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A Multiuser Detector Based on Artificial Bee Colony Algorithm for DS-UWB Systems

机译:一种基于人工蜂菌落算法的多用户探测器DS-UWB系统

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Artificial Bee Colony (ABC) algorithm is an optimization algorithm based on the intelligent behavior of honey bee swarm. The ABC algorithm was developed to solve optimizing numerical problems and revealed premising results in processing time and solution quality. In ABC, a colony of artificial bees search for rich artificial food sources; the optimizing numerical problems are converted to the problem of finding the best parameter which minimizes an objective function. Then, the artificial bees randomly discover a population of initial solutions and then iteratively improve them by employing the behavior: moving towards better solutions by means of a neighbor search mechanism while abandoning poor solutions. In this paper, an efficient multiuser detector based on a suboptimal code mapping multiuser detector and artificial bee colony algorithm (SCM-ABC-MUD) is proposed and implemented in direct-sequence ultra-wideband (DS-UWB) systems under the additive white Gaussian noise (AWGN) channel. The simulation results demonstrate that the BER and the near-far effect resistance performances of this proposed algorithm are quite close to those of the optimum multiuser detector (OMD) while its computational complexity is much lower than that of OMD. Furthermore, the BER performance of SCM-ABC-MUD is not sensitive to the number of active users and can obtain a large system capacity.
机译:人造蜜蜂菌落(ABC)算法是一种基于蜂蜜蜜蜂群的智能行为的优化算法。开发了ABC算法以解决优化数值问题,并揭示了处理时间和解决方案质量的预览结果。在ABC中,人工蜂殖民地寻求富人的人工食物来源;优化数值问题被转换为查找最小化目标函数的最佳参数的问题。然后,人工蜜蜂随机发现初始解决方案的群体,然后通过采用行为来迭代地改善它们:通过邻居搜索机制转向更好的解决方案,同时放弃差的解决方案。本文提出了一种基于次优代码映射多用户检测器和人造群菌落算法(SCM-ABC-MUD)的有效多用户检测器,并在添加白色高斯的直接序列超宽带(DS-UWB)系统中实现噪声(AWGN)频道。仿真结果表明,该算法的BER和近距离效应电阻性能非常接近最佳多用户检测器(OMD),而其计算复杂性远低于OMD的那些。此外,SCM-ABC-MUD的BER性能对有源用户的数量不敏感,并且可以获得大的系统容量。

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