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Multi User Detection in CDMA System Using Linear and Non Linear Detector
S Parija , S Acharya
Pages - 18 - 33     |    Revised - 30-08-2010     |    Published - 30-10-2010
Volume - 1   Issue - 1    |    Publication Date - December 2010  Table of Contents
DS-Code division multiple access is considered as the third generation of cellular mobile used in interim standard 95(IS-95) [1]and it is currently being standardized for universal mobile telecommunication systems (UMTS). CDMA offers attractive features, such as frequency reuse, soft handoff, increased capacity, and multipath combating. In a CDMA system, several users simultaneously transmit information over a common channel using pre-assigned codes. The conventional single user detector consists of a bank of filters matched to the spreading codes. This detector suffers from two problems. First, multiple access interference (MAI) produced by the other co-channel users is a significant limitation to the capacity of this detector. The second problem is the near-far effect which occurs when the relative received power of interfering signals becomes larger. A potential solution is multi-user detection which exploits the information of signals of interfering users. In the present study performance of various linear detectors like matched filter detector, MMSE detector, and adaptive LMS detector are studied. These are the linear detectors that operate linearly on the received signal statistics and are suboptimal detectors. The matched filter bank is the conventional detector and offers the simplest way of demodulating CDMA signals .The detector resulting from the MMSE (minimum mean square error) criterion shows better performance over the conventional one for low SNR value. Adaptive LMS is employed to enhance the BER performance in MUD application.Several factors motivated the research to apply neural network as multi-user detector. NN are nonlinear classifier in addition to being adaptive and computationally efficient. The performance of two layer perceptron neural network using BP learning rule is used for multi-user detection of CDMA signals in AWGN channels. The neural network detectors show improvement of BER in the comparative analysis done in the present work. and offers further research scope for solving multi-user detection problems in CDMA application.
CITED BY (3)  
1 Chauhan, S., Kumar, V., & Kanwar, V. Multi user detection for ds-cdma system using artificial neural network (ann) with mmse.
2 Chauhan, S., Kumar, V., & Kanwar, V. Multi user detection techniques for ds-cdma.
3 Nemade, S. N., & Kolte, M. T. (2013). Non Iterative Algorithm for Multi-user Detection in DS-CDMA System: An Enhanced Harmony Search Algorithm. International Journal of Computer Applications, 72(7).
1 Google Scholar 
2 CiteSeerX 
3 refSeek 
4 Scribd 
5 SlideShare 
7 PdfSR 
B. S. Sharif, T. C. Chuah, O. R Hinton, S. Jima. ”Perceptron-based CDMA receiver in non-Gaussian noise”. IEEE Trans. on Neural Networks, 8:643-646, 2003
Honig and M. K. Tsatsanis. “Adaptive techniques for multiuse receivers enhanced signal processing with short codes”. IEEE Signal Process.Mag., pp. 49–61 (2000)
Koulakiotis, A. H. Aghvami. “Data detection techniques for DS/CDMA mobile systems: A review”. IEEE Pers. Commun., 7:24–34, 2000
Kung. S Y Taur, J.S. ”Decision based neural networks with signal image classification applications”. IEEE Trans.on.Neural Networks, 6:170-181, 1995
M Benson, Carrasco RA. ”Investigation of diversity combining algorithms for frequency selective fading channels”. IEEE Trans. on Neural network, 8:28-29, 1997
M Benson, Carrasco RA. ”Mobile communication system using neural network approach”. IEEE Trans .on Neural Networks, 4:570-581, 2004
M. Benson ,Carrasco RA. ”Recurrent neural network array for CDMA mobile communication systems”. IEEE Trans. on Neural Networks, 33:2105-2107, 1997
M. G. Shayesteh, H. Amindavar. “Multi user detection in CDMA system using neural network approach”. International standard of Electronics and communications, 54:215- 235, 2004
M. G. Shayesteh, H. Amindavar. ”Performance Analysis of Neural Network Detectors in DS/CDMA Systems”. International standard of Electronics and communications, 55:220- 236, 2003
M. K Varanasi, B. A. ”Near optimum detection in synchronous code-division multipleaccess systems”. IEEE Transon. communication, 39:725-735, 1991
M.Ghotbi and M. R. Soleymani. “Partial parallel interference cancellation of DS-CDMA satellite signals with amplitude and phase estimation”. In Proc.IEEE GLOBECOM, Taipei, Taiwan, pp. 2882–2886, 2002
M.Ghotbi. “Multi-user detection of DS-CDMA signals using parallel interference cancellation in wireless communications”, M.S. thesis, Concordia Univ., Montreal, Canada, Dec. 2001
Nedeljkovic V. “A novel multilayer neural networks training algorithm that minimizes the probability of classification error”. IEEE Trans.on Neural Networks, 4:1993
R.L PickholtzL, B. Milstein, D.L. Schilling. “Spread Spectrum for Mobile Communications”. IEEE Trans. On Vehicular Technology, 40(2):313-322, 2001
R.Lupas, S.V. “Linear multi-user detectors for synchronous code –division multiple access systems”. IEEE Trans.on Information Theory, 35:123-136,1989
Suard B, Xu G, Liu H,Kailath T. ”Uplink channel capacity of space –division-multiple access schemes”. IEEE Trans. on information theory, 4:1468-1476, 1998
Verdù S. “Multi-user Detection”, Cambridge University Press, New York, USA, 40: pp.85- 96 (1998)
Zhou, P. Austin, J. ”Learning criteria for training neural network classifiers”. On Neural Computing & Application, pp. 334–342, 1998
Mr. S Parija
- India
Mr. S Acharya
- India

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