diversification of IoT application scenarios,researchers urgently need to seek new communication technologies to enhance energy and spectral efficiency in wireless communication,while minimizing the cost of new deployments.Symbiotic Radio(SR),as a potential technology to promote the green Internet of Everything,has been widely studied by scholars at home and abroad.Specifically,the SR system consists of a Primary Transmitter(PTx),a Backscatter Device(BD),and a Receiver(Rx).The BD can load its own information onto the RF signal from the PTx,and reflect it to the Rx to achieve low-power information transfer.In addition,the Reconfigurable Intelligent Surface(RIS)can adjust the direction of the reflected electromagnetic wave beam or polarization direction of the incident signal,etc,so as to achieve the purpose of improving channel capacity or reducing signal interference.While being green,energy-saving,and easy to deploy,RIS can also backscatter its own information to Rx,so it is often introduced into the SR system as a secondary transmitter(STx)to assist the transmission of the primary signal.In order to improve the performance of the IoT system and reduce the total energy consumption on the basis of ensuring signal performance,this thesis constructs the RIS enhanced Multiple-Input Multiple-Output(MIMO)SR system.Then,based on the model,this thesis will study the system-related beamforming design and algorithm to improve the bit error rate(BER)performance and minimize the total system energy consumption.Considering BER as a key indicator to measure system performance,this thesis first constructs a RIS-enhanced MIMO SR system for the purpose of enhancing the performance of the BER of the system,in which the primary system is the Single-Input Multiple-Output(SIMO)structure and the secondary system is the MIMO structure.As the STx,RIS improves the freedom of the reflection coefficient desig,which can effectively alleviate the double fading in the SR system,and then assist the detection of signals at the Rx.In the existing relevant research,there is little content on the analysis and optimization of BER,so this thesis first derives and analyzes the detailed expression of the BER of the primary and the secondary signal in the RIS enhanced SR system,and then takes the BER of the primary signal as the objective function.Based on the energy constraint of RIS,this thesis proposes a two-step optimization algorithm combined with the semidefinite relaxation algorithm(SDR)and the one-dimensional search method,then effectively designs the reflecting beamforming of RIS,which ultimately reduces the BER of primary signal.Through a large number of simulations,this thsis first proves the accuracy of the derived BER expressions.After comparing with the random beamforming scheme,it can be clearly observed that the two-step optimization algorithm is significantly better than the random beamforming scheme,which effectively enhances the BER performance of the primary and the secondary signals.In order to improve the system model and reduce the total energy consumption of the IoT system while ensuring the signal performance,this thesis further considers the SR system with MIMO primary system,and studies the related beamforming design to minimize energy consumption of the RIS enhanced MIMO SR system.In this system,a base station(BS)with multiple antennas is set as the PTx to send the primary signal,whose transmitting beamforming can be adjusted simultaneously with the reflecting beamforming of RIS,providing more freedom to optimize the total energy consumption.Unlike many existing studies that set up single-pass signals,this thesis will construct the system with multi-channel secondary signals,and then study the signal to noise(SNR)expressions of the primary and secondary signals.Considering the promotion of the development of green IoT,this thesis establishes and analyzes the energy consumption model of the RIS enhanced MIMO SR system.Aiming to minimize the total energy consumption of the system,this thesis uses an alternating optimization algorithm based on successive Convex Approximation(SCA)and SDR,which reduces the total energy consumption of the system.Thus,the effectiveness of the optimization algorithm is proved.In addition,the energy consumption model of traditional small cell assisted MIMO backscatter system is established for comparison.The results show that,under the same settings,the total energy consumption of the RIS enhanced MIMO SR system is always lower than the total energy consumption of the comparison system,which highlights the superiority of RIS and SR systems.