Techniques and adaptation algorithms for direct-sequence spread-spectrum CDMA single-user detection

Abstract

The capacity of a direct-sequence spread-spectrum code division multiple access (DSSS-CDMA) system is limited by multiple access interference (MAJ) and the near-far problem. There are two approaches to mitigating these problems: multiuser detection and single-user detection techniques. Multiuser detection techniques cancel the interference and enhance system capacity, but have large computational requirements and require the knowledge of MAI parameters. Single-user detection techniques require only the knowledge of the desired user’s spreading code and timing, and have a complexity comparable to the conventional receiver.

This thesis reviews a wide range of DSSS-CDMaA single-user detectors found in the literature. The receivers are explained with a common approach using an adaptive antenna array perspective and noting that single-user detectors exploit spectral redundancy, while adaptive arrays exploit spatial redundancy. Commonly used trained adaptation algorithms for single-user detection are first presented, and are followed by newly proposed blind adaptation algorithms. These new blind algorithms are Griffiths’ algorithm, and the linearly constrained constant modulus algorithm (LCCMA ). Through simulation, a blindly-adapted single-user detector is shown to greatly outperform the conventional receiver in terms of bit-error-rate (BER) performance, and to perform almost as well as in the case of trained adaptation. The receivers are shown to be near-far resistant, and are computationally attractive for a mobile receiver. Both receivers have good convergence properties and don’t suffer from catastrophic failure.