Distributed Sensing of a Slowly Time-Varying Sparse Spectrum Using Matrix Completion


S. Corroy, A. Bollig, R. Mathar,


        In this paper, we consider the problem of sensing a frequency spectrum in a distributed manner using as few measurements as possible while still guaranteeing a low detection error. To achieve this goal we use the newly developed technique of matrix completion which enables to recover a low rank matrix from a small subset of its entries. We model the sensed bandwidth at different cognitive radios as a spectrum matrix. It has been shown that in many cases the spectrum used by a primary user is underutilized. Therefore the spectrum matrix often has a low rank structure. By taking few measurements at several cognitive radios and reconstructing the matrix at a fusion center, we can dramatically reduce the required number of samples to reconstruct the utilization of the bandwidth. This is a key enabler for efficient and reliable spectrum reuse.

BibTEX Reference Entry 

	author = {Steven Corroy and Andreas Bollig and Rudolf Mathar},
	title = "Distributed Sensing of a Slowly Time-Varying Sparse Spectrum Using Matrix Completion",
	pages = "296-300",
	booktitle = "International Symposium on Wireless Communication  2011",
	address = {Aachen, Deutschland},
	month = Nov,
	year = 2011,
	hsb = hsb999910117232,


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