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Recently, there has been a surge of interests in paradigms such as device-to-device (D2D) communications and radio frequency energy harvesting (RFEH) to improve the spectrum as well as energy efficiencies of next-generation decentralized cognitive radio networks. However, little attention has been paid to the dual but competing task of subband selection of any desired bandwidth in D2D mode (i.e.,...
Although the research on traffic prediction is an established field, most existing works have been carried out on traditional wired broadband networks and rarely shed light on cellular radio access networks (CRANs). However, with the explosively growing demand for radio access, there is an urgent need to design a traffic-aware energy-efficient network architecture. In order to realize such a design,...
Compressed sensing (CS) is an emerging theory based on the fact that the salient information of a signal can be preserved in a relatively small number of linear projections. Besides its applications in image compression and signal processing in the past few years, compressed sensing has been attracting ever-increasing interests in the areas of wireless communication and sensor networks. According...
Fast Fourier transform (FFT) is widely used in signal processing and communications such as digital filtering, spectral analysis, and multicarrier cognitive radio systems based on OFDM (orthogonal frequency-division multiplexing) and FBMC (filter-bank multi-carriers). There are several methods that have been developed to eliminate or reduce the computation within a DFT if the input points have many...
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