Robust Adaptive Spread-Spectrum Receiver With Neural-Net Preprocessing in Non-Gaussian Noise  

Oleh:

Teong, Chee Chuah ; Sharif, B. S. ; Hinton, O. R.

Jenis: Article from Journal - ilmiah internasional
Dalam koleksi: IEEE Transactions on Neural Networks vol. 12 no. 3 (2001), page 546-558.
Topik: gaussian; robust; adaptive; spread - spectrum receiver; neural - net; non - gaussian noise

Ketersediaan

Perpustakaan Pusat (Semanggi) Nomor Panggil: II36.5 Non-tandon: 1 (dapat dipinjam: 0) Tandon: tidak ada

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Isi artikel

Multiuser communications channels based on code division multiple access (CDMA) technique exhibit non -G aussian statistics due to the presence of highly structured multiple access interference (MAI) and impulsive ambient noise. Linear adaptive interference suppression techniques are attractive for mitigating MAI under Gaussian noise. However, the Gaussian noise hypothesis has been found inadequate in many wireless channels characterized by impulsive disturbance. Linear finite impulse response (FIR) filters adapted with linear algorithms are limited by their structural formulation as a simple linear combiner with a hyperplanar decision boundary, which are extremely vulnerable to impulsive interference. This raises the issues of devising robust reception algorithms accounting at the design stage the non - Gaussian behaviour of the interference. We propose a multiuser receiver that involves an adaptive nonlinear preprocessing front - end based on a multilayer perceptron neural network, which acts as a mechanism to reduce the influence of impulsive noise followed by a postprocessing stage using linear adaptive filters for MAI suppression. Theoretical arguments supported by promising simulation results suggest that the proposed receiver, which combines the relative merits of both non linear and linear signal processing, presents an effective approach for joint suppression of MAI and non - Gaussian ambient noise.

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