The 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.
ASJC Scopus subject areas
- Electrical and Electronic Engineering