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A Novel Multiuser Detector Based on Restricted Search Space and Depth-First Tree Search Method in DS/CDMA Communication Systems

机译:DS / CDMA通信系统中基于受限搜索空间和深度优先树搜索方法的新型多用户检测器

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摘要

In this paper, we consider an improved and efficient algorithm for the multiuser detection (MUD) in direct sequence/code division multiple access (DS/CDMA) communication systems. The optimum detector for MUD is the maximum likelihood (ML) detector, but its complexity is very high and it calls for an optimization problem that involves an exhaustive search. Consequently, there has been considerable interest in suboptimal multiuser detectors with less complexity and reasonable performance. The idea of reducing the complexity by sub-optimum detectors was efficient and applicable but had some defects. The idea proposed in this paper is the restriction of the search space. This idea comprises using a sub-optimum detector such as ordinary genetic algorithm for which the size of the search space is confined to a predetermined region that is smaller than the whole search space. This limited region includes the objective bit sequence. Then by using depth-first tree search algorithm, we could find the optimum bit stream. We compare our algorithm to the ML detector, the genetic algorithm with conventional detector, and the ant colony optimization (ACO) detector which have been used for MUD in DS/CDMA. Simulation results show that the performance of this algorithm is near the optimal detector with very low complexity, and works better in comparison to other algorithms.
机译:在本文中,我们考虑了一种改进的高效算法,用于直接序列/码分多址(DS / CDMA)通信系统中的多用户检测(MUD)。 MUD的最佳检测器是最大似然(ML)检测器,但是它的复杂性非常高,因此需要涉及穷举搜索的优化问题。因此,人们对具有较低复杂度和合理性能的次优多用户检测器产生了极大的兴趣。通过次优检测器来降低复杂度的想法是有效和适用的,但存在一些缺陷。本文提出的想法是对搜索空间的限制。这个想法包括使用次最佳检测器,例如普通遗传算法,对于该次最佳检测器,搜索空间的大小被限制在小于整个搜索空间的预定区域中。该有限区域包括目标比特序列。然后,通过使用深度优先树搜索算法,我们可以找到最佳比特流。我们将我们的算法与ML检测器,具有常规检测器的遗传算法以及用于DS / CDMA中MUD的蚁群优化(ACO)检测器进行了比较。仿真结果表明,该算法的性能接近最优检测器,且复杂度非常低,与其他算法相比效果更好。

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