Adaptive least mean square CDMA detection with Gram-Schmidt pre-processing

The Gram-Schmidt (GS) orthogonalisation procedure has been used to improve the convergence speed of least mean square (LMS) adaptive code-division mul tiple-access (CDMA) detectors. However, this algorithm updates two sets of parameters, namely the GS transform coefficients and the tap weights, simul taneously. Because of the additional adaptation noise introduced by the for mer, it is impossible to achieve the same performance as the ideal orthogon alised LMS filter, unlike the result implied in an earlier paper. The autho rs provide a lower bound on the minimum achievable mean squared error (MSE) as a function of the forgetting factor lambda used in finding the GS trans form coefficients, and propose a variable-lambda algorithm to balance the c onflicting requirements of good tracking and low misadjustment.