relation: http://www.eledia.org/students-reports/402/
title: A genetic algorithm-assisted semi-adaptive MMSE multi-user detection for MC-CDMA mobile communication systems
creator: Sacchi, Claudio
creator: D'Orazio, Leandro
creator: Donelli, Massimo
creator: De Natale, Francesco G.B.
subject: TU Technical Reports and Publications
description: In this work, a novel Minimum-Mean Squared-Error (MMSE) multi-user detector is proposed for MC-CDMA transmission systems working over mobile radio channels characterized by time-varying multipath fading. The proposed MUD algorithm is based on a Genetic Algorithm (GA)-assisted per-carrier MMSE criterion. The GA block works in two successive steps: a training-aided step aimed at computing the optimal receiver weights using a very short training sequence, and a decision-directed step aimed at dynamically updating the weights vector during a channel coherence period. Numerical results evidenced BER performances almost coincident with ones yielded by ideal MMSE-MUD based on the perfect knowledge of channel impulse response. The proposed GA-assisted MMSE-MUD clearly outperforms state-of-the-art adaptive MMSE receivers based on deterministic gradient algorithms, especially for high number of transmitting users.
date: 2006-05
type: Technical Report
type: NonPeerReviewed
format: text
language: en
identifier: http://www.eledia.org/students-reports/402/1/DIT-06-024.pdf
identifier:   Sacchi, Claudio and D'Orazio, Leandro and Donelli, Massimo and De Natale, Francesco G.B.  (2006) A genetic algorithm-assisted semi-adaptive MMSE multi-user detection for MC-CDMA mobile communication systems.  [Technical Report]    (Unpublished)