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Conventional compressive sensing-based data gathering (CS-DG) algorithms require a large number of sensors for each compressive sensing measurement, thereby resulting in high energy consumption in clustered wireless sensor networks (WSNs). To solve this problem, we propose a novel energy-efficient CS-DG algorithm, which exploits the better reconstruction accuracy of the adjacency matrix of an unbalanced...
The recently emerged compressive sensing (CS) theory provides a whole new avenue for data gathering (DG) in wireless sensor networks (WSNs) with the benefits of energy efficient. The exiting CS based DG approaches design the routing processes based on the assumption that there is a transform that can sparsely represent the sensor readings. However, most of the real sensor readings are well approximated...
In cognitive radio (CR) networks, two main challenges faced by cooperative spectrum sensing are low detection performance and long detection time in low SNR scenario. To the best of our knowledge, little study analyzes these two problems simultaneously and thoroughly. Therefore, this paper proposes a novel spectrum sensing scheme, termed multistep detection (MD) scheme, which aims to resolve the above...
This paper proposes a novel wideband spectrum sensing (WSS) scheme, termed multi-antenna compressed wideband spectrum sensing (MCWSS) scheme, which utilizes compressed sensing (CS) to reduce the extremely high sampling rate of wideband signal. Although there are studies on compressed wideband spectrum sensing, they only focus on single antenna signal. Since multi-antenna technology can enhance the...
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