Physical Layer Security for 5G Distributed Massive MIMO Systems

Applications are invited for a three-year PhD studentship on the theme of physical layer security in 5G distributed massive multiple-input multiple-output (MIMO) systems.

Massive MIMO (mMIMO) is one of the most powerful spectral and energy efficient techniques for next-generation (5G and beyond) wireless communication systems. Most recently, distributed mMIMO emerges as a promising distributed network architecture that breaks the conventional cell boundaries and efficiently supports massive devices connectivity. It employs massive distributed access points (APs), e.g., smart sensors, to coherently serve user devices over the same time/frequency resource. Nevertheless, the broadcast nature of wireless channels jeopardizes the privacy of wireless communication and makes it inherently prone to eavesdropping and jamming. While traditional solutions secure communication in the application/network layer through cryptographic encryption, physical layer security techniques, from an information-theoretic perspective, secure communication directly at the physical layer. The mMIMO inherently facilitates physical layer security through jointly forming very narrow beams to the legitimate users (LU) and therefore avoiding spill over of the signal power to passive eavesdroppers (ED).

In distributed mMIMO systems, however, the distributed locations of APs impose a challenge to joint channel estimation and power control, which are essential to form the narrow beams and avoid eavesdropping. In addition, the uplink training during the channel estimation phase is vulnerable to a pilot contamination attack - the active eavesdropper pretends to be a LU and sends another valid pilot symbol of his/her own when LU transmits a pilot symbol to the APs to learn the channel coefficients. This may severely degrade the secrecy capabilities - ED may be indistinguishable from LU, and thus the system is unable to protect the privacy of wireless communication at all.

This PhD project will focus on both theoretic limits and algorithm design for physical layer security in distributed mMIMO systems. The theoretical aspect is to characterise the information-theoretic limits of secure communications in the presence of passive/active eavesdroppers. The practical aspect is to translate the insights of theoretical findings to distributed algorithm design and potential implementations. This project can be divided into three tasks: (1) Construct a unifying framework, from an information-theoretic perspective, for the system modelling and secrecy capacity characterisation of distributed mMIMO systems in the presence of passive/active eavesdroppers; (2) Develop and analyse distributed secure transmission schemes (e.g., artificial noise, cooperative jamming) with proper pilot assignment and power control optimisation to cope with passive eavesdropping; (3) Develop distributed algorithms to detect and mitigate pilot contamination attack by active eavesdroppers using supervised/unsupervised learning methods, and implement secure protocols at both physical and network layers.

The applicant should hold or expect to hold a 2.1 Hons (or equivalent) undergraduate degree or MSc in a relevant discipline such as Communication Engineering, Computer Science, Electrical Engineering, Applied Mathematics, Theoretical Physics, Operational Research, etc. A relevant Master’s degree and/or experience in one or more of the following will be an advantage: information theory, wireless communications, optimisation, machine learning, signal processing and statistics. Should have strong mathematical background and/or programming skills in languages such as MATLAB, Python, R, C++ are highly desirable. The applicant must have good communication skills, both verbal and in writing (English), be self-motivated and helpful team member.

Applications should be made formally by following the University of Liverpool’s standard process. Details can be found here: https://www.liverpool.ac.uk/electrical-engineering-and-electronics/postgraduate/phd/phd-apply/. Applications should list Dr Xinping Yi as the potential supervisor and choose the option "School funded PhD" when asked how you will fund the PhD.