MIMO系统中基于星座约束的LAS检测算法

LAS detection algorithms based on constellation constraints in MIMO systems

似然上升搜索(LAS)算法是一种启发式邻域搜索算法,能够对空分复用的大规模多输入多输出(MIMO)系统的接收信号进行检测。为了降低传统LAS算法的复杂度,提出了一种基于星座约束(CC)的CC–LAS算法。该算法利用一个星座约束(CC)结构判定每个候选解的可靠性,根据可靠性判定结果缩小候选解的邻域空间,再利用LAS算法对不可靠候选解进行检测。提出的CC–LAS算法通过忽略LAS邻域空间中大量不必要的邻居向量,排除对低可靠度信号的低效处理,从而大幅度降低了传统LAS算法的计算复杂度。仿真结果表明,提出的CC–LAS算法的误码率(BER)性能与传统的LAS算法非常接近,并且在信噪比(SNR)相同的情况下,能够大幅度降低计算复杂度。

The Likelihood Ascend Search(LAS)algorithm is a heuristic neighborhood search algorithm that detects the received signals of large–scale Multiple–Input–Multiple–Output(MIMO)systems with space–division multiplexing.A Constellation Constraint–LAS(CC–LAS)is proposed for reducing the computational complexity of the traditional LAS algorithm.The algorithm first introduces a novel CC structure to determine the reliability of each candidate solution.Then,according to the reliability determination result,the neighborhood space of the candidate solution is narrowed.Finally,the unreliable candidate solution is detected by using the LAS algorithm.The proposed CC–LAS algorithm eliminates the inefficient processing of low–reliability signals by ignoring a large number of unnecessary neighbor vectors in the LAS neighborhood space.Hence,CC–LAS algorithm is capable of greatly reducing the computational complexity of the traditional LAS algorithm.The simulation results show that the BER performance of the proposed CC–LAS algorithm is very close to that of the traditional LAS algorithm;nevertheless,the computational complexity can be greatly reduced under the same Signal–to–Noise Ratio(SNR)compared to traditional LAS algorithm.