Compressed Wideband Sensing in Cooperative Cognitive Radio Networks
- 1 January 2008
- conference paper
- conference paper
- Published by Institute of Electrical and Electronics Engineers (IEEE)
Abstract
In emerging cognitive radio (CR) networks with spectrum sharing, the first cognitive task preceding any dynamic spectrum access is the sensing and identification of spectral holes in wireless environments. This paper develops a distributed compressed spectrum sensing approach for (ultra-)wideband CR networks. Compressed sensing is performed at local CRs to scan the very wide spectrum at practical signal-acquisition complexity. Meanwhile, spectral estimates from multiple local CR detectors are fused to collect spatial diversity gain, which improves the sensing quality especially under fading channels. New distributed consensus algorithms are developed for collaborative sensing and fusion. Using only one-hop local communications, these distributed algorithms converge fast to the globally optimal solutions even for multi-hop CR networks, at low communication and computation load scalable to the network size.Keywords
This publication has 8 references indexed in Scilit:
- Consensus in Ad Hoc WSNs With Noisy Links—Part I: Distributed Estimation of Deterministic SignalsIEEE Transactions on Signal Processing, 2007
- Distributed average consensus with least-mean-square deviationJournal of Parallel and Distributed Computing, 2007
- A Wavelet Approach to Wideband Spectrum Sensing for Cognitive RadiosPublished by Institute of Electrical and Electronics Engineers (IEEE) ,2006
- Compressed sensingIEEE Transactions on Information Theory, 2006
- Robust uncertainty principles: exact signal reconstruction from highly incomplete frequency informationIEEE Transactions on Information Theory, 2006
- Collaborative spectrum sensing for opportunistic access in fading environmentsPublished by Institute of Electrical and Electronics Engineers (IEEE) ,2005
- Atomic Decomposition by Basis PursuitSIAM Journal on Scientific Computing, 1998
- Energy detection of unknown deterministic signalsProceedings of the IEEE, 1967