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 resi stant receiver for direct-sequence (DS) code-division multiple-access (CDMA) known as the minimum mean-squared error (MMSE) receiver. This r eceiver structure is known to be near-far resistant and yet does not r equire the large amounts of side information that are typically requir ed for other near-far resistant receivers, In fact, this receiver only requires code timing on the one desired signal, The MMSE receiver use s an adaptive filter which is operated in a manner similar to adaptive equalizers, Initially there is a training period where the filter loc ks onto the signal that is sending a known training sequence, After tr aining, the system can then switch to a decision-directed mode and sen d actual data, This work examines the length of the training period ne eded 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 a ll 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 probl em without excessively long convergence time.