Adaptive filter theory
Self-organizing maps
Equalization of satellite UMTS channels using neural network devices
ICASSP '99 Proceedings of the Acoustics, Speech, and Signal Processing, 1999. on 1999 IEEE International Conference - Volume 05
Conditional distribution learning with neural networks and itsapplication to channel equalization
IEEE Transactions on Signal Processing
IEEE Journal on Selected Areas in Communications
Channel equalization using adaptive complex radial basis function networks
IEEE Journal on Selected Areas in Communications
Performance Comparison of Several Non-Linear Equalizers in the Context of Mobile Telecommunications
Information Systems Frontiers
EURASIP Journal on Applied Signal Processing
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The use of non-linear amplifiers near saturation in satellite channels causes severe distortion of the transmitted signal. These distortions make the matter of power efficiency prevail over spectral efficiency in satellite communication systems. Nowadays, the use of satellite segments for applications requiring ever increasing data rates puts this principle in question. The present article proposes to fight non-linear distortion caused by satellite amplifiers by resorting to simple neural network equalisation devices in the receiving earth terminals. Several neural network equalisers are introduced, and applied to a satellite Universal Mobile Telecommunication System (S-UMTS) channel model. They are shown not only to outperform conventional equalisation techniques like the linear transversal equaliser, but also to have better performance than the non-linear Volterra equaliser. The performance improvement is all the more sensitive as the modulation scheme used is severely distorted. The case of 16-QAM transmission over a mobile satellite link is studied in details.