Genetically modified multiuser detection for code division multiple access systems

The problem of multiple access interference (MAI) and intersymbol interference (ISI) suppression in code division multiple access (CDMA) systems is considered. By combining the theory of multiuser detection (MUD) and evolutionary computation, a hybrid genetic engine is proposed, suitable for detection of CDMA signals in presence of MAI and ISI. The proposed hybrid detector structure can be extended to most of multiuser detectors, used as the base detector within the structure. Using random selection, mutation, and crossover operators and unique chromosome structure, the genetic algorithm evolves the base detector to a group of more efficient detectors in terms of bit-error rate performance. First a new packet-level genetic MUD technique, using conventional single user detector as the base detector, for asynchronous COMA (ACDMA) with negligible ISI is proposed. Then the signal-subspace-based minimum mean square error detector is chosen as a base detector and wrapped inside the hybrid genetic engine to evolve to a better structure to nearly eliminate both ISI and MAI. The novelty of the proposed structure is the way the deterministic closed-form solution of the base detector is mapped to a genetic engine resulting to a group of more efficient and adaptive detectors.