Blind source separation algorithms for mitigating co-channel interference and noise in wireless communication systems

Abstract

Blind Source Separation (BSS) algorithms have been applied with considerable success in a variety of fields. In case of communication signals, these BSS algorithms can be applied for blind beamforming and channel estimation. In this thesis, these BSS algorithms are employed to solve the co-channel interference problem in wireless communication systems. Algorithms such as Joint Approximate Diagonalization of Eigen-matrices (JADE) and Analytical Constant Modulus Algorithm (ACMA) can handle source separation in the complex domain. We propose a modified version of the JADE source separation algorithm based on the alternating row updating of the un-mixing matrix. This proposed algorithm is called the Alternating Row Diagonalization Joint Approximate Diagonalization of Eigen-matrices (ARD-JADE). Simulation results show improvement in the Bit Error Rate (BER) and the output Signal to Interference plus Noise ratio (SINR) by application of these source separation algorithms for various SNR levels. Algorithms developed for application in communication systems must not only have the capability of working in the complex domain, but also have relatively low computational complexity. We propose a Fast Fourier Transform (FFT) based algorithm called Feedback Independent Component Analysis (FEBICA) that is able to blindly separate complex modulated digital signals. By applying this algorithm to communication signals, ii ATTENTION: The Singapore Copyright Act applies to the use of this document. Nanyang Technological University Library