Pilot Contamination Attack Detection for 5G MmWave Grant-Free IoT Networks

Grant-free random access is an emerging technology for providing massive connectivity for 5G massive machine-type communications (mMTC), where non-orthogonal pilot sequences are used to simultaneously detect active users and estimate channels. However, grant-free 5G IoT networks are vulnerable to pilot contamination attacks (PCA), where the attacker can send the same pilots as legitimate IoT users to harm the active user detection and channel estimation. To defend against this attack, in this article, we propose a physical-layer countermeasure based on the channel virtual representation (CVR). CVR can emphasize the unique characteristics of mmWave channels that are sensitive to the location of the sender. This can be utilized to counter PCA no matter if the attacker's pilots are superimposed to that of the victim or not. Based on this observation, to achieve an efficient PCA detection, a single-hidden-layer multiple measurement (SHMM) Siamese network is employed. This solution tackles the challenges of channel randomness and massive connectivity in mMTC IoT networks, and supports small sample learning. Simulation results evaluate and confirm the effectiveness of the proposed detection scheme under various scenarios. The detection accuracy can approach 99% with 128 antennas at the receiver and reach above 95% even with only 50 training samples.

I. Introduction

It is envisioned that the fifth-generation (5G) cellular communication systems will provide massive connectivity for machine-type communications (mMTC) [1], [2]. MMTC is able to support the diverse Internet of Things (IoT) applications such as environmental sensing, smart manufacturing and smart farming. Compared with conventional human-centric communication, mMTC IoT communications have two distinctive characteristics: (i) there are a massive number of machine-type connections; (ii) only a small and random fraction of the devices are active at any given instant. To accommodate these communication characteristics, grant-free random access schemes are proposed as promising solutions to enable massive connectivity with low-latency in mMTC 5G IoT networks [3]. In grant-free schemes, each active device directly transmits its identity and data to the based station (BS) without waiting for any permission, and the non-orthogonal pilot sequences are used to identify active users and estimate the corresponding channels [4], [5].