Dual-battery enabled green proximal M2M communications in LPWA for IoT

Xilong Liu, Nirwan Ansari

Research output: Chapter in Book/Report/Conference proceedingConference contribution

5 Scopus citations


Internet of Things (IoT) promotes a heightened level of awareness about our world and makes our life more intelligent and convenient. In IoT, machine-to-machine (M2M) communications enables direct connectivities among machines and devices to automatically exchange information and perform actions. Low Power Wide Area (LPWA) plays a crucial role in provisioning wide area coverage and low energy consumption network for M2M communications in IoT. Moreover, green energy harvesting is essential for mobile machine type-devices (MTDs) to achieve their self-sustainability and independence. Therefore, we propose dual-battery architecture to empower MTDs with concurrent green energy harvesting and IoT functionalities. Rather than routing through an LPWA base station (BS), direct and dual-hop transmissions are proposed for proximal M2M communications. According to the residual green energy in the MTDs' batteries, we provision a relay incentive policy and relay selection schemes to facilitate direct and dual-hop M2M communications. For dual-hop M2M communications, some heuristics are proposed to maximize the overall data rate with low computational complexity. Finally, we validate the performances of the proposed architecture and schemes through extensive simulations.

Original languageEnglish (US)
Title of host publication2018 IEEE International Conference on Communications, ICC 2018 - Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Print)9781538631805
StatePublished - Jul 27 2018
Event2018 IEEE International Conference on Communications, ICC 2018 - Kansas City, United States
Duration: May 20 2018May 24 2018

Publication series

NameIEEE International Conference on Communications
ISSN (Print)1550-3607


Other2018 IEEE International Conference on Communications, ICC 2018
Country/TerritoryUnited States
CityKansas City

All Science Journal Classification (ASJC) codes

  • Computer Networks and Communications
  • Electrical and Electronic Engineering


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