UBC Theses and Dissertations

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UBC Theses and Dissertations

Physical layer security in massive MIMO systems Zhu, Jun


Massive multiple-input multiple-output (MIMO) is one of the key technologies for the emerging fifth generation (5G) wireless networks, and has the potential to tremendously improve spectral and energy efficiency with low-cost implementations. While massive MIMO systems have drawn great attention from both academia and industry, few efforts have been made on how the richness of the spatial dimensions offered by massive MIMO affects wireless security. As security is crucial in all wireless systems due to the broadcast nature of the wireless medium, in this thesis, we study how massive MIMO technology can be used to guarantee communication security in the presence of a passive multi-antenna eavesdropper. Our proposed massive MIMO system model incorporates relevant design choices and constraints such as time-division duplex (TDD), uplink training, pilot contamination, low-complexity signal processing, and low-cost hardware components. The thesis consists of three main parts. We first consider physical layer security for a massive MIMO system employing simple artificial noise (AN)-aided matched-filter (MF) precoding at the base station (BS). For both cases of perfect training and pilot contamination, we derive a tight analytical lower bound for the achievable ergodic secrecy rate, and an upper bound for the secrecy outage probability. Both bounds are expressed in closed form, providing an explicit relationship between all system parameters, offering significant insights for system design. We then generalize the work by comparing different types of linear data and AN precoders in a secure massive MIMO network. The system performance, in terms of the achievable ergodic secrecy rate is obtained in closed form. In addition, we propose a novel low-complexity data and AN precoding strategy based on a matrix polynomial expansion. Finally, we consider a more realistic system model by taking into account non-ideal hardware components. Based on a general hardware impairment model, we derive a lower bound for the ergodic secrecy rate achieved by each user when AN-aided MF precoding is employed at the BS. By exploiting the derived analytical bound, we investigate the impact of various system parameters on the secrecy rate and optimize both the uplink training pilots and AN precoder to maximize the secrecy rate.

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