Transmission Design For Intelligent Reflecting Surface-Aided Multi-Antenna Systems With Finite Alphabet Inputs

With the exponential growth in the number of mobile users and end devices and the rapid development of various emerging smart technologies,there is a huge demand for the communication quality and performance of wireless systems.Using intelligent reflecting surface(IRS)to realize intelligent reconfigurable radio wave propagation environment has become a key issue of beyond fifth generation(B5G)and even sixth generation(6G)mobile communication technologies and is expected to solve the problem of increasing communication needs.By dynamically adjusting the reflective phase shift of its passive reflecting elements,IRS can provide the transmitter with an effective reflective path in addition to the direct link,thereby improving the signal propagation environment,extending the signal coverage and enhancing the performance of the wireless communication system.However,given the special structure of IRS,it is a great challenge to combine the transmit signal processing and the IRS phase shifts for high performance and low complexity joint transmission design.On the other hand,although there has been a lot of work investigating the transmission design of IRS-aided wireless communication systems,the vast majority of these studies have been carried out under the assumption of ideal Gaussian inputs,which are fundamentally different from the finite-alphabet inputs used in real world,such as phase shift keying(PSK)and quadrature amplitude modulation(QAM)of the input signals.For these reasons,work has been carried out in this paper on the following points:First,the transmission design for IRS-aided multiple-input single-output(MISO)simultaneous wireless information and power transfer(SWIPT)system with Gaussian inputs and finite-alphabet inputs is investigated,and an alternating optimization(AO)-based mutual information maximization algorithm is proposed for two cases of perfect and imperfect channel state information(CSI),respectively.For the perfect CSI case,the transmit beamforming vector and the IRS phase shift matrix in the mutual information maximization problem are optimized by the semidefinite relaxation(SDR)technique and the penalty-based manifold optimization(PMO)algorithm respectively,subject to the constraints of transmit power,energy harvesting threshold and IRS phase shift matrix.For the case of imperfect CSI,the worst-case optimization problem in the channel uncertainty region is considered and the optimization of the transmit beamforming and phase shifts is accomplished by combining the S-Procedure and SDR techniques.Simulation results show that the proposed transmission design algorithm provides significant gains to the system.Then,the transmission design for IRS-aided multiple input multiple output(MIMO)SWIPT system with finite-alphabet inputs is investigated.In the case of perfect CSI,an AO algorithm based on the successive convex approximation(SCA)technique and PMO is proposed to solve the problems of mutual decoupling of the transmit precoder and the IRS phase shift matrix and the non-convex constraint on the energy harvesting threshold.For the case of imperfect CSI,this paper investigates the mutual information maximization problem from the perspective of the worst-case CSI estimation to improve the lower bound of the system performance in the channel uncertainty region.Then,an AO algorithm combining SCA,S-Procedure and SDR is proposed for this problem.Simulation results show that the proposed transmission optimization algorithm substantially outperforms the benchmark scheme including transmission design with Gaussian inputs.Finally,the transmission design for IRS-aided MIMO cognitive network system based on finite-alphabet inputs with different CSI estimation error models is investigated.For the statistical CSI error model,an AO algorithm in the stochastic successive convex approximation(SSCA)framework is proposed to maximize the mutual information expectations under imperfect CSI.For the part of the bounded CSI error model,a joint optimization algorithm combining SCA,SDR and S-Procedure is proposed,in addition to the assumption of imperfect estimation of all channels of the system.Simulation results demonstrate the robustness of the proposed algorithm for different CSI estimation error models.