Title :
Genetically modified multiuser detection for code division multiple access systems
Author :
Abedi, Saied ; Tafazolli, Rahim
Author_Institution :
Fujitsu Labs. of Eur. Ltd., Hayes, UK
fDate :
2/1/2002 12:00:00 AM
Abstract :
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 the detection of CDMA signals in the presence of MAI and ISI. The proposed hybrid detector structure can be extended to most multiuser detectors and used as the base detector within the structure. Using random selection, mutation and crossover operators and a 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 a conventional single user detector as the base detector, is proposed for asynchronous CDMA (ACDMA) with negligible ISI. 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 nearly to 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 in a group of more efficient and adaptive detectors
Keywords :
adaptive signal detection; code division multiple access; error statistics; genetic algorithms; interference suppression; intersymbol interference; least mean squares methods; multiuser channels; BER performance; ISI; MAI; MMSE; adaptive detectors; asynchronous CDMA; bit-error rate performance; chromosome structure; code division multiple access; crossover operators; evolutionary computation; genetically modified multiuser detection; hybrid detector structure; hybrid genetic engine; interference suppression; intersymbol interference; minimum mean square error detector; multiple access interference; mutation; random selection; Biological cells; Detectors; Engines; Evolutionary computation; Genetic mutations; Intersymbol interference; Multiaccess communication; Multiple access interference; Multiuser detection; Signal detection;
Journal_Title :
Selected Areas in Communications, IEEE Journal on