Linear Precoding for Relay Networks with Finite-Alphabet Constraints

In this paper, we investigate the optimal precoding scheme for relay networks with finite-alphabet constraints. We show that the previous work utilizing various design criteria to maximize either the diversity order or the transmission rate with the Gaussian-input assumption may lead to significant loss for a practical system with finite constellation set constraint. A linear precoding scheme is proposed to maximize the mutual information for relay networks. We exploit the structure of the optimal precoding matrix and develop a unified two-step iterative algorithm utilizing the theory of convex optimization and optimization on the complex Stiefel manifold. Numerical examples show that this novel iterative algorithm achieves significant gains compared to its conventional counterpart.Comment: Accepted by IEEE Int. Conf. Commun. (ICC), Kyoto, Japan, 201

Power allocation and linear precoding for wireless communications with finite-alphabet inputs

This dissertation proposes a new approach to maximizing data rate/throughput of practical communication system/networks through linear precoding and power allocation. First, the mutual information or capacity region is derived for finite-alphabet inputs such as phase-shift keying (PSK), pulse-amplitude modulation (PAM), and quadrature amplitude modulation (QAM) signals. This approach, without the commonly used Gaussian input assumptions, complicates the mutual information analysis and precoder design but improves performance when the designed precoders are applied to practical systems and networks. Second, several numerical optimization methods are developed for multiple-input multiple-output (MIMO) multiple access channels, dual-hop relay networks, and point-to-point MIMO systems. In MIMO multiple access channels, an iterative weighted sum rate maximization algorithm is proposed which utilizes an alternating optimization strategy and gradient descent update. In dual-hop relay networks, the structure of the optimal precoder is exploited to develop a two-step iterative algorithm based on convex optimization and optimization on the Stiefel manifold. The proposed algorithm is insensitive to initial point selection and able to achieve a near global optimal precoder solution. The gradient descent method is also used to obtain the optimal power allocation scheme which maximizes the mutual information between the source node and destination node in dual-hop relay networks. For point-to-point MIMO systems, a low complexity precoding design method is proposed, which maximizes the lower bound of the mutual information with discretized power allocation vector in a non-iterative fashion, thus reducing complexity. Finally, performances of the proposed power allocation and linear precoding schemes are evaluated in terms of both mutual information and bit error rate (BER). Numerical results show that at the same target mutual information or sum rate, the proposed approaches achieve 3-10dB gains compared to the existing methods in the medium signal-to-noise ratio region. Such significant gains are also indicated in the coded BER systems --Abstract, page iv-v

A Survey of Physical Layer Security Techniques for 5G Wireless Networks and Challenges Ahead

Physical layer security which safeguards data confidentiality based on the information-theoretic approaches has received significant research interest recently. The key idea behind physical layer security is to utilize the intrinsic randomness of the transmission channel to guarantee the security in physical layer. The evolution towards 5G wireless communications poses new challenges for physical layer security research. This paper provides a latest survey of the physical layer security research on various promising 5G technologies, including physical layer security coding, massive multiple-input multiple-output, millimeter wave communications, heterogeneous networks, non-orthogonal multiple access, full duplex technology, etc. Technical challenges which remain unresolved at the time of writing are summarized and the future trends of physical layer security in 5G and beyond are discussed.Comment: To appear in IEEE Journal on Selected Areas in Communication

An Overview of Physical Layer Security with Finite-Alphabet Signaling

Providing secure communications over the physical layer with the objective of achieving perfect secrecy without requiring a secret key has been receiving growing attention within the past decade. The vast majority of the existing studies in the area of physical layer security focus exclusively on the scenarios where the channel inputs are Gaussian distributed. However, in practice, the signals employed for transmission are drawn from discrete signal constellations such as phase shift keying and quadrature amplitude modulation. Hence, understanding the impact of the finite-alphabet input constraints and designing secure transmission schemes under this assumption is a mandatory step towards a practical implementation of physical layer security. With this motivation, this article reviews recent developments on physical layer security with finite-alphabet inputs. We explore transmit signal design algorithms for single-antenna as well as multi-antenna wiretap channels under different assumptions on the channel state information at the transmitter. Moreover, we present a review of the recent results on secure transmission with discrete signaling for various scenarios including multi-carrier transmission systems, broadcast channels with confidential messages, cognitive multiple access and relay networks. Throughout the article, we stress the important behavioral differences of discrete versus Gaussian inputs in the context of the physical layer security. We also present an overview of practical code construction over Gaussian and fading wiretap channels, and we discuss some open problems and directions for future research.Comment: Submitted to IEEE Communications Surveys & Tutorials (1st Revision

A Novel Power Allocation Scheme for Two-User GMAC with Finite Input Constellations

Constellation Constrained (CC) capacity regions of two-user Gaussian Multiple Access Channels (GMAC) have been recently reported, wherein an appropriate angle of rotation between the constellations of the two users is shown to enlarge the CC capacity region. We refer to such a scheme as the Constellation Rotation (CR) scheme. In this paper, we propose a novel scheme called the Constellation Power Allocation (CPA) scheme, wherein the instantaneous transmit power of the two users are varied by maintaining their average power constraints. We show that the CPA scheme offers CC sum capacities equal (at low SNR values) or close (at high SNR values) to those offered by the CR scheme with reduced decoding complexity for QAM constellations. We study the robustness of the CPA scheme for random phase offsets in the channel and unequal average power constraints for the two users. With random phase offsets in the channel, we show that the CC sum capacity offered by the CPA scheme is more than the CR scheme at high SNR values. With unequal average power constraints, we show that the CPA scheme provides maximum gain when the power levels are close, and the advantage diminishes with the increase in the power difference.Comment: To appear in IEEE Transactions on Wireless Communications, 10 pages and 7 figure