Outage probability for two-way solar-powered relay networks with stochastic scheduling

Wei Li, Meng Lin Ku, Yan Chen, K. J.Ray Liu

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

An optimal relay transmission policy by exploiting a stochastic energy harvesting (EH) model is proposed for EH two-way relay (TWR) networks, wherein a solar-powered relay with a finite-sized battery adopts an amplify-and-forward protocol for helping relaying signals. The relay transmission power is optimized to minimize the long-term outage probability by considering the causal EH information, battery energy and random channel status. The design framework is formulated as a Markov decision process (MDP), in which a monotonic structure for the long-term reward values and a threshold property for the optimal relay transmission are revealed. Furthermore, an interesting saturation structure of the outage performance is uncovered, which means the expected outage probability eventually approaches to the relay's battery empty probability. Simulation results are demonstrated to verify the theoretical analysis and prove that the proposed optimal policy outperforms other myopic policies.

Original languageEnglish
Title of host publication2015 IEEE Global Conference on Signal and Information Processing, GlobalSIP 2015
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages1230-1234
Number of pages5
ISBN (Electronic)9781479975914
DOIs
StatePublished - 23 Feb 2016
EventIEEE Global Conference on Signal and Information Processing, GlobalSIP 2015 - Orlando, United States
Duration: 13 Dec 201516 Dec 2015

Publication series

Name2015 IEEE Global Conference on Signal and Information Processing, GlobalSIP 2015

Conference

ConferenceIEEE Global Conference on Signal and Information Processing, GlobalSIP 2015
Country/TerritoryUnited States
CityOrlando
Period13/12/1516/12/15

Fingerprint

Dive into the research topics of 'Outage probability for two-way solar-powered relay networks with stochastic scheduling'. Together they form a unique fingerprint.

Cite this