Power Allocation in Land Mobile Satellite Systems: An Energy-Efficient Perspective

Energy-efficient resource allocation schemes have gained considerable attention in satellite communications since the energy consumption powered by solar panels or batteries strongly affect the on-board payload and operation lifetime. This letter proposes an energy-efficient power allocation scheme in a downlink land mobile satellite (LMS) system, which aims at maximizing the ratio of average rate over the total consumed power. With the aid of fractional programming, the energy-efficient optimal power allocation coefficient is first obtained for the LMS system by considering the practical propagation environment and maximum transmit power constraint. Then, analytical result for the optimal mean energy efficiency (EE) of the considered system is derived, which provides an effective approach to evaluate the satellite beam angle, terminal’s elevation angle, and constant circuit power consumption on the EE of the LMS system.

[1]  K. ArtiM.,et al.  Channel Estimation and Detection in Satellite Communication Systems , 2016, IEEE Trans. Veh. Technol..

[2]  Ali Abdi,et al.  A new simple model for land mobile satellite channels: first- and second-order statistics , 2003, IEEE Trans. Wirel. Commun..

[3]  Fatih Alagöz,et al.  Energy Efficiency and Satellite Networking: A Holistic Overview , 2011, Proc. IEEE.

[4]  M. K. Arti.  Performance evaluation of maximal ratio combining in Shadowed-Rician fading land mobile satellite channels with estimated channel gains , 2015, IET Commun..

[5]  K. ArtiM..  Beamforming and combining based scheme over κ - μ shadowed fading satellite channels , 2016, IET Commun..

[6]  Athanasios D. Panagopoulos,et al.  Climatic-dependent energy efficient design of satellite links operating above 10GHz: An optimal stopping approach , 2014, The 8th European Conference on Antennas and Propagation (EuCAP 2014).

[7]  Mingwei Xu,et al.  Towards Energy-Efficient Routing in Satellite Networks , 2016, IEEE Journal on Selected Areas in Communications.

[8]  Daniele Tarchi,et al.  Energy Efficient Adaptive Network Coding Schemes for Satellite Communications , 2016, WISATS.

[9]  Manav R. Bhatnagar,et al.  Two-Way Mobile Satellite Relaying: A Beamforming and Combining Based Approach , 2014, IEEE Communications Letters.

[10]  Xiao Ma,et al.  Mean Energy Efficiency Maximization in Cognitive Radio Channels With PU Outage Constraint , 2015, IEEE Communications Letters.

[11]  Symeon Chatzinotas,et al.  Energy-efficient MMSE beamforming and power allocation in multibeam satellite systems , 2011, 2011 Conference Record of the Forty Fifth Asilomar Conference on Signals, Systems and Computers (ASILOMAR).

[12]  K. ArtiM..  Channel Estimation and Detection in Hybrid Satellite-Terrestrial Communication Systems , 2016, IEEE Trans. Veh. Technol..

[13]  Philip Constantinou,et al.  Power Allocation in Cognitive Satellite Terrestrial Networks with QoS Constraints , 2013, IEEE Communications Letters.

[14]  Philip Constantinou,et al.  Effective Capacity and Optimal Power Allocation for Mobile Satellite Systems and Services , 2012, IEEE Communications Letters.

[15]  M. K. Arti.  Imperfect CSI based AF relaying in hybrid satellite-terrestrial cooperative communication systems , 2015, 2015 IEEE International Conference on Communication Workshop (ICCW).

[16]  Manav R. Bhatnagar,et al.  On the Closed-Form Performance Analysis of Maximal Ratio Combining in Shadowed-Rician Fading LMS Channels , 2014, IEEE Communications Letters.

[17]  Xiaoming Xu,et al.  Resource Allocations for Secure Cognitive Satellite-Terrestrial Networks , 2017, IEEE Wireless Communications Letters.

[18]  Symeon Chatzinotas,et al.  Resource Allocation for Cognitive Satellite Communications With Incumbent Terrestrial Networks , 2015, IEEE Transactions on Cognitive Communications and Networking.