Title :
Application of compressed sensing in wideband cognitive radios when sparsity is unknown
Author :
Shaban, M. ; Perkins, D. ; Bayoumi, M.
Author_Institution :
Center for Adv. Comput. Studies, Univ. of Louisiana at Lafayette, Lafayette, LA, USA
Abstract :
We present a novel solution for wideband spectrum sensing when the sparsity of the sensed signal or the occupation rate of the frequency band of interest is unknown. Moreover, the proposed method offers the first solution to sense the frequency band of interest when almost fully occupied. Generally, our method employs compressed sensing to acquire the received signal at sub-Nyquist rates. Then, the sum (or the average) of the frequency spectra per each frequency subband is estimated using least squares optimization where the sparsity is assumed as the total number of frequency subbands. Moreover, a detection criterion is formulated. A reduction in the design complexity of the sampling stage as well as the computational complexity of the recovery stage is achieved compared to compressive wideband spectrum sensing methods including the sequential compressed sensing method.
Keywords :
Nyquist criterion; cognitive radio; compressed sensing; computational complexity; frequency estimation; least squares approximations; optimisation; radio spectrum management; signal detection; signal sampling; compressed sensing; computational complexity; design complexity reduction; frequency spectra estimation; frequency subband; least squares optimization; received signal acquire; sampling stage; signal detection criterion; subNyquist rate; unknown sensed signal sparsity; wideband cognitive radio; wideband spectrum sensing; Accuracy; Cognitive radio; Compressed sensing; Frequency estimation; Sensors; Signal to noise ratio; Wideband; Cognitive radio; compressed sensing; sub-Nyquist sampling; unknown sparsity; wideband spectrum sensing;
Conference_Titel :
Wireless and Microwave Technology Conference (WAMICON), 2014 IEEE 15th Annual
Conference_Location :
Tampa, FL
DOI :
10.1109/WAMICON.2014.6857771