Adaptive linear interference suppression for packet DS‐CDMA

Abstract

AbstractThe performance of adaptive linear interference suppression is studied in the context of packet DS‐CDMA. A multi‐cell system is assumed with stochastic arrivals and departures of asynchronous users, and additive Gaussian noise as the only channel impairment. Interference suppression is achieved with a tapped‐delay line filter, where the filter spans a single symbol interval. Adaptive algorithms considered include the stochastic gradient (LMS), exponentially‐weighted Least Squares (LS), block LS, and a reduced‐rank LS algorithm. The reduced‐rank LS algorithm first projects the received signal onto a signal sub‐space spanned by eigenvectors of the averaged outer product matrix of received vectors. The purpose of the projection is to eliminate low‐level background interference and noise. Both decision‐directed and blind algorithms, which do not require a training sequence, are compared. Computer simulation is used to obtain error rates as a function of traffic load, and algorithm and system parameters (including timing offset). Results indicate that the adaptive algorithms offer a significant increase in capacity (nearly a factor of two at moderate error rates), and are insensitive to variations in received power over the user population.