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Sensors 2017, 17(9), 2025; https://doi.org/10.3390/s17092025

Energy-Efficient Optimal Power Allocation in Integrated Wireless Sensor and Cognitive Satellite Terrestrial Networks

1,†
,
1,†,* , 1,†
,
1,†
and
2,†
1
College of Communications Engineering, PLA University of Science and Technology, No. 2 Biaoying, Qinhuai District, Nanjing 210007, China
2
Wolfson School of Mechanical, Electrical and Manufacturing Engineering, Loughborough University, Loughborough LE11 3TU, UK
These authors contributed equally to this work.
*
Author to whom correspondence should be addressed.
Received: 22 July 2017 / Revised: 29 August 2017 / Accepted: 31 August 2017 / Published: 4 September 2017
(This article belongs to the Special Issue Cognitive Radio Sensing and Sensor Networks)
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Abstract

This paper proposes novel satellite-based wireless sensor networks (WSNs), which integrate the WSN with the cognitive satellite terrestrial network. Having the ability to provide seamless network access and alleviate the spectrum scarcity, cognitive satellite terrestrial networks are considered as a promising candidate for future wireless networks with emerging requirements of ubiquitous broadband applications and increasing demand for spectral resources. With the emerging environmental and energy cost concerns in communication systems, explicit concerns on energy efficient resource allocation in satellite networks have also recently received considerable attention. In this regard, this paper proposes energy-efficient optimal power allocation schemes in the cognitive satellite terrestrial networks for non-real-time and real-time applications, respectively, which maximize the energy efficiency (EE) of the cognitive satellite user while guaranteeing the interference at the primary terrestrial user below an acceptable level. Specifically, average interference power (AIP) constraint is employed to protect the communication quality of the primary terrestrial user while average transmit power (ATP) or peak transmit power (PTP) constraint is adopted to regulate the transmit power of the satellite user. Since the energy-efficient power allocation optimization problem belongs to the nonlinear concave fractional programming problem, we solve it by combining Dinkelbach’s method with Lagrange duality method. Simulation results demonstrate that the fading severity of the terrestrial interference link is favorable to the satellite user who can achieve EE gain under the ATP constraint comparing to the PTP constraint. View Full-Text
Keywords: wireless sensor network; cognitive satellite; power allocation; energy efficiency; fading channels; interference power constraint; transmit power constraint wireless sensor network; cognitive satellite; power allocation; energy efficiency; fading channels; interference power constraint; transmit power constraint
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Shi, S.; Li, G.; An, K.; Gao, B.; Zheng, G. Energy-Efficient Optimal Power Allocation in Integrated Wireless Sensor and Cognitive Satellite Terrestrial Networks. Sensors 2017, 17, 2025.

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