Energy Efficient Adaptive Transmissions in Integrated Satellite-Terrestrial Networks with ser Constraints

Yuhan Ruan, Yongzhao Li*, Cheng-Xiang Wang, Rui Zhang

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

47 Citations (SciVal)


Allowing frequency reuse between satellite and terrestrial networks, the integrated satellite-terrestrial network can spatially optimize the usage of scarce spectrum resource and is thus becoming one of the most promising infrastructures for future multimedia services. Taking the requirements of both efficiency and reliability in satellite communications into account, we propose an adaptive transmission scheme for the integrated network in this paper, where the satellite can communicate with the destination user either in direct mode or in cooperative mode. Specifically, we first investigate the symbol error rate (SER) performance of two transmission modes with co-channel interference under composite multipath/shadowing fading. Taking the derived SERs as constraints, we formulate the adaptive transmission scheme as an optimization problem with the objective of maximizing energy efficiency (EE) and discuss the trade-off among EE, spectral efficiency (SE), and SER. Furthermore, economic efficiency is also analyzed as a complementary performance measure to SE and EE. Simulation results show that the proposed scheme can increase the attainable EE of satellite communications, which indicates that we should choose the transmission mode adaptively according to different interfering scenarios and shadowing degrees, rather than adopting cooperative transmission aggressively.

Original languageEnglish
Pages (from-to)210-222
Number of pages13
JournalIEEE Transactions on Wireless Communications
Issue number1
Early online date24 Oct 2017
Publication statusPublished - 1 Jan 2018


  • adaptive transmission
  • economic efficiency
  • energy efficiency
  • Integrated satellite-terrestrial networks
  • symbol error rate

ASJC Scopus subject areas

  • Computer Science Applications
  • Electrical and Electronic Engineering
  • Applied Mathematics


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