ACO-Based Multi-User Detection in Cooperative CDMA Networks

In this paper, the cooperative diversity is investigated in the uplink of a Code Division Multiple Access (CDMA) network in which users cooperate by relaying each other’s messages toward the Base Station (BS). It is assumed that the spreading waveforms are not orthogonal and hence, Multiple Access Interference (MAI) exists at the relay nodes as well as the BS. MAI degrades the signal quality at both relays and BS and decreases the cooperative diversity gain. To alleviate this problem, an Ant Colony Optimization (ACO) based Multi-User Detector (MUD) has been proposed to efficiently combine the received signals from the direct and relay paths and sub-optimally extract transmitted bits at the BS. The computational complexity of proposed algorithm is significantly lower than that of the Maximum Likelihood (ML) detector. More explicitly, for a cooperative network supporting 15 users, the computational complexity of the proposed ACO algorithm is a factor of 103 lower than that of the optimum Bayesian detector. Simulation results show that the performance of the proposed ACO-based detector can closely approach the maximum diversity in terms of BER and efficiently cancel the MAI at the BS. Keywords– Cooperative diversity, DS-CDMA systems, multiuser detection, ant colony optimization.