Secrecy-Optimized Resource Allocation for Device-to-Device Communication Underlaying Heterogeneous Networks

TL;DR

This paper proposes a novel resource allocation method to maximize secure capacity in D2D underlaying HetNets, effectively enhancing security against eavesdropping while maintaining spectral efficiency.

Contribution

It introduces a convex reformulation of the non-convex optimization problem and develops a heuristic iterative algorithm based on proximal theory for secure resource allocation.

Findings

Significant improvement in secure capacity achieved

Fast convergence of the proposed algorithm

Effective handling of transmit rate and power constraints

Abstract

Device-to-device (D2D) communications recently have attracted much attention for its potential capability to improve spectral efficiency underlaying the existing heterogeneous networks (HetNets). Due to no sophisticated control, D2D user equipments (DUEs) themselves cannot resist eavesdropping or security attacks. It is urgent to maximize the secure capacity for both cellular users and DUEs. This paper formulates the radio resource allocation problem to maximize the secure capacity of DUEs for the D2D communication underlaying HetNets which consist of high power nodes and low power nodes. The optimization objective function with transmit bit rate and power constraints, which is non-convex and hard to be directly derived, is firstly transformed into matrix form. Then the equivalent convex form of the optimization problem is derived according to the Perron-Frobenius theory. A heuristic iterative algorithm based on the proximal theory is proposed to solve this equivalent convex problem through evaluating the proximal operator of Lagrange function. Numerical results show that the proposed radio resource allocation solution significantly improves the secure capacity with a fast convergence speed.