Subband transforms for adaptive, RLS direct sequence spread spectrum receivers

Adaptive Direct Sequence Spread Spectrum (DSSS) receivers have advantages over their fixed matched filter counterparts including interference cancellation capabilities and simplification of PN code acquisition. However, convergence using the LMS algorithm will be very slow in situations with relatively high SNR and/or a large number of users. The use of the RLS algorithm will improve convergence speed but at significantly increased computational cost, especially for long PN codes. Unfortunately, computationally efficient, fast RLS algorithms cannot be used because the filter is updated at the symbol rate rather than at every sample. In this paper, we propose a subband version of the RLS-based receiver that utilizes multiple, shorter length adaptive filters. This approach significantly reduces computation and introduces architectural parallelism into the system implementation. We design an optimal subband transform and provide simulation results demonstrating the improved convergence properties as compared with the fullband system.