Design And Optimization Of Transmission Schemes For Intelligent Reflecting Surface Aided Communication Systems

To establish the Internet-of-Things(IoT)ecosystem and support emerging appli-cation scenarios,the next-generation mobile communication network needs to achieve greater coverage,higher spectrum/energy/cost efficiency,stronger reliability,and lower transmission delay.This puts forward more stringent requirements on wireless commu-nication networks.Traditional communication technologies such as multi-antenna and coding modulation can only passively adapt to complex wireless transmission environ-ments and have defects such as high complexity and high cost.In order to improve the condition of the signal transmission environment,intelligent reflecting surface(IRS)technology has been proposed.By intelligently reconfiguring the reflection coefficient of each reflecting element on the IRS,the IRS can change the phase and amplitude of the incident signal,thereby reshaping the wireless transmission environment.Besides,the IRS is light and thin,easy to deploy,and has a low manufacturing cost.Various ex-cellent characteristics of IRS make it a promising technology with great potential in the next generation of communication.However,the optimal design of IRS-aided wireless communication systems also faces lots of new challenges.For example,how to opti-mize the coefficient of each reflecting element on the IRS to achieve different optimiza-tion goals? How to design a more appropriate transmission strategy to fully unlock the performance gain of IRS? In order to solve the above problems,this work investigates the design and optimization of the transmission schemes for IRS-aided communication systems,and has achieved some interesting results,which are briefly summarized as follows.· In order to reduce the total transmission delay of the multi-user(MU)uplink data transmission system,this work considers introducing IRS between the base sta-tion and users to improve the condition of the signal transmission environment.Besides,to unlock the full potential of IRS,a new IRS-aided multiple access strat-egy is custom designed for the considered system,which combines the benefits of IRS-aided time division multiple access(TDMA)and IRS-aided non-orthogonal multiple access(NOMA)technologies.The proposed IRS-aided hybrid multi-ple access(HMA)scheme can significantly reduce the total transmission delay by exploiting the additional gain brought by the dynamic IRS beamforming of the TDMA scheme,as well as the high spectral efficiency of the NOMA scheme.Two typical communication scenarios are investigated,namely the transmit power limited case and the transmit energy limited case,where the device’s rearranged order,time and power allocation,as well as IRS beamforming patterns are jointly optimized to minimize the sum transmission delay.Besides,the performance of the proposed IRS-aided HMA scheme is compared with the IRS-aided TDMA scheme and IRS-aided NOMA scheme through theoretical analysis.After that,low-complexity efficient algorithms are proposed to solve the corresponding op-timization problems by utilizing alternating optimization,successive convex ap-proximation(SCA)and fractional programming method.The simulation results verify the accuracy of the aforementioned theoretical analysis and the superiority of the proposed strategy compared to other benchmarks,and reveal the advantages of introducing IRS into the system.· To avoid the performance degradation caused by non-ideal settings in practical applications,the joint beamforming design for IRS-aided downlink MU multiple-input multiple-output system under imperfect channel state information(CSI)is investigated this work,where the reflection coefficients of IRS need to satisfy the discrete phase constraints.Based on this system model,a weighted sum rate maxi-mization problem is established.To solve the multi-variable coupling non-convex problem,the original problem is equivalently transformed to the corresponding weighted minimum mean square error minimization problem by utilizing the prop-erties of the optimal solution.The closed-form expressions of the key variables are derived based on their statistical properties and the proposed channel estimation er-ror model.Besides,two effective algorithms for the solution of IRS beamforming design are provided.The convergence and effectiveness of the proposed joint op-timization algorithms are verified by the simulation results.Moreover,it is found that under imperfect CSI,even with low-resolution phase shifters at the IRS,the IRS can still significantly improve the weighted sum rate of the system.· To achieve the sustainability of IoT devices,this work further introduces wireless energy transmission technology into the wireless data transmission system,and in-vestigates the IRS-aided wireless powered communication networks(WPCNs).To alleviate the influence of double fading in IRS-related channels,this work adopts active IRS to assist the energy and information transmission,and compares it with passive IRS-aided WPCNs.To balance system performance and computational complexity,three IRS beamforming strategies are considered(i.e.,user-adaptive IRS beamforming,uplink-adaptive IRS beamforming,and static IRS beamform-ing).After deeply exploring the structure of the optimization problems,an al-ternating optimization based algorithm is proposed by utilizing the SCA method,whose effectiveness is validated by the simulation results.Besides,the benefits of applying active IRS in WPCNs are also verified.