MIMO DF Relay Beamforming for Secrecy with Artificial Noise, Imperfect CSI, and Finite-Alphabet

In this paper, we consider decode-and-forward (DF) relay beamforming with imperfect channel state information (CSI), cooperative artificial noise (AN) injection, and finite-alphabet input in the presence of an user and $J$ non-colluding eavesdroppers. The communication between the source and the user is aided by a multiple-input-multiple-output (MIMO) DF relay. We use the fact that a wiretap code consists of two parts: i) common message (non-secret), and ii) secret message. The source transmits two independent messages: i) common message (non-secret), and ii) secret message. The common message is transmitted at a fixed rate $R_{0}$, and it is intended for the user. The secret message is also intended for the user but it should be kept secret from the $J$ eavesdroppers. The source and the MIMO DF relay operate under individual power constraints. In order to improve the secrecy rate, the MIMO relay also injects artificial noise. The CSI on all the links are assumed to be imperfect and CSI errors are assumed to be norm bounded. In order to maximize the worst case secrecy rate, we maximize the worst case link information rate to the user subject to: i) the individual power constraints on the source and the MIMO relay, and ii) the best case link information rates to $J$ eavesdroppers be less than or equal to $R_{0}$ in order to support a fixed common message rate $R_{0}$. Numerical results showing the effect of perfect/imperfect CSI, presence/absence of AN with finite-alphabet input on the secrecy rate are presented

A Survey on MIMO Transmission with Discrete Input Signals: Technical Challenges, Advances, and Future Trends

Multiple antennas have been exploited for spatial multiplexing and diversity transmission in a wide range of communication applications. However, most of the advances in the design of high speed wireless multiple-input multiple output (MIMO) systems are based on information-theoretic principles that demonstrate how to efficiently transmit signals conforming to Gaussian distribution. Although the Gaussian signal is capacity-achieving, signals conforming to discrete constellations are transmitted in practical communication systems. As a result, this paper is motivated to provide a comprehensive overview on MIMO transmission design with discrete input signals. We first summarize the existing fundamental results for MIMO systems with discrete input signals. Then, focusing on the basic point-to-point MIMO systems, we examine transmission schemes based on three most important criteria for communication systems: the mutual information driven designs, the mean square error driven designs, and the diversity driven designs. Particularly, a unified framework which designs low complexity transmission schemes applicable to massive MIMO systems in upcoming 5G wireless networks is provided in the first time. Moreover, adaptive transmission designs which switch among these criteria based on the channel conditions to formulate the best transmission strategy are discussed. Then, we provide a survey of the transmission designs with discrete input signals for multiuser MIMO scenarios, including MIMO uplink transmission, MIMO downlink transmission, MIMO interference channel, and MIMO wiretap channel. Additionally, we discuss the transmission designs with discrete input signals for other systems using MIMO technology. Finally, technical challenges which remain unresolved at the time of writing are summarized and the future trends of transmission designs with discrete input signals are addressed.Comment: 110 pages, 512 references, submit to Proceedings of the IEE