Distributed Null-Steering Beamformer Design for Physical Layer Security Enhancement in Internet-of-Things Networks

With the rapid proliferation of the Internet of Things (IoT), small devices in various applications generate, process, and exchange security and safety-critical data as well as privacy-sensitive information. However, due to limited hardware capabilities of such small devices, the IoT networks are inherently vulnerable to security attacks. In this context, the analog cooperative beamforming (ACB)-based physical layer security (PLS) technique can be a suitable solution to guarantee security in the IoT networks by creating a virtual antenna array with multiple IoT devices. Nevertheless, such techniques suffer from poor secrecy performance, when an eavesdropper is located within the main beam toward the legitimate receiver. Motivated by this limitation, in this article, we propose a fully distributed null-steering beamformer, which is suitable for IoT networks following decentralized architecture. Through analysis and simulation, we show that the proposed PLS algorithm outperforms the existing ACB-based PLS scheme. Furthermore, we show that there exists an optimal degree of nulling that maximizes the secrecy performance, which can be estimated based on the analytical results.

I. Introduction

In wireless communications, a significant amount of effort has been devoted to guarantee security by preventing an eavesdropper from overhearing [1]. Originally, security was regarded as a high-layer problem to be tackled using cryptographic methods. However, in general, such security solutions in the high layer are complex and need an infrastructure to generate and manage public or private keys [2]. For this reason, physical layer security (PLS) based on information theory has been gaining increasing attention in recent years because security key distribution and management are not required [3]. Specifically, the fundamental principle behind PLS is to exploit the inherent randomness of noise and communication channels, which are known to the trusted transmitter and the legitimate receiver but not to an eavesdropper [4]. This helps to protect the signal from being detected, demodulated, or decoded properly, making the unintended receiver unable to even understand the information-carrying signal [1].