Conformación ciega de haz mediante regresión con máquinas de vectores soporte

Abstract

Blind beamforming is a common problem in wireless communications, where an array of antennas receives a number of signals from distinct locations at the same frequency and at the same time. In this paper the problem of blind beamforming for multiple constant modulus (CM) signals separation is solved using support vector machine (SVM) techniques. The CM property of the signal is used to formulate a regression problem which can be adapted to the SVM scheme, leading to an iterative reweighted algorithm. Once a signal is recovered, its contribution to the original observations is removed and the iterative procedure can be applied again to extract another CM signal. Simulation results show that this SVM-based algorithm offers better performance than the algebraic constant modulus algorithm (ACMA), mainly when only a small number of snapshots is available.