Analysis, design and optimization of robust and secure wireless communication systems

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Wireless communications are an essential part of modern society and the way it functions at different layers. Wide availability of multi-media content puts a great demand on the supported rates and quality-of-service. A large number of sensitive transactions require a high degree of security offered by such systems. A high mobility of users makes the wireless propagation channel highly dynamic/unpredictable and hence dictates an adaptive and robust design of systems. These 3 key challenges will be addressed in the proposed project. Specifically, methods for analysis, design and optimization of secure and robust wireless communication systems will be studied.***To address the requirement for high rates, wireless multiple-input multiple-output (MIMO, or multi-antenna) systems are widely adopted by academia and industry due to their high spectral efficiency. The broadcast nature of wireless channels stimulated significant interest in their security aspects. While cryptography provides valuable tools for ensuring the secrecy of communications, it also comes with a number of drawbacks (leaked keys etc.). Physical-layer security has recently emerged as a powerful approach, which is complementary to cryptography and which allows to address a number of the shortcomings of the latter. Hence, the physical-layer security approach to MIMO channels will be studied using the tools of information and communication theory. In particular, optimal (adaptive and robust) transmission techniques will be developed, which will provide high data rates over highly-variable channels ensuring the secrecy of the transmitted data at the same time. Real-world (non-stationary, non-ergodic) nature of the wireless propagation channel as well as its estimation inaccuracy will be taken into account. The powerful tools of convex optimization will be used.******Overall, the project will address three key and inter-related aspects of secure wireless communications: its information-theoretic foundations, optimal signaling strategies and practical implementation issues (e.g. robustness to channel uncertainty).*****