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应用科学学报 ›› 2000, Vol. 18 ›› Issue (3): 214-217.

• 论文 • 上一篇    下一篇

变尺度因子暂态混沌神经网络多用户检测器

仲文, 程时昕   

  1. 东南大学无线电工程系移动通信国家重点实验室, 江苏南京 210096
  • 收稿日期:1999-03-09 修回日期:1999-08-07 出版日期:2000-09-30 发布日期:2000-09-30
  • 作者简介:仲文(1968-),女,江苏南京人,博士生;程时听(1936-),男,湖北鄂城人,教授,博导.

Multi-user Detector Using Timevarying Scaling-parameter Transiently Chaotic Neural Network

ZHONG Wen, CHENG Shi-xin   

  1. National Communication Research Laboratory, Department of Radio Engineering, Southeast University, Nanjing 210096, China
  • Received:1999-03-09 Revised:1999-08-07 Online:2000-09-30 Published:2000-09-30

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摘要： 提出一种变尺度因子暂态混沌神经网络,具有较好的逃逸局部最优点的能力,并将其用于实现DS/CD-MA通信系统中的最佳多用户检测器.实验结果表明这种基于变尺度因子混沌神经网络的多用户检测器,其误码率性能优于已有的神经网络多用户检测器,能较好地逼近最佳多用户检测器的性能。

关键词: 远近效应, 多用户检测, 最佳检测, 混沌神经网络

Abstract: The existing neural network multi-user detectors are often trapped in the local minima, resulting in the performance degradation. In this paper, a timevarying scaling-parameter transiently chaotic neural network (TSTCNN) is proposed. The TSTCNN network has powerful capability to escape from getting into the local minima. The TSTCNN network is applied to the optimum detection problem in DS/CDMA systems. Numerical results show that the TSTCNN-based detector can perform better than the existing neural network detectors. The proposed detector can approximate to the optimum detector closely.

Key words: multi-user detection, optimum detection, chaotic neural network, near-far problem

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