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Joint Energy-Efficient Cooperative Spectrum Sensing and Power Allocation in Cognitive Machine-to-Machine Communications

Pham, Hai Ngoc; Zhang, Yan; Skeie, Tor; Engelstad, Paal E.; Eliassen, Frank
Peer reviewed, Chapter
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URI
https://hdl.handle.net/10642/3717
Date
2016
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Original version
Pham Hai Ngoc, Zhang Y, Skeie T, Engelstad P.E., Eliassen F: Joint Energy-Efficient Cooperative Spectrum Sensing and Power Allocation in Cognitive Machine-to-Machine Communications. In: NN N. Proceedings of the 2016 International Wireless Communications and Mobile Computing Conference (IWCMC 2016), 2016. IEEE   http://dx.doi.org/10.1109/IWCMC.2016.7577208
Abstract
In battery-powered Cognitive Machine-to-Machine

Communications (CM2M), the energy consumption, opportunis-

tic data access capacity and interference to the licensed system

need to be optimized simultaneously. We consider this as joint

cooperative spectrum sensing and power allocation, and model

this as a constraint multiobjective optimization problem of three

objectives. Our model helps to find a Pareto optimal variable

set of sensing duration, detection threshold and transmission

power for each individual sensor in cooperative spectrum sensing.

The evaluation of our model shows that energy consumption,

opportunistic data capacity and interference are optimized

simultaneously while keeping the total cooperative spectrum

sensing error lower than a predefined threshold. Pareto optimal

results show that better energy efficiency [bits/joule] makes lower

harmful interference to the primary system.
Publisher
IEEE

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