Paper Info
Title
Efficient compressive spectrum sensing algorithm for M2M devices
Abstract
Spectrum used for Machine-to-Machine (M2M) communications should be as cheap as possible or even free in order to connect billions of devices. Recently, both UK and US regulators have conducted trails and pilots to release the UHF TV spectrum for secondary licence-exempt applications. However, it is a very challenging task to implement wideband spectrum sensing in compact and low power M2M devices as high sampling rates are very expensive and difficult to achieve. In recent years, compressive sensing (CS) technique makes fast wideband spectrum sensing possible by taking samples at sub-Nyquist sampling rates. In this paper, we propose a two-step CS based spectrum sensing algorithm. In the first step, the CS is implemented in an SU and only part of the spectrum of interest is supposed to be sensed by an SU in each sensing period to reduce the complexity in the signal recovery process. In the second step, a denoising algorithm is proposed to improve the detection performance of spectrum sensing. The proposed two-step CS based spectrum sensing is compared with the traditional scheme and the theoretical curves.
Year
DOI
Venue
2014
10.1109/GlobalSIP.2014.7032306
GlobalSIP
Keywords
Field
DocType
signal denoising,machine-to-machine communications,compressive spectrum sensing algorithm,wideband spectrum sensing,radio spectrum management,compressed sensing,denoising algorithm,uk regulators,uhf tv spectrum,us regulators,m2m devices,noise reduction,cognitive radio,signal to noise ratio,sensors
Noise reduction,Wideband,Computer science,Signal-to-noise ratio,Algorithm,Sampling (statistics),Direct-sequence spread spectrum,Ultra high frequency,Compressed sensing,Cognitive radio
Conference
Citations 
PageRank 
References 
5
0.58
7
Authors
5
Name
Order
Citations
PageRank
Zhijin Qin162334.85
Yue Gao255852.83
M. D. Plumbley31915202.38
Clive G. Parini480.96
Laurie G. Cuthbert521329.30