Spectrum sensing in cognitive radio sensor networks: towards ultra low overhead, distributed channel findings

Authors:
Fei Hu;Rahul Patibandla;Yang Xiao
Affiliations:
Department of Computer Engineering, Rochester Institute of Technology, Rochester, NY 14623, USA.;Department of Computer Engineering, Rochester Institute of Technology, Rochester, NY 14623, USA.;Department of Computer Science, The University of Alabama, 101 Houser Hall, Box 870290, Tuscaloosa, AL 35487-0290, USA
Venue:
International Journal of Sensor Networks
Year:
2008

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Abstract

Cognitive radios can utilise the idle spectrum holes that arenot occupied by the Primary Users (PUs) (i.e. licensed users) fortemporary wireless communication tasks. A challenging issue is toefficiently reach global/regional views among the Secondary Users(SUs) on channel availability. The SUs need to exchange controlmessages on their spectrum sensing results. A traditional way is tosend out 'raw' channel information from each individual node. Itconsumes much wireless communication bandwidth. This researchproposes a new cognitive radio spectrum sensing scheme based on ourproposed Spatially-Decaying, Time-Incremental (SDTI) updatingalgorithm. Our SDTI algorithm is based on the extension ofGossiping Updates for Efficient Spectrum Sensing (GUESS) schemethat adopts Flajolet-Martin (FM) aggregation to reduce data amount.Our SDTI automatically assigns weights to channel information basedon the distance between a source node and an observing node.Further, distance nodes have less important information to theobserving node.