Taşpinar, N., Çiçek, M., Işik, Y. (2008). Multi-user detection based on neural network for multi-carrier code division multiple access systems. test, 6(6th International Conference on Electrical Engineering ICEENG 2008), 1-11. doi: 10.21608/iceeng.2008.34205
Necmi Taşpinar; Metin Çiçek; Yalçin Işik. "Multi-user detection based on neural network for multi-carrier code division multiple access systems". test, 6, 6th International Conference on Electrical Engineering ICEENG 2008, 2008, 1-11. doi: 10.21608/iceeng.2008.34205
Taşpinar, N., Çiçek, M., Işik, Y. (2008). 'Multi-user detection based on neural network for multi-carrier code division multiple access systems', test, 6(6th International Conference on Electrical Engineering ICEENG 2008), pp. 1-11. doi: 10.21608/iceeng.2008.34205
Taşpinar, N., Çiçek, M., Işik, Y. Multi-user detection based on neural network for multi-carrier code division multiple access systems. test, 2008; 6(6th International Conference on Electrical Engineering ICEENG 2008): 1-11. doi: 10.21608/iceeng.2008.34205

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, Pages 1-11    PDF (134.28 K)
Document Type: Original Article
DOI: 10.21608/iceeng.2008.34205
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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