Approximations to joint-ML and ML symbol-channel estimators in MUD CDMA

Abstract

In this contribution we conceptually derive two symbol-channel estimators, the joint-ML and the ML, both having exponential complexity. Pragmatically we derive three approximations with polynomial complexity, one to the joint-ML: the pseudo-joint-ML; two to the ML: the naive-ML and the linear-response-ML. We assess the resulting average bit error rates empirically. Performance gains of several dB are observed from using the ML based approximations compared to the joint-ML.