Wireless Powered Cooperative Jamming for Secure OFDM System

TL;DR

This paper proposes a wireless powered cooperative jamming scheme for OFDM systems to enhance secrecy rates, optimizing power and time allocation with both optimal and low-complexity solutions, demonstrating significant improvements over benchmarks.

Contribution

It introduces a novel harvest-then-jam protocol with joint power and time optimization for secure OFDM communication, including solutions for different receiver types.

Findings

Optimal solution via Lagrange dual method with high complexity

Low-complexity algorithms based on minorization maximization and heuristics

Significant secrecy rate improvements over benchmark schemes

Abstract

This paper studies the secrecy communication in an orthogonal frequency division multiplexing (OFDM) system, where a source sends confidential information to a destination in the presence of a potential eavesdropper. We employ wireless powered cooperative jamming to improve the secrecy rate of this system with the assistance of a cooperative jammer, which works in the harvest-then-jam protocol over two time-slots. In the first slot, the source sends dedicated energy signals to power the jammer; in the second slot, the jammer uses the harvested energy to jam the eavesdropper, in order to protect the simultaneous secrecy communication from the source to the destination. In particular, we consider two types of receivers at the destination, namely Type-I and Type-II receivers, which do not have and have the capability of canceling the (a-priori known) jamming signals, respectively. For both types of receivers, we maximize the secrecy rate at the destination by jointly optimizing the transmit power allocation at the source and the jammer over sub-carriers, as well as the time allocation between the two time-slots. First, we present the globally optimal solution to this problem via the Lagrange dual method, which, however, is of high implementation complexity. Next, to balance tradeoff between the algorithm complexity and performance, we propose alternative low-complexity solutions based on minorization maximization and heuristic successive optimization, respectively. Simulation results show that the proposed approaches significantly improve the secrecy rate, as compared to benchmark schemes without joint power and time allocation.