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Neural Computing and Applications

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26.06.2017 | Original Article

Design of MC-CDMA receiver using radial basis function network to mitigate multiple access interference and nonlinear distortion

verfasst von: Ravi Kumar C.V., Kala Praveen Bagadi

Erschienen in: Neural Computing and Applications | Sonderheft 2/2019

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Abstract

Multicarrier code division multiple access (MC-CDMA) is a novel wireless communication technology with high spectral efficiency and system performance. However, all multiple access techniques including MC-CDMA were most likely to have multiple access interference (MAI). So, this paper mainly aims at designing a suitable receiver for MC-CDMA system to mitigate such MAI. The classical receivers like maximal-ratio combining and minimum mean square error fail to cancel MAI when the MC-CDMA is subjected to nonlinear distortions, which may occur due to saturated power amplifiers or arbitrary channel conditions. Being highly nonlinear structures, the neural network (NN) receivers such as multilayer perceptron and radial basis function networks could be better alternative for such a case. The possibility NN receiver for a MC-CDMA system under different nonlinear conditions has been studied with respect to both performance and complexity analysis.

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Titel: Design of MC-CDMA receiver using radial basis function network to mitigate multiple access interference and nonlinear distortion
verfasst von: Ravi Kumar C.V.
Kala Praveen Bagadi
Publikationsdatum: 26.06.2017
Verlag: Springer London
Erschienen in: Neural Computing and Applications / Ausgabe Sonderheft 2/2019
Print ISSN: 0941-0643
Elektronische ISSN: 1433-3058
DOI: https://doi.org/10.1007/s00521-017-3127-0

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