Adaptive spreading code optimization in multiantenna multipath fading channels in CDMA

The aim of this paper is to present discrete stochastic approximation algorithms for adaptively optimizing the spreading code of users in a CDMA system. The proposed algorithm can adapt to slowly time varying channel conditions. The most important property of the proposed algorithm is its self-learning capability - it spend most of the computational effort at the global minimizer of the objective function. A tracking analysis of the adaptive algorithms is also presented together with square convergence analysis. Numerical examples illustrate the performance of the algorithms in multipath fading channels.