Study On Performance Optimization Of MIMO System With Finite-alphabet Inputs

Multiple-input multiple-output(MIMO)technology is widely used in the fourth generation mobile communication system(4G)as an important method to improve the spectrum efficiency of wireless communication system.MIMO technology and its evolution massive MIMO technology will continue to play an important role in the fifth generation mobile communication system(5G).Most of the existing researches on MIMO technology are based on that the channel inputs are Gaussian;however,for the practical communication system,the channel input is discrete finite-alphabet input,such as quadrature amplitude modulation(QAM)or phase shift keying(PSK)modulations.Therefore,the research results based on Gaussian input are not fully applicable to practical communication systems with finite-alphabet input.In view of this,this paper studies the performance optimization of MIMO communication system with finite-alphabet input,including MIMO precoding,MIMO signal detection and MIMO physical layer security.The main contributions and innovations of this paper are as follows:1.We deduce the closed-form expressions of the mutual information of a single antenna system,as well as the lower bound and approximation of the mutual information of MIMO system.With finite-alphabet input,the mutual information of MIMO system has no closed expression and only complex numerical integration can be used for estimating the mutual information.In this paper,we first derive the closed-form expressions of mutual information of a single antenna system,and then the lower bound and approximation are obtained by using Jensen inequality and entropy power approximation.The closed-form expressions,the lower bound,and the approximation can greatly reduce the computational complexity of the mutual information;and more importantly,the closed-form expressions and the lower bound are of great significance to the subsequent performance analysis of MIMO system.2.We propose two efficient MIMO precoding schemes.Transmission precoding is an important technology to improve the spectrum efficiency of MIMO system.Under finite-alphabet inputs,the MIMO precoding scheme involves the calculation of the minimum mean-square error(MMSE)matrix.Due to the complex calculation of mutual information and MMSE matrix,we use the lower bound of the mutual information and ergodic mutual information to design two efficient precoding schemes for static MIMO channel and weichselberger MIMO fading channel,respectively.The precoding scheme based on the lower bound reduces the computational complexity greatly while the performance loss is negligible.3.The physical layer security of MIMO system is studied.Transmission precoding can greatly increase the performance of physical layer security,but the precoding scheme based the optimization of secrecy rate has high complexity.Based on the lower bound of the mutual information,two efficient transmission precoding schemes are proposed for MIMO static channel and Kronecker MIMO fading channel,respectively.Simulation results show that the proposed precoding scheme can greatly reduce the computational complexity.4.We propose an optimal linear detection scheme for maximizing the mutual information of MIMO system.The traditional linear detection scheme is widely used due to its low complexity,but its performance is poor.In this paper,we study how to maximize the mutual information by using linear detection.Based on the relationship between MMSE matrix and mutual information,the necessary conditions for the optimal MIMO linear detection scheme are given.Simulation results show that the performance of the proposed optimal linear detection scheme is better than that of the traditional linear detection scheme.5.We propose an efficient active user detection scheme for multi-user system.For multiuser systems,especially 5G machine-type communication systems,how to design an efficeient algorithm for active user detection and channel estimation is of great importance.In this paper,we first derive the relationship between Reed-Muller sequence and its subsequences;and then,based on this relationship,we design an efficient active user detection and channel estimation algorithm.The simulation results show that the device identification and message decoding scheme developed in this work can serve as the basis for grant-free massive access for billions of devices with hundreds of simultaneously active devices in each cell.