Energy — Efficiency techniques in cooperative spectrum sensing: A survey

Author(s):  
Meenakshi Awasthi ◽  
Vijay Kumar ◽  
M. J. Nigam
IEEE Access ◽  
2020 ◽  
Vol 8 ◽  
pp. 41298-41308 ◽  
Author(s):  
Seleman Daudi Arthur Nkalango ◽  
Hui Zhao ◽  
Yuxin Song ◽  
Tianqi Zhang

Author(s):  
Yi Li ◽  
◽  
Jun Peng ◽  
Fu Jiang ◽  
Kaiyang Liu ◽  
...  

To address the inherent energy constraint in cognitive radio sensor networks, a novel joint optimization method of spectrum sensing and data transmission for energy efficiency is investigated in this paper. To begin with, a cooperative spectrum sensing scheme based on dynamic censoring is employed to shorten sensing time and save unnecessary spectrum sensing energy. Then to jointly optimize the energy efficiency, the distortion constrained probabilistic transmission scheme is utilized. Afterwards the sensing threshold solving issue can be formulated as a nonlinear minmax optimization problem with the detection probability and false alarm probability constraints. Solving by the Matlab software with the free OPTI toolbox, simulation results demonstrate that significant energy can be saved via the the proposed joint optimization method in various mobile cloud scenarios.


2013 ◽  
Vol 17 (8) ◽  
pp. 1564-1567 ◽  
Author(s):  
S. Althunibat ◽  
V. Sucasas ◽  
H. Marques ◽  
J. Rodriguez ◽  
R. Tafazolli ◽  
...  

2015 ◽  
Vol 7 (3) ◽  
pp. 140 ◽  
Author(s):  
Shaoyang Men ◽  
Pascal Chargé ◽  
Sébastien Pillement

Cooperative spectrum sensing (CSS) is able to effectively solve the hidden terminal, depth attenuation, multipath shadows and other issues which are not addressed by the single-user sensing. Therefore, it has attracted a large amount of interest and several CSS algorithms have been proposed. However, they are not specifically tailored for cognitive wireless sensor networks (CWSNs) where transmission reliability, power management and interference avoidance are critical issues. In this paper, we propose a robust and energy efficient CSS scheme in CWSNs. Firstly, taking into account the limited energy of sensor node, especially the mobile node, we introduce the nodes of the network into multiple clusters for the CSS in order to save energy consumed in reporting results and exchanging information and extend the lifetime of the network. Secondly, we consider that some cognitive nodes may not work as expected. Hence, facing the problem of faulty nodes in clusters, we propose an evaluation method which considers simultaneously the node reliability and the mutually supportive degree among different nodes to support adapted decisions. Finally, after removing the node of low credibility, the energy efficiency and reliability of each cluster are improved significantly. Simulation results allow to validate that the proposed method outperforms the state of the art in energy efficiency and detection reliability, even in presence of faulty nodes.


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