A Bayesian approach to spectrum sensing, denoising and anomaly detection

Authors:
Erik Axell;Erik G. Larsson
Affiliations:
Department of Electrical Engineering (ISY), Linköping University, 581 83, Sweden;Department of Electrical Engineering (ISY), Linköping University, 581 83, Sweden
Venue:
ICASSP '09 Proceedings of the 2009 IEEE International Conference on Acoustics, Speech and Signal Processing
Year:
2009

Citing 0
Cited 1

Review: A Bayesian approach for adaptive multiantenna sensing in cognitive radio networks

Signal Processing

Quantified Score

Hi-index	0.00

Visualization

Abstract

This paper deals with the problem of discriminating samples that contain only noise from samples that contain a signal embedded in noise. The focus is on the case when the variance of the noise is unknown. We derive the optimal soft decision detector using a Bayesian approach. The complexity of this optimal detector grows exponentially with the number of observations and as a remedy, we propose a number of approximations to it. The problem under study is a fundamental one and it has applications in signal denoising, anomaly detection, and spectrum sensing for cognitive radio. We illustrate the results in the context of the latter.