Ant-Colony Based Near-ML Space-Time Multiuser Detection for the STBC Assisted DS-CDMA Uplink

In this contribution, a novel Ant Colony Optimization (ACO) based Space-Time (ST) Multiuser Detection (MUD) algorithm was proposed in order to improve the Bit Error Ratio (BER) versus Signal-to-Noise Ratio (SNR) performance achieved by the Space-Time Block Code (STBC) assisted two transmit antenna aided fully loaded DS-CDMA system directly employing an ACO based MUD algorithm. Our simulation results demonstrate that the proposed ACO based MUD algorithm enables the fully loaded system to approach the single user performance associated with a second-order diversity gain. Furthermore, the complexity of the improved ACO based MUD algorithm is a factor of 10¹⁸ lower than that of the Maximum Likelihood (ML) MUD, when K = 32 users are supported by the STBC Q₂ asssited DS-CDMA systems employing Gold codes having a length of 31 chips.