Hopfield neural network for UWB multiuser detection

The Hopfield neural network (HNN) is introduced in the paper and is proposed as an effective multiuser detection in direct sequence-ultra-wideband (DS-UWB) systems. It can approximate to maximum likelihood (ML) detector by mathematical analysis. According to the HNN-based technique, the computer simulation results show that they have good performances and much lower computational complexity in a multiuser environment.

[1]  Vivien Chu,et al.  Ultra Wideband Signals and Systems in Communication Engineering , 2007 .

[2]  Moe Z. Win,et al.  Ultra-wide bandwidth time-hopping spread-spectrum impulse radio for wireless multiple-access communications , 2000, IEEE Trans. Commun..

[3]  Ryuji Kohno,et al.  Ultra Wideband Signals and Systems in Communication Engineering: Ghavami/Ultra Wideband Signals and Systems in Communication Engineering , 2004 .

[4]  G. G. Stokes.  "J." , 1890, The New Yale Book of Quotations.

[5]  John J. Hopfield,et al.  Neural networks and physical systems with emergent collective computational abilities , 1999 .

[6]  Chia-Hsin Cheng,et al.  Subspace-based Blind Multi-user Detection for TH-UWB Systems in Multi-path Channels , 2008 .

[7]  Sailes K. Sengijpta.  Fundamentals of Statistical Signal Processing: Estimation Theory , 1995 .

[8]  Lu Gao,et al.  Performance analysis of MMSE multiuser detection , 2000, WCC 2000 - ICCT 2000. 2000 International Conference on Communication Technology Proceedings (Cat. No.00EX420).

[9]  Ryuji Kohno,et al.  Optimum multi-user detection in ultra-wideband (UWB) multiple-access communication systems , 2002, 2002 IEEE International Conference on Communications. Conference Proceedings. ICC 2002 (Cat. No.02CH37333).

[10]  Wu-Shiung Feng,et al.  Performance comparison of PPM-TH, PAM-TH, and PAM-DS UWB Rake receivers with channel estimators via correlation mask , 2005 .

[11]  Deva K. Borah,et al.  Adaptive MMSE maximum likelihood CDMA multiuser detection , 1999, IEEE J. Sel. Areas Commun..

[12]  M. Seidl,et al.  Code division multiple access communications: multiuser detection based on a recurrent neural network structure , 1996, Proceedings of ISSSTA'95 International Symposium on Spread Spectrum Techniques and Applications.

[13]  Sergio Verdu,et al.  Multiuser Detection , 1998 .

[14]  Huaping Liu,et al.  Ultra-wideband for multiple access communications , 2005, IEEE Communications Magazine.

[15]  Elias S. Manolakos,et al.  Hopfield neural network implementation of the optimal CDMA multiuser detector , 1996, IEEE Trans. Neural Networks.

[16]  Evaggelos Geraniotis,et al.  Iterative multiuser detection for coded CDMA signals in AWGN and fading channels , 2000, IEEE Journal on Selected Areas in Communications.

[17]  Bernd-Peter Paris,et al.  Neural networks for multiuser detection in code-division multiple-access communications , 1992, IEEE Trans. Commun..

[18]  Tan-Hsu Tan,et al.  Performance analysis of multi-user DS-UWB system under multipath effects , 2008, ICC 2008.

[19]  J. Foerster,et al.  Channel modeling sub-committee report final , 2002 .

[20]  Nirwan Ansari,et al.  Computational Intelligence for Optimization , 1996, Springer US.

[21]  Urbashi Mitra,et al.  Neural network techniques for adaptive multiuser demodulation , 1994, IEEE J. Sel. Areas Commun..

[22]  Janos Levendovszky,et al.  STOCHASTIC HOPFIELD NETWORK FOR MULTI-USER DETECTION , 2000 .

[23]  A.A.M. Saleh,et al.  A Statistical Model for Indoor Multipath Propagation , 1987, IEEE J. Sel. Areas Commun..