【摘要】 利用穷搜索的ML(MaximumLikelihood)联合检测其复杂度随输入长度指数增长,因而在实际系统中很难实现。为此,提出一种用于LAS-CDMA(LargeAreaSynchronousCodeDivisionMultipleAccess)系统联合检测的球译码算法。与原始算法相比,该算法具有更低的复杂度。仿真表明,该算法复杂度能降低大概一半。对初始半径的选择敏感性更低。在初始半径的选择足够大时,即使对于大的调制星座,也可在保证低复杂度的同时取得ML解,对于LAS-CDMA系统,该算法在ML的意义上是最优的。更多还原

【Abstract】 Complexity of ML(Maximum Likelihood) joint detection using exhaust search increases exponentially as input length.Sphere decoding becomes a hot spot because it can achieve ML performance in complexity of polynomial. We propose in a new reduced complexity decoder for CDMA(Code Division Multiple Access) system based on LS code. Compared to the original algorithm, this algorithm has lower computation complexity and is more insensitive to the choice of initial radius. Simulation indicates the complexity can reduce to half of that of original one. Thus, by making the choice of radius sufficiently large, the ML solution is guaranteed with low complexity, even for large constellations, this algorithm is optimal for LAS-CDMA system in the sense of ML.更多还原