Signal processing algorithms for adaptive interference suppression

Future wireless communication systems will involve significant adaptive signal processing capabilities to enhance the performance of high-rate transmission through limited bandwidth, dynamic multiple-access channels. Structured interference is a dominant, performance-limiting characteristic of such channels, and this paper provides a brief overview of basic adaptive signal processing algorithms that are useful for combatting this problem. This overview focuses primarily on adaptive linear methods for the suppression of multiple-access interference, although the mitigation of such impairments as dispersion and impulsive noise, and the exploitation of receiver diversity arising either from natural multipath or from the use of multiple antennas, are also discussed briefly. The discussion considers algorithms based on traditional techniques such as recursive-least-squares, as well as those based on more recently developed methods involving subspace tracking.