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A new support vector machine based multiuser detection scheme

A new support vector machine based multiuser detection scheme
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摘要 In order to suppress the multiple access interference (MAI) in 3G, which limits the capacity of a CDMA communication system, a fast relevance vector machine (FRVM) is employed in the multiuser detection (MUD) scheme. This method aims to overcome the shortcomings of many ordinary support vector machine (SVM) based MUD schemes, such as the long training time and the inaccuracy of the decision data, and enhance the performance of a CDMA communication system. Computer simulation results demonstrate that the proposed FRVM based multiuser detection has lower bit error rate, costs short training time, needs fewer kernel functions and possesses better near-far resistance. In order to suppress the multiple access interference （MAI） in 3G, which limits the capacity of a CDMA communication system, a fast relevance vector machine （FRVM） is employed in the multiuser detection （MUD） scheme. This method aims to overcome the shortcomings of many ordinary support vector machine （SVM） based MUD schemes, such as the long training time and the inaccuracy of the decision data, and enhance the performance of a CDMA communication system. Computer simulation results demonstrate that the proposed FRVM based multiuser detection has lower bit error rate, costs short training time, needs fewer kernel functions and possesses better near-far resistance.
作者 王永建 赵洪林
机构地区 The Research Center on Communication
出处 《Journal of Harbin Institute of Technology(New Series)》 EI CAS 2008年第5期620-623,共4页 哈尔滨工业大学学报（英文版）
关键词 multiuser detection support vector machine relevance vector machine bit error rate 多用户检测 支持向量机 关联向量机 误比特率
分类号 TN91 [电子电信—通信与信息系统]
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  • 1[1]B. Aazhang, B. Paris, G. Orsak, Neural networks for multiuser detection in CDMA communication, IEEE Trans. on Communications, 1992, 40(7), 1212-1222.
  • 2[2]C. Burges, A tutorial on support vector machines for pattern recongition, Data Mining and Knowledge Discovery, 1998, 2(2), 121-167.
  • 3[3]U. Madhow, M. Honing, MMSE interference suppression for direct-sequence spread-spectrum CDMA, IEEE Trans. on Communications, 1994, 42(12), 3178-3188.
  • 4[4]U. Madhow, MMSE interference suppression for timing acquisition and demodulation in directsequence CDMA systems, IEEE Trans. on Communications, 1998, 46(8), 1065 1075.
  • 5[5]G. Proakis, Digital Communication, Third Edition, USA: McGraw-Hill, 1995, 758-833.
  • 6[6]S. Rappaport, Wireless Communications Principles and Practice, USA, Prentice-Hall, 1996, 177181.
  • 7[7]S. Keerthi, S, Shevade, C. Bhattacharyya, K. Murthy, A fast iterative nearest point algorithn for support vector machine classifier design, IEEE Trans. on Neural Networks, 2000, 11 (1), 124-136.
  • 8[1]Verdu S. Multiuser detection[ M]. Cambridge, UK: Cambridge Univ Press, 1998.
  • 9[3]Vapnik V. The nature of statistical learning theory[M]. New York: Springer-Verlag, 1995.
  • 10[4]Chen S, Samingan A K, Hanzo L. Support vector machine multiuser receiver for DS-CDMA signals in multipath channels[J]. IEEE Trans on Neural Networks, 2001,12 (3): 604-611.

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Journal of Harbin Institute of Technology(New Series)
2008年 第5期

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