A genetic algorithm-assisted semi-adaptive MMSE multi-user detection for MC-CDMA mobile communication systems

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. UNSPECIFIED. (Unpublished)

[img]
Preview
PDF
Download (188Kb) | Preview

    Abstract

    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.

    Item Type: Departmental Technical Report
    Department or Research center: Information Engineering and Computer Science
    Subjects: T Technology > TK Electrical engineering. Electronics Nuclear engineering > TK7885 Computer Engineering
    T Technology > TK Electrical engineering. Electronics Nuclear engineering > TK5105.5 Computer Networks
    Q Science > QA Mathematics > QA276 Mathematical Statistics
    Q Science > QA Mathematics > QA273 Probabilities
    Report Number: DIT-06-024
    Repository staff approval on: 09 May 2006

    Actions (login required)

    View Item