MIMO系统双向自适应高斯逼近检测算法

Bidirectional adaptive Gaussian approximation for MIMO systems

针对多输入多输出(MIMO)系统高斯逼近检测算法计算复杂度高,以及在搜索径数较少的时候,可能出现严重的误差传播,导致检测性能下降等问题,对多输入多输出系统检测进行了研究,提出了一种新的双向自适应高斯逼近算法.传统的高斯逼近算法在接收端进行树形搜索,当搜索径数较多时,高斯逼近算法能很好地抑制误差传播,但算法开销很大;当搜索径数较少时,存在严重的误差传播.双向自适应高斯逼近检测算法(BID-A-GA),通过从正向和反向并行地进行检测,判断误差传播是否产生,从而自适应地调整搜索径数,在抑制误差传播的同时,降低了算法复杂度.新的双向自适应检测算法能并行计算,运算时延低,且能在低复杂度情况下有效地抑制误差传播.

A bidirectional detection method was proposed based on Gaussian approximation algorithm to reduce computational complexity and combat error propagation in multiple input multiple output（MIMO） detection.Conventional Gaussian approximation detection executes tree search at the receiver.When the number of searching paths is large,error propagation is well prevented at the cost of high complexity;when few paths are searched,serious error propagation may occur.In the new method,transmitted symbols were estimated parallel both in sequential order and inverse order,and the number of searching paths was determined by comparing the results of bidirectional detection and exploiting the error propagation,which could prevent error propagation at reduced complexity. The novel algorithm could be executed at low delay because of parallel computing,and showed good performance at low complexity.