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Lookup NU author(s): Emeritus Professor Rolando Carrasco
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Linear and nonlinear adaptive algorithms are investigated for Space Division Multiple Access (SDMA). SDMA is one of the emerging techniques for multiple access of users in mobile radio, which used spatial distribution of users for their differentiation. The performance of the linear Square Root Kalman (SRK) algorithm for SDMA is compared to that of the nonlinear recurrent neural network (RNN) techniques. The proposed SDMA-RNN technique is evaluated over Rician fading channels, and it shows improved bit error rate (BET) performance in comparison with the linear SRK-based technique. The performance of SDMA-RNN is also compared with that of Code Division Multiple Access (CDMA) systems, showing that it could be used as a viable alternative scheme for multiple access of users. Finally, a hybrid CDMA-SDMA system is proposed combining CDMA and SDMA-RNN systems. Hybrid CDMA-SDMA exhibits a very good potential for increase in the capacity and the performance of mobile communications systems. (19 References).
Author(s): Carrasco RA; Benson M
Publication type: Article
Publication status: Published
Journal: Neural Computing & Applications
Year: 2001
Volume: 10
Issue: 2
Pages: 136-147
ISSN (print): 0941-0643
ISSN (electronic): 1433-3058
Publisher: Springer
URL: http://dx.doi.org/10.1007/s005210170005
DOI: 10.1007/s005210170005
Notes: Publisher: Springer-Verlag, UK.
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