基于大规模MIMO-OFDM系统的5G通信信道估计算法研究

Research on Channel Estimation Algorithm for 5G Communication Based on Massive MIMO-OFDM System

信道估计对宽带无线移动通信系统的具体实现至关重要。本文介绍了大规模MIMO-OFDM系统的通信原理,指出5G无线信道存在的局限性,再根据信道衰落、多径效应等问题的成因,提出基于压缩感知理论的信道估计算法,并以MATLAB为仿真平台,设置了载波数量、稀疏度、载波频率等仿真参数,在不同的信噪比下开展了算法性能检验。结果显示,稀疏度自适应匹配追踪算法的性能表现最佳。

Channel estimation is crucial to the realization of broadband wireless mobile communication systems.Hence,this paper introduces the communication principle of large-scale MIMO-OFDM system,expounds the limitations of 5G wireless channel,and then proposes the channel estimation algorithm based on compressed sensing theory according to the causes of channel fading and multi-path effect,sets the simulation parameters such as carrier quantity,sparsity,and carrier frequency in MATLAB platform,and carries out the algorithm performance test under different signal-to-noise ratios.The results suggest that the sparsity-adaptive matching tracking algorithm has the optimal performance.