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The existing works on analyzing/utilizing spectrum whitespace in Cognitive Radio Networks (CRNs) are either empirical studies lacking of theoretical guarantee, or local primary network information based inducing inaccurate analysis and estimation, or overlooking the spectrum whitespace details. Therefore, we propose to systematically analyze the spectrum whitespace in CRNs from a social network perspective...
Complicated collisions and spectrum uncertainty constrain the usage of Cognitive Radio Networks (CRNs) on heavy transmission and time sensitive applications. On the other hand, data aggregation has been considered as an essential operation in wireless networks. A large amount of effort has been dedicated to the investigation of CRNs and data aggregation in wireless networks. However, the existing...
This paper introduces a method based on compressive sensing to acquire voice signals from distributed wireless sensors. The method uses compressive sensing technology to sample, transmit and recover data to reduce the sampling rate and further compress the data. As the voice signals in the discrete cosine transform domains are approximately sparse, this paper builds a JSM-1 based model and uses the...
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