Energy-Efficient Optimal Power Allocation in Integrated Wireless Sensor and Cognitive Satellite Terrestrial Networks
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...
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doaj-915bb94bb34344fbbc91c767f28d07302020-11-24T23:08:34ZengMDPI AGSensors1424-82202017-09-01179202510.3390/s17092025s17092025Energy-Efficient Optimal Power Allocation in Integrated Wireless Sensor and Cognitive Satellite Terrestrial NetworksShengchao Shi0Guangxia Li1Kang An2Bin Gao3Gan Zheng4College of Communications Engineering, PLA University of Science and Technology, No. 2 Biaoying, Qinhuai District, Nanjing 210007, ChinaCollege of Communications Engineering, PLA University of Science and Technology, No. 2 Biaoying, Qinhuai District, Nanjing 210007, ChinaCollege of Communications Engineering, PLA University of Science and Technology, No. 2 Biaoying, Qinhuai District, Nanjing 210007, ChinaCollege of Communications Engineering, PLA University of Science and Technology, No. 2 Biaoying, Qinhuai District, Nanjing 210007, ChinaWolfson School of Mechanical, Electrical and Manufacturing Engineering, Loughborough University, Loughborough LE11 3TU, UKThis 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.https://www.mdpi.com/1424-8220/17/9/2025wireless sensor networkcognitive satellitepower allocationenergy efficiencyfading channelsinterference power constrainttransmit power constraint |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Shengchao Shi Guangxia Li Kang An Bin Gao Gan Zheng |
spellingShingle |
Shengchao Shi Guangxia Li Kang An Bin Gao Gan Zheng Energy-Efficient Optimal Power Allocation in Integrated Wireless Sensor and Cognitive Satellite Terrestrial Networks Sensors wireless sensor network cognitive satellite power allocation energy efficiency fading channels interference power constraint transmit power constraint |
author_facet |
Shengchao Shi Guangxia Li Kang An Bin Gao Gan Zheng |
author_sort |
Shengchao Shi |
title |
Energy-Efficient Optimal Power Allocation in Integrated Wireless Sensor and Cognitive Satellite Terrestrial Networks |
title_short |
Energy-Efficient Optimal Power Allocation in Integrated Wireless Sensor and Cognitive Satellite Terrestrial Networks |
title_full |
Energy-Efficient Optimal Power Allocation in Integrated Wireless Sensor and Cognitive Satellite Terrestrial Networks |
title_fullStr |
Energy-Efficient Optimal Power Allocation in Integrated Wireless Sensor and Cognitive Satellite Terrestrial Networks |
title_full_unstemmed |
Energy-Efficient Optimal Power Allocation in Integrated Wireless Sensor and Cognitive Satellite Terrestrial Networks |
title_sort |
energy-efficient optimal power allocation in integrated wireless sensor and cognitive satellite terrestrial networks |
publisher |
MDPI AG |
series |
Sensors |
issn |
1424-8220 |
publishDate |
2017-09-01 |
description |
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. |
topic |
wireless sensor network cognitive satellite power allocation energy efficiency fading channels interference power constraint transmit power constraint |
url |
https://www.mdpi.com/1424-8220/17/9/2025 |
work_keys_str_mv |
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