Low-complexity pilot-aided data detection in MC-CDMA systems

In this paper, the performance of a MultiUserDetection (MUD) receiver is investigated for a multi-carrier-Code Division Multiple Access (MC-CDMA) system in an Indoor environment. Furthermore, low complexity pilot-aided methods are introduced for estimating channel parameters in an effort to study the resistance of the proposed solution to imperfect channel estimates. Simulation results show that benefits of MC-CDMA schemes, in terms of capacity and probability of error (Pe), are enhanced by means of a Selective Parallel Interference Cancellation (S-PIC) receiver (at the expense of moderate increases in overall system complexity). The proposed channel estimation methods, based on a classical mean and a newly Adaptive Mean Square Error (AMSE) algorithm, introduce low performance loss, in terms of Pe and throughput, with respect to the ideal channel estimate situation. Moreover, the AMSE shows better accuracy and faster convergence than the mean algorithm.