A SUBSPACE APPROACH TO ADAPTIVE NARROW-BAND INTERFERENCE SUPPRESSION IN DSSS

In this paper we address the problem of suppression of a digital narro w-band interferer in direct-sequence spread spectrum (DSSS) communicat ions, We focus on the adaptive suppression method proposed by Honig, M adhow, and Verdu [1] for wide-band interference, applying it to a narr ow-band interferer, We identify the eigenspaces of the system dynamics to analyze the convergence of the adaptive version of the minimum mea n square error (MMSE) algorithm for this application. Using this subsp ace approach we are able to: 1) significantly decrease convergence tim es via a new constraint on step size in adaptation; 2) introduce a sim ple parameterization of the mean output energy (MOE) and signal-to-int erference ratio (SIR) to compare performance of various receivers; and 3) identify modes of operation where the algorithm will cease to effe ctively cancel interference. We propose a new adaptive receiver that a voids the convergence anomalies identified, while capitalizing on the new step size for faster convergence, Simulation results to support th eoretical results are presented.