Training analysis of adaptive interference suppression for direct-sequence code-division multiple-access systems

This paper studies the transient behavior of an adaptive near-far resistant receiver for direct-sequence (DS) code-division multiple-access (CDMA) known as the minimum mean-squared error (MMSE) receiver. This receiver structure is known to be near-far resistant and yet does not require the large amounts of side information that are typically required for other near-far resistant receivers. In fact, this receiver only requires code timing on the one desired signal. The MMSE receiver uses an adaptive filter which is operated in a manner similar to adaptive equalizers. Initially there is a training period where the filter locks onto the signal that is sending a known training sequence. After training, the system can then switch to a decision-directed mode and send actual data. This work examines the length of the training period needed as a function of the number of interfering users and the severity of the near-far problem. A standard least mean-square (LMS) algorithm is used to adapt the filter and so the trade-off between convergence and excess mean-squared error is studied. It is found that in almost all cases a step size near 1.0/(total input power) gives the best speed of convergence with a reasonable excess mean-squared error. Also, it is shown that the MMSE receiver can tolerate a 30-40 dB near-far problem without excessively long convergence time.