Secure Communication through Wireless-Powered Friendly Jamming: Jointly Online Optimization over Geography, Energy and Time

TL;DR

This paper proposes a distributed online optimization framework for deploying wireless-powered friendly jammers to enhance secure communication, maximizing energy efficiency and network lifetime in geographic regions with heterogeneous energy demands.

Contribution

It introduces the first distributed scalable solutions for jammer placement and power allocation using wireless energy harvesting, with approximation algorithms for NP-hard placement problems.

Findings

Distributed online algorithms effectively optimize jammer placement and power.

Near-optimal PTAS algorithms address NP-hard placement problems.

Extended multi-channel scenarios improve energy efficiency and reduce jammer count.

Abstract

Exploring the interference-emitting friendly jammers to protect the sensitive communications in the presence of eavesdroppers has increasingly being investigated in literature. In parallel, scavenging energy from abient radio signals for energy-constrained devices, namely \emph{wireless energy harvesting} (WEH), has also drawn significant attention. Without relying on external energy supply, the wireless-powered friendly jammer by WEH from legitimate wireless devices is an effective approach to prolong their lifetime and gain the flexibility in deployments. This paper studies the online optimization of the placement and WEH of a set of friendly jammers in a geographic location with the energy-efficiency (EE) consideration. We adopt a simple "time switching" protocol where power transfer and jammer-assisted secure communications occur in different time blocks when WEH requests are launched. Our scheme has the following important advantages: 1) The proposed online jammers placement and interfering power allocation to attack eavesdroppers is the first distributed and scalable solutions within any specified geographic region, 2) We model the WEH for jammers as a \emph{JAM-NET lifetime maximization problem}, where online scheduling algorithms with heterogeneous energy demands of each jammer (from energy sources) are designed, 3) Under our model, the problem of placing a minimum number of jammers with distance-based power assignments is NP-hard, and near optimal PTAS approximation algorithms are provided, 4) When durations of the eavesdropping and legitimate communicating are available and the scenario is extended to the multi-channels setting, our results are strengthened to see further improved EE and reduced number of jammers. Simulations back up our theory.