@unpublished{elediasc12402,
            year = {2006},
          author = {Claudio Sacchi and Leandro D'Orazio and Massimo Donelli and Francesco G.B. De Natale},
           month = {May},
           title = {A genetic algorithm-assisted semi-adaptive MMSE multi-user detection for MC-CDMA mobile communication systems},
             url = {http://www.eledia.org/students-reports/402/},
        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.}
}