Secure Communication for Spatially Sparse Millimeter-Wave Massive MIMO Channels via Hybrid Precoding

In this paper, we investigate secure communication over sparse millimeter-wave (mm-Wave) massive multiple-input multiple-output (MIMO) channels by exploiting the spatial sparsity of legitimate user's channel. We propose a secure communication scheme in which information data is precoded onto dominant angle components of the sparse channel through a limited number of radio-frequency (RF) chains, while artificial noise (AN) is broadcast over the remaining nondominant angles interfering only with the eavesdropper with a high probability. It is shown that the channel sparsity plays a fundamental role analogous to secret keys in achieving secure communication. Hence, by defining two statistical measures of the channel sparsity, we analytically characterize its impact on secrecy rate. In particular, a substantial improvement on secrecy rate can be obtained by the proposed scheme due to the uncertainty, i.e., 'entropy', introduced by the channel sparsity which is unknown to the eavesdropper. It is revealed that sparsity in the power domain can always contribute to the secrecy rate. In contrast, in the angle domain, there exists an optimal level of sparsity that maximizes the secrecy rate. The effectiveness of the proposed scheme and derived results are verified by numerical simulations

Cost-Effective Signal Processing Algorithms for Physical-Layer Security in Wireless Networks

Data privacy in traditional wireless communications is accomplished by cryptography techniques at the upper layers of the protocol stack. This thesis aims at contributing to the critical security issue residing in the physical-layer of wireless networks, namely, secrecy rate in various transmission environments. Physical-layer security opens the gate to the exploitation of channel characteristics to achieve data secure transmission. Precoding techniques, as a critical aspect in pre-processing signals prior to transmission has become an effective approach and recently drawn significant attention in the literature. In our research, novel non-linear precoders are designed focusing on the improvement of the physical-layer secrecy rate with consideration of computational complexity as well as the Bit Error Ratio (BER) performance. In the process of designing the precoder, strategies such as Lattice Reduction (LR) and Artificial Noise (AN) are employed to achieve certain design requirements. The deployment and allocation of resources such as relays to assist the transmission also have gained significant interest. In multiple-antenna relay networks, we examine various relay selection criteria with arbitrary knowledge of the channels to the users and the eavesdroppers. Furthermore, we provide novel effective relay selection criteria that can achieve a high secrecy rate performance. More importantly they do not require knowledge of the channels of the eavesdroppers and the interference. Combining the jamming technique with resource allocation of relay networks, we investigate an opportunistic relaying and jamming scheme for Multiple-Input Multiple-Output (MIMO) buffer-aided downlink relay networks. More specifically, a novel Relaying and Jamming Function Selection (RJFS) algorithm as well as a buffer-aided RJFS algorithm are developed along with their ability to achieve a higher secrecy rate. Relying on the proposed relay network, we detail the characteristics of the system, under various relay selection criteria, develop exhaustive search and greedy search-based algorithms, with or without inter-relay Interference Cancellation (IC)