The computation involved in multiuser detection (MUD) for multicarrier CDMA (MC-CDMA) based on maximum likelihood (ML) principle grows exponentially with the number of users. Particle swarm optimization (PSO) with soft decisions has been proposed to mitigate this problem. The computational complexity of PSO, is comparable with genetic algorithm (GA), but is much less than the optimal ML detector and yet its performance is much better than GA.

The computational complexity of the optimum maximum likelihood detector (OMLD) does not allow its utility for multi-user detection (MUD) in code division multiple access (CDMA) systems. As proposed in this letter, particle swarm optimization (PSO) with soft decision offers a much more efficient option with few parameters to be adjusted, flexibility to implement, that gives a much faster convergence compared to OMLD. It outperforms the conventional detector, the genetic algorithm approach and the standard suboptimal detectors considered in the literature.