Abstract:In the late years, MIMO MC-CDMA approach has been proposed in order to expand framework capacity over frequency-selective wireless channels. The key component of MIMO MC-CDMA is the capacity of abusing diversity jointly in time, frequency and in the space domain. In this work, we implement an efficient multi-user STBC MC-CDMA transmission System Based on Minimum Conditional BER Criterion and Oppositional krill herd algorithm (OKHA) assisted channel estimation. The multiuser MC-CDMA system using Alamouti's Space-Time Block coding for encoding the transmitting sequence. The estimation of Channel State Information (CSI) is optimally selected using OKHA. Normally, KHA is a natural-inspired metaheuristic algorithm which mimics the herding behavior of ocean krill individual. To improve the convergence speed and accuracy of the basic KHA algorithm, in this proposed work we combine KHA with oppositional based learning (OBL). The experimental results are conducted for the different algorithm based on BER, SER, and spectral efficiency. The simulation results show that the proposed algorithm is properly reducing the BER, SER and properly increase the spectral efficiency value compare to other techniques.