Cognitive radio (CR) has emerged as one of the most promising candidate solutions to improve spectrum utilization for future wireless networks. A crucial requirement for future CR networks is the ability to sense wideband spectrum. Recently, compressive sensing (CS) has been proposed as a solution to replace high speed analog-to-digital converters. CS enables sub-Nyquist sampling for wideband spectrum sensing by exploiting the sparse nature of spectrum occupancy. In this paper, the CS based spectrum sensing model is firstly summarized. The measurement matrix designs and the hardware implementations of CS based wideband spectrum sensing algorithms are then explored. The implementations of CS with real-time signals over TV white space spectrum in CR is further established. This paper is concluded by providing outlooks and open research challenges on the practical implementation of CS in wideband spectrum sensing in cognitive radio.


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    Title :

    Implementation of Compressive Sensing with Real-Time Signals over TV White Space Spectrum in Cognitive Radio


    Contributors:
    Gao, Yue (author) / Qin, Zhijin (author)


    Publication date :

    2016-09-01


    Size :

    320207 byte




    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English



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