Research On MIMO Channel Equalization Technology Based On Blind Equalization Algorithm

With the rapid development of technology,mobile communication technology has become a hot topic in the field of modern communication,receiving increasing attention due to its good mobility,scalability,compatibility,and user satisfaction with data transmission rates.Wireless communication channel is an important component of mobile communication systems,so studying and exploring them becomes particularly crucial.In the entire field of wireless communication research,Inter Symbol Interference(ISI)has always been a key factor affecting communication quality.In order to improve communication quality and reduce the impact of inter symbol interference,blind equalization technology is often applied to the receiver to reduce or even eliminate its impact on the wireless channel Due to the fact that the response of wireless channels usually changes over time,adaptive equalizers are generally used for implementation.Adaptive equalizers can automatically adjust coefficients to track channels and have become a crucial technology in wireless communication systems.In response to the above issues,this article first conducts research on blind equalization technology,analyzes the improvement effects of several typical blind equalization algorithms on communication quality,and combines blind equalization algorithms with MIMO channels for improvement,and analyzes and compares the improvement effects on communication quality.This article focuses on the following aspects of research,and the specific research work is as follows:1.Introduced large-scale fading and small-scale fading to illustrate the impact of wireless communication channels on signal transmission.Firstly,the path loss in free space is only related to distance;Secondly,the main causes of small-scale fading are analyzed.Finally,the characteristics of MIMO channels subject to Rayleigh fading are emphatically discussed and modeled.2.Introduced the working principle of blind equalization algorithms,and compared and analyzed the main structures of classical blind equalizers and Decision Feedback Equalization(DFE).We compared and analyzed the Least Mean Square(LMS)algorithm and Recursive Least Squares(RLS)algorithm in blind equalization algorithms.It is pointed out that the performance of blind equalization can be divided into six points:convergence rate,computational complexity,steady-state residual error,ability to track time-varying channels,error rate characteristics,and noise resistance,and they are discussed separately.3.Combining the equalization criteria of blind equalization algorithms and the influencing factors of blind equalization algorithm performance indicators,several commonly used adaptive blind equalization algorithms in Bussgang class blind equalization algorithms were analyzed:Constant modulus algorithm(CMA),CMA-DD algorithm(Constant modulus algorithm-Decision Directed),and MCMA algorithm(Modified Constant modulus algorithm).By using a Quadrature Amplitude Modulation(QAM)input signal modulation and demodulation system,the above three adaptive blind equalization algorithms were modeled and simulated.Several key factors such as step size,residual mean square error(MSE),inter symbol interference(ISI),and convergence performance were analyzed in detail.The simulation results provide the advantages,disadvantages,and applicable conditions of each of the three algorithms,laying the foundation for studying the improvement of MIMO channel communication quality in wireless communication system and the improvement of the Normalized Constant modulus algorithm(NCMA).4.An improved NCMA algorithm is proposed for MIMO channel characteristics in wireless communication system.To solve the problem of signal distortion in MIMO channels,an improved NCMA semi blind equalization scheme based on blind equalization algorithm is proposed.Simulation has shown that the improved NCMA algorithm solves the problem of slow convergence speed in the initial stage of the algorithm,and can also reduce mean square error by controlling the step size in the later stage of the algorithm,greatly improving the communication quality of MIMO channels in wireless communication systems.