Multi-user detection based on neural network for multi-carrier code division multiple access systems | ||||
The International Conference on Electrical Engineering | ||||
Article 18, Volume 6, 6th International Conference on Electrical Engineering ICEENG 2008, May 2008, Page 1-11 PDF (134.28 K) | ||||
Document Type: Original Article | ||||
DOI: 10.21608/iceeng.2008.34205 | ||||
View on SCiNiTO | ||||
Authors | ||||
Necmi Taşpinar1; Metin Çiçek2; Yalçin Işik3 | ||||
1Department of Electrical and Electronic Engineering, Erciyes University, Kayseri, Turkey | ||||
2Graduate School of Natural and Applied Sciences, Erciyes University, Kayseri, Turkey. | ||||
3Silifke-Taşucu Vocational High School, Selçuk University, ççel, Turkey. | ||||
Abstract | ||||
Abstract: In this paper, we present fundemental linear multiuser detection (MUD) techniques and compare them with the technique based on neural network (NN) in multicarrier code division multiple access (MC-CDMA) systems. In a MC-CDMA system, increasing with the number of users, receiver’s bit error rate (BER) performance goes up. Also, the system’ s performance is effected by the power level differences among the users. Simulation results demostrate the higher performance of NN receiver compared to conventional receiver (matched filter) for MC-CDMA. And also, performance results show that the NN structure, gives nearer results comparing to decorrelator and MMSE receivers. Simulations implemented in MATLAB program and performances are examined for synchronous communication and AWGN channels. The Levenberg- Marquardt algorithm is used as the learning algorithm for NN. | ||||
Keywords | ||||
Multiuser detection (MUD); MC-CDMA; Neural network | ||||
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