Programmable canonical correlation analysis: a flexible framework for blind adaptive spatial filtering

Abstract

In wireless communications, including cellular communication systems, spread spectrum overlay systems, and signals intelligence applications, the degradation caused by rapidly time-varying multipath and unknown co-channel interference can be reduced by adaptive spatial filtering using adaptive antenna arrays. The authors propose a flexible framework for adapting a spatial filter without using a training signal, array calibration data, or knowledge of spatial characteristics of the desired or interfering signals. The framework exploits one or more user-selected statistical properties to adapt the array. Simulation results illustrate the performance of algorithms developed within the new framework.<>