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基于模拟退火并行进化规划的MIMO-CDMA多用户检测器 被引量:1

Multiuser detector based on simulated annealing parallel evolutionary programming for MIMO-CDMA systems
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摘要 为解决最佳多用户检测计算复杂度高的难题,将多种群并行进化规划和模拟退火两种思想有机地融合起来,提出一种新的模拟退火并行进化规划算法,并应用到MIMO-CDMA系统多用户检测问题求解中。在新算法中,不同的子群并行进行进化过程,利用模拟退火的局部寻优能力,避免单个种群在进化过程中出现的早熟现象,从而加快整个算法的收敛速度。实验结果证明,新的多用户检测器抗远近效应和抗多址干扰的能力都优于传统检测器和单种群的模拟退火进化规划多用户检测器,并且在远近效应和多址干扰存在的条件下,该检测器的收敛速度比单种群模拟退火进化规划检测器提高了约108%和100%。 To resolve high complexity of optimum multiuser detection, Multigroup parallel Evolutionary Programming and simulated annealing are well combined in this paper. The paper apply the hill climbing performance of simulated annealing and the global optimum performance of evolutionary programming, A novel algorithm based on simulated annealing parallel evolutionary programming is proposed and applied to address the MIMO-CDMA muhiuser detection problem. In the algorithm, evolutions of subgroups are parallely performed among subgroups, and the local optimum of simulated annealing is utilized, so this algorithm avoids premature convergence of alone group evolution- ary process and accelerates the convergence speed of the algorithm. Simulation results show that the new muhiuser detector is superior to the conventional detector and the alone group simulated annealing evolutionary programming muhiuser detector in the aspects of near-far effect and multiple-access interference, and the convergence speed in- creased by about 108% ( near-far effect ) and 100% ( multiple-access interference) than the alone group simulated annealing evolutionary programming detector.
出处 《电子测量与仪器学报》 CSCD 2014年第5期514-519,共6页 Journal of Electronic Measurement and Instrumentation
关键词 多输入多输出 多用户检测器 进化规划 并行 MIMO(multiple-input multiple-output) multiuser detector evolutionary programming parallel
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  • 1ASHRAFINIA S, NAEM M. A low complexity evolution- ary algorithm for multi-user MIMO detection [ C ]. Pro- ceedings of IEEE Symposium on Computational Intelli- gence in Muhicriteria Decision-Making, Paris, France, April,2011 : 8-13.
  • 2TAKEUCHI K, VEHKAPERA M. Large-system analysis of joint channel and data estimation for MIMO DS-CD- MA systems [ J ] . IEEE Transactions on Information The- ory,2012,58(3) : 1385-1412.
  • 3SOM P, CHOCKALINGAM A. Muhiuser detection in large-dimension muhicode MIMO-CDMA systems with higher-order modulation[ C]. 2011 Military Communica- tions Conference, USA ,2011:364-370.
  • 4FENG F B ,TSIA SH CH. Adaptive detectors for MIMO DS/CDMA communication systems [ J]. IEEE Transac- tions on Vehicular Technology, 2008, 57 ( 5 ):.3015-3027.
  • 5KECHRIOTIS G, MANOLAKOS E S. Hopfield neural network implementation of the optimal CDMA muhiuser detector [ J ]. IEEE Transactions on Neural Networks, 1996,7( 1 ) :131-141.
  • 6黑永强,李晓辉,易克初,郁光辉.求解多输入多输出检测新算法——遗传粒子群优化[J].电波科学学报,2011,26(1):42-49. 被引量:1
  • 7ISIK Y, TASPINAR N. Multiuser detection with neural network and PIC in CDMA systems for AWGN and Ray- leigh fading asynchronous channels [ J ]. Wireless Per- sonal Communications,2007,43 (4) : 1185-1194.
  • 8SOUJERI E A. DS-CDMA MAl-cancellation using hys- teretic Hopfield neural networks [ C ]. 2006 IEEE Elec- trotechnical Conference, Mediterranean,2006 : 660-663.
  • 9HUANG Y F, YIN D. Genetic-based multi-user detector for multi-carrier CDMA communication systems [ C ]. Proceedings of the l lth IEEE Singapore International Conference on Communication Systems, Guangzhou, Chi- na,2008 : 461-465.
  • 10ABRAO T, CIRIACO F, OLIVEIRA L D. GA, SA, and TS near-optimum muhiuser detectors for s/MIMO MC- CDMA systems[ C]. Fourth International Conference on Wireless Communication and Sensor Networks, India, 2008 : 173-178.

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