DocumentCode :
2370373
Title :
Network coding based wideband compressed spectrum sensing
Author :
Dehghan, Hoda ; Lambadaris, Ioannis ; Lung, Chung-Horng
Author_Institution :
Dept. of Syst. & Comput. Eng., Carleton Univ., Ottawa, ON, Canada
fYear :
2012
fDate :
10-15 June 2012
Firstpage :
1405
Lastpage :
1409
Abstract :
One of the fundamental components in cognitive radios (CRs) is spectrum sensing. For sensing the wide range of frequency bands, CRs need high sampling rate analog to digital converters (ADCs) which have to operate at or above the Nyquist rate. The high operating rate constitutes a major implementation challenge. Compressive sensing (CS) is a method that may overcome this problem. Sub-Nyquist rate can be used for CS recovery algorithms such as ℓ1-minimization. While boundary information of all frequency sub-bands is available, a more efficient recovery algorithm based on ℓ2/ℓ1-minimization can be used instead of ℓ1-minimization. In cognitive radio systems, network coding could be used for primary users (PUs) to increase packet transmissions. Furthermore, network coding provides a structure for vacant sub-bands of spectrum and makes the spectrum more predictable. Using this information that network coding provides us, we combine ℓ1-minimization and ℓ2/ℓ1-minimization algorithms with network coding for compressive spectrum sensing. Our methods require reduced signal sampling rate and result in improved false alarm (FA) and missed detection (MD) probabilities for idle band detection.
Keywords :
Nyquist criterion; analogue-digital conversion; cognitive radio; compressed sensing; minimisation; network coding; signal sampling; ℓ2-ℓ1-minimization; ADC; CR; CS recovery algorithms; FA; MD probabilities; PU; cognitive radio systems; false alarm improvement; high sampling rate analog to digital converters; idle band detection; missed detection probabilities; network coding; packet transmissions; primary users; signal sampling rate reduction; sub-Nyquist rate; vacant subbands; wideband compressed spectrum sensing; Cognitive radio; Compressed sensing; Minimization; Network coding; Radiation detectors; Vectors;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Communications (ICC), 2012 IEEE International Conference on
Conference_Location :
Ottawa, ON
ISSN :
1550-3607
Print_ISBN :
978-1-4577-2052-9
Electronic_ISBN :
1550-3607
Type :
conf
DOI :
10.1109/ICC.2012.6364036
Filename :
6364036
Link To Document :
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