Performance study of DD ML phase estimators for DS-CDMA communications systems

In the case of Data-Aided (DA) Maximum-Likelihood (ML) phase estimators operating in Direct Sequence-Code Division Multiple Access (DS-CDMA) communication systems, it has been shown [1, 2] that a multiuser (MU) design of the estimator helped to define parameter estimators exhibiting a lower variance than those designed in the conventional, single-user (SU) way. The present paper applies the same MU design strategy in the more realistic case of Decision-Directed (DD) estimators. The performance of these DD structures are derived from the DA variance expressions, assuming decisions to be correct and limiting the mitigation of the Multiple Access Interference (MAI) to its causal contribution.