Spectrum Sensing Over Multipath Fading Channels through Ofdm Signals for Cognitive Radios

Abstract

This paper focuses on the matter of distributed composite hypothesis testing in a network of sparsely interconnected agents, during which only a little section of the field modeling parametric alternatives is noticeable at every agent. A recursive generalized likelihood ratio test (GLRT) type algorithm in a very distributed setup of the consensus-plus-innovations form is proposed, during which the agents update their parameter estimates and decision statistics by at the same time processing the newest sensed information (innovations) and information obtained from neighboring agents (consensus). This paper characterizes the conditions and also the testing algorithm design parameters that make sure that the chances of decision errors decay to zero asymptotically within the giant sample limit. Finally, simulations studies are presented that illustrate the findings.