Bayesian compressive sensing framework for spectrum reconstruction in Rayleigh fading channels

Iqbak, N., Mahmood, A., Hussain, S. and Ghafoor, A. (2016) Bayesian compressive sensing framework for spectrum reconstruction in Rayleigh fading channels. Turkish Journal of Electrical Engineering and Computer Sciences, 24(5), pp. 3240-3252. (doi: 10.3906/elk-1405-198)

Abstract

Compressive sensing (CS) is a novel digital signal processing technique that has found great interest in many applications including communication theory and wireless communications. In wireless communications, CS is particularly suitable for its application in the area of spectrum sensing for cognitive radios, where the complete spectrum under observation, with many spectral holes, can be modeled as a sparse wide-band signal in the frequency domain. Considering the initial works performed to exploit the benefits of Bayesian CS in spectrum sensing, the fading characteristic of wireless communications has not been considered yet to a great extent, although it is an inherent feature for all sorts of wireless communications and it must be considered for the design of any practically viable wireless system. In this paper, we extend the Bayesian CS framework for the recovery of a sparse signal, whose nonzero coefficients follow a Rayleigh distribution. It is then demonstrated via simulations that mean square error significantly improves when appropriate prior distribution is used for the faded signal coefficients and thus, in turns, the spectrum reconstruction improves. Different parameters of the system model, e.g., sparsity level and number of measurements, are then varied to show the consistency of the results for different cases.

• Item Type: Articles
• Status: Published
• Refereed: Yes
• Glasgow Author(s) Enlighten ID: Hussain, Dr Sajjad
• Authors: Iqbak, N., Mahmood, A., Hussain, S., and Ghafoor, A.
• College/School: College of Science and Engineering > School of Engineering > Electronics and Nanoscale Engineering
• Journal Name: Turkish Journal of Electrical Engineering and Computer Sciences
• Publisher: Scientific and Technical Research Council of Turkey
• ISSN: 1300-0632
• ISSN (Online): 1303-6203
• Published Online: 01 April 2015
• Copyright Holders: Copyright © 2016 TUBITAK
• First Published: First published in Turkish Journal of Electrical Engineering and Computer Sciences 24(5):3371-3387
• Publisher Policy: Reproduced in accordance with the copyright policy of the publisher