Power Allocation for Fingerprint-Based PHY-Layer Authentication with mmWave UAV Networks

TL;DR

This paper proposes a power allocation method for fingerprint-based physical layer authentication in mmWave UAV networks, enhancing security and rate performance by exploiting 3D spatial beamforming.

Contribution

It introduces a novel power allocation scheme that balances secrecy and data rate in multi-user mmWave UAV networks using fingerprint authentication.

Findings

Achieves optimal achievable rate with expected secrecy.

Effectively manages power between precoder and authentication tag.

Enhances security leveraging mmWave beamforming in UAV networks.

Abstract

Physical layer security (PLS) techniques can help to protect wireless networks from eavesdropper attacks. In this paper, we consider the authentication technique that uses fingerprint embedding to defend 5G cellular networks with unmanned aerial vehicle (UAV) systems from eavesdroppers and intruders. Since the millimeter wave (mmWave) cellular networks use narrow and directional beams, PLS can take further advantage of the 3D spatial dimension for improving the authentication of UAV users. Considering a multi-user mmWave cellular network, we propose a power allocation technique that jointly takes into account splitting of the transmit power between the precoder and the authentication tag, which manages both the secrecy as well as the achievable rate. Our results show that we can obtain optimal achievable rate with expected secrecy.