一种MIMO-OTFS低复杂度信号检测算法

A low complexity MIMO-OTFS signal detection algorithm

摘要:

由于高速多径环境下频率色散现象严重破坏正交频分复用（OFDM）系统子载波正交性，为解决高速多径环境下的频率色散问题，正交时频空调制技术技术（OTFS）应运而生；而多输入多输出技术（MIMO）具有可以有效提升信道容量和系统可靠性的特点，文章采用了MIMO技术与OTFS技术结合的方法，推导了MIMO-OTFS系统中最大比合并信号检测算法（MRC）理论并加以仿真；针对MIMO-OTFS系统中MRC信号检测算法复杂度过高的情况，提出了一种低复杂度信号检测算法；该算法的基本思想是利用最大比合并方法对时延—多普勒网格中传输符号的接收多径分量进行提取和相干合并，以提高合并信号的信噪比，同时利用Cholesky矩阵分解理论，对信道增益矩阵进行求逆运算的优化，降低了算法复杂度，为MIMO-OTFS系统的实际应用做出贡献；

Abstract:

The frequency dispersion phenomenon under high-speed multipath circumstance significantly influence the subcarriers’ orthogonalitySof the OFDM system. To solve this problem, a multiplexing technique named Orthogonal Time Frequency Space (OTFS) modulation technology has emerged. The application of multiple-input multiple-output (MIMO) over OTFS modulation is named MIMO-OTFS system, which takes both advantage of the channel capacity and reliability benefits of MIMO and the robustness of OTFS in multipath dispersion.SThis paper is concerned with the theory and simulation of Maximum Ratio Merging (MRC) detection algorithm in MIMO-OTFS system. In particular, a low-complexity MRC estimation approach is proposed to reduce the computational cost.To enhance the signal-to-noise ratio of the signal in observation space, MRC algorithm is applied to symbol detection and multipath delay coherent combining process at the receiver (Tx) in delay-Doppler grid. Cholesky decomposition is applied to enhance the performance when evaluating the MIMO-OTFS channel inverse matrix.