Energy Efficient Communication for Secure D2D Underlaid Cellular Networks

Younggap Kwon, Hyunjoon Suh, Jintaek Oh, Taewon Hwang

Research output: Contribution to journalArticle

11 Citations (Scopus)

Abstract

We study energy-efficient secure communication in large-scale device-To-device (D2D) underlaid cellular networks, where base stations (BSs) and D2D users send their messages occupying the same spectrum while eavesdroppers (Eve nodes) overhear their transmissions. First, we consider the secure cellular network where users operate only in the cellular mode. We propose a link adaptation of the cellular network that strikes a balance between secrecy energy efficiency (SEE) and secrecy spectral efficiency (SSE) by maximizing the weighted product of SEE and SSE. Besides, we show that SSE first increases and then decreases with the BS power when the ratio of the eavesdropper (Eve) node density to the BS density is above a certain threshold while it monotonically increases when the Eve-To-BS density ratio is below the threshold. On the other hand, SEE first increases and then decreases with the BS power regardless of the Eve-To-BS density ratio. Next, we study how to deploy the secure D2D network under the existing secure cellular network while guaranteeing an acceptable secrecy performance of the cellular network. We show that the secrecy performance of the cellular network decreases with the D2D power when the Eve nodes are sparse while it first increases and then decreases when the Eve nodes are dense. Based on the result, we propose a link adaptation for the D2D network that maximizes the weighted product of SEE and SSE under the secrecy performance constraint of the cellular network. Simulation results show that the proposed link-Adaptation schemes can achieve all the points on the Pareto boundary in SSE-SEE plane.

Original languageEnglish
Article number7944601
Pages (from-to)9110-9123
Number of pages14
JournalIEEE Transactions on Vehicular Technology
Volume66
Issue number10
DOIs
Publication statusPublished - 2017 Oct

All Science Journal Classification (ASJC) codes

  • Automotive Engineering
  • Aerospace Engineering
  • Electrical and Electronic Engineering
  • Applied Mathematics

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