Rethinking Secure Precoding via Interference Exploitation: A Smart Eavesdropper Perspective

Based on the concept of constructive interference (CI), multiuser interference (MUI) has recently been shown to be beneficial for communication secrecy. A few CI-based secure precoding algorithms have been proposed that use both the channel state information (CSI) and knowledge of the instantaneous transmit symbols. In this paper, we examine the CI-based secure precoding problem with a focus on smart eavesdroppers that exploit statistical information gleaned from the precoded data for symbol detection. Moreover, the impact of correlation between the main and eavesdropper channels is taken into account. We first modify an existing CI-based preocding scheme to better utilize the destructive impact of the interference. Then, we point out the drawback of both the existing and the new modified CI-based precoders when faced with a smart eavesdropper. To address this deficiency, we provide a general principle for precoder design and then give two specific design examples. Finally, the scenario where the eavesdropper's CSI is unavailable is studied. Numerical results show that although our modified CI-based precoder can achieve a better energy-secrecy trade-off than the existing approach, both have a limited secrecy benefit. On the contrary, the precoders developed using the new CI-design principle can achieve a much improved trade-off and significantly degrade the eavesdropper's performance

Massive MIMO transmission techniques

Next generation of mobile communication systems must support astounding data traffic increases, higher data rates and lower latency, among other requirements. These requirements should be met while assuring energy efficiency for mobile devices and base stations. Several technologies are being proposed for 5G, but a consensus begins to emerge. Most likely, the future core 5G technologies will include massive MIMO (Multiple Input Multiple Output) and beamforming schemes operating in the millimeter wave spectrum. As soon as the millimeter wave propagation difficulties are overcome, the full potential of massive MIMO structures can be tapped. The present work proposes a new transmission system with bi-dimensional antenna arrays working at millimeter wave frequencies, where the multiple antenna configurations can be used to obtain very high gain and directive transmission in point to point communications. A combination of beamforming with a constellation shaping scheme is proposed, that enables good user isolation and protection against eavesdropping, while simultaneously assuring power efficient amplification of multi-level constellations

Statistical-CSI-Based Antenna Selection and Precoding in Uplink MIMO

Classical antenna selection schemes require instantaneous channel state information (CSI). This leads to high signaling overhead in the system. This work proposes a novel joint receive antenna selection and precoding scheme for multiuser multiple-input multiple-output uplink transmission that relies only on the long-term statistics of the CSI. The proposed scheme designs the switching network and the uplink precoders, such that the expected throughput of the system in the long term is maximized. Invoking results from the random matrix theory, we derive a closed-form expression for the expected throughput of the system. We then develop a tractable iterative algorithm to tackle the throughput maximization problem, capitalizing on the alternating optimization and majorization-maximization (MM) techniques. Numerical results substantiate the efficiency of the proposed approach and its superior performance as compared with the baseline.Comment: 6 page

Novel transmission and beamforming strategies for multiuser MIMO with various CSIT types

In multiuser multi-antenna wireless systems, the transmission and beamforming strategies that achieve the sum rate capacity depend critically on the acquisition of perfect Channel State Information at the Transmitter (CSIT). Accordingly, a high-rate low-latency feedback link between the receiver and the transmitter is required to keep the latter accurately and instantaneously informed about the CSI. In realistic wireless systems, however, only imperfect CSIT is achievable due to pilot contamination, estimation error, limited feedback and delay, etc. As an intermediate solution, this thesis investigates novel transmission strategies suitable for various imperfect CSIT scenarios and the associated beamforming techniques to optimise the rate performance. First, we consider a two-user Multiple-Input-Single-Output (MISO) Broadcast Channel (BC) under statistical and delayed CSIT. We mainly focus on linear beamforming and power allocation designs for ergodic sum rate maximisation. The proposed designs enable higher sum rate than the conventional designs. Interestingly, we propose a novel transmission framework which makes better use of statistical and delayed CSIT and smoothly bridges between statistical CSIT-based strategies and delayed CSIT-based strategies. Second, we consider a multiuser massive MIMO system under partial and statistical CSIT. In order to tackle multiuser interference incurred by partial CSIT, a Rate-Splitting (RS) transmission strategy has been proposed recently. We generalise the idea of RS into the large-scale array. By further exploiting statistical CSIT, we propose a novel framework Hierarchical-Rate-Splitting that is particularly suited to massive MIMO systems. Third, we consider a multiuser Millimetre Wave (mmWave) system with hybrid analog/digital precoding under statistical and quantised CSIT. We leverage statistical CSIT to design digital precoder for interference mitigation while all feedback overhead is reserved for precise analog beamforming. For very limited feedback and/or very sparse channels, the proposed precoding scheme yields higher sum rate than the conventional precoding schemes under a fixed total feedback constraint. Moreover, a RS transmission strategy is introduced to further tackle the multiuser interference, enabling remarkable saving in feedback overhead compared with conventional transmission strategies. Finally, we investigate the downlink hybrid precoding for physical layer multicasting with a limited number of RF chains. We propose a low complexity algorithm to compute the analog precoder that achieves near-optimal max-min performance. Moreover, we derive a simple condition under which the hybrid precoding driven by a limited number of RF chains incurs no loss of optimality with respect to the fully digital precoding case.Open Acces

A Tutorial on Extremely Large-Scale MIMO for 6G: Fundamentals, Signal Processing, and Applications

Extremely large-scale multiple-input-multiple-output (XL-MIMO), which offers vast spatial degrees of freedom, has emerged as a potentially pivotal enabling technology for the sixth generation (6G) of wireless mobile networks. With its growing significance, both opportunities and challenges are concurrently manifesting. This paper presents a comprehensive survey of research on XL-MIMO wireless systems. In particular, we introduce four XL-MIMO hardware architectures: uniform linear array (ULA)-based XL-MIMO, uniform planar array (UPA)-based XL-MIMO utilizing either patch antennas or point antennas, and continuous aperture (CAP)-based XL-MIMO. We comprehensively analyze and discuss their characteristics and interrelationships. Following this, we examine exact and approximate near-field channel models for XL-MIMO. Given the distinct electromagnetic properties of near-field communications, we present a range of channel models to demonstrate the benefits of XL-MIMO. We further motivate and discuss low-complexity signal processing schemes to promote the practical implementation of XL-MIMO. Furthermore, we explore the interplay between XL-MIMO and other emergent 6G technologies. Finally, we outline several compelling research directions for future XL-MIMO wireless communication systems.Comment: 38 pages, 10 figure

Downlink Training in Cell-Free Massive MIMO: A Blessing in Disguise

Cell-free Massive MIMO (multiple-input multiple-output) refers to a distributed Massive MIMO system where all the access points (APs) cooperate to coherently serve all the user equipments (UEs), suppress inter-cell interference and mitigate the multiuser interference. Recent works demonstrated that, unlike co-located Massive MIMO, the \textit{channel hardening} is, in general, less pronounced in cell-free Massive MIMO, thus there is much to benefit from estimating the downlink channel. In this study, we investigate the gain introduced by the downlink beamforming training, extending the previously proposed analysis to non-orthogonal uplink and downlink pilots. Assuming single-antenna APs, conjugate beamforming and independent Rayleigh fading channel, we derive a closed-form expression for the per-user achievable downlink rate that addresses channel estimation errors and pilot contamination both at the AP and UE side. The performance evaluation includes max-min fairness power control, greedy pilot assignment methods, and a comparison between achievable rates obtained from different capacity-bounding techniques. Numerical results show that downlink beamforming training, although increases pilot overhead and introduces additional pilot contamination, improves significantly the achievable downlink rate. Even for large number of APs, it is not fully efficient for the UE relying on the statistical channel state information for data decoding.Comment: Published in IEEE Transactions on Wireless Communications on August 14, 2019. {\copyright} 2019 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other use

Physical Layer Security in Integrated Sensing and Communication Systems

The development of integrated sensing and communication (ISAC) systems has been spurred by the growing congestion of the wireless spectrum. The ISAC system detects targets and communicates with downlink cellular users simultaneously. Uniquely for such scenarios, radar targets are regarded as potential eavesdroppers which might surveil the information sent from the base station (BS) to communication users (CUs) via the radar probing signal. To address this issue, we propose security solutions for ISAC systems to prevent confidential information from being intercepted by radar targets. In this thesis, we firstly present a beamformer design algorithm assisted by artificial noise (AN), which aims to minimize the signal-to-noise ratio (SNR) at the target while ensuring the quality of service (QoS) of legitimate receivers. Furthermore, to reduce the power consumed by AN, we apply the directional modulation (DM) approach to exploit constructive interference (CI). In this case, the optimization problem is designed to maximize the SINR of the target reflected echoes with CI constraints for each CU, while constraining the received symbols at the target in the destructive region. Apart from the separate functionalities of radar and communication systems above, we investigate sensing-aided physical layer security (PLS), where the ISAC BS first emits an omnidirectional waveform to search for and estimate target directions. Then, we formulate a weighted optimization problem to simultaneously maximize the secrecy rate and minimize the Cram\'er-Rao bound (CRB) with the aid of the AN, designing a beampattern with a wide main beam covering all possible angles of targets. The main beam width of the next iteration depends on the optimal CRB. In this way, the sensing and security functionalities provide mutual benefits, resulting in the improvement of mutual performances with every iteration of the optimization, until convergence. Overall, numerical results show the effectiveness of the ISAC security designs through the deployment of AN-aided secrecy rate maximization and CI techniques. The sensing-assisted PLS scheme offers a new approach for obtaining channel information of eavesdroppers, which is treated as a limitation of conventional PLS studies. This design gains mutual benefits in both single and multi-target scenarios

A Generalized Cluster-Free NOMA Framework Towards Next-Generation Multiple Access

A generalized downlink multi-antenna non-orthogonal multiple access (NOMA) transmission framework is proposed with the novel concept of cluster-free successive interference cancellation (SIC). In contrast to conventional NOMA approaches, where SIC is successively carried out within the same cluster, the key idea is that the SIC can be flexibly implemented between any arbitrary users to achieve efficient interference elimination. Based on the proposed framework, a sum rate maximization problem is formulated for jointly optimizing the transmit beamforming and the SIC operations between users, subject to the SIC decoding conditions and users' minimal data rate requirements. To tackle this highly-coupled mixed-integer nonlinear programming problem, an alternating direction method of multipliers-successive convex approximation (ADMM-SCA) algorithm is developed. The original problem is first reformulated into a tractable biconvex augmented Lagrangian (AL) problem by handling the non-convex terms via SCA. Then, this AL problem is decomposed into two subproblems that are iteratively solved by the ADMM to obtain the stationary solution. Moreover, to reduce the computational complexity and alleviate the parameter initialization sensitivity of ADMM-SCA, a Matching-SCA algorithm is proposed. The intractable binary SIC operations are solved through an extended many-to-many matching, which is jointly combined with an SCA process to optimize the transmit beamforming. The proposed Matching-SCA can converge to an enhanced exchange-stable matching that guarantees the local optimality. Numerical results demonstrate that: i) the proposed Matching-SCA algorithm achieves comparable performance and a faster convergence compared to ADMM-SCA; ii) the proposed generalized framework realizes scenario-adaptive communications and outperforms traditional multi-antenna NOMA approaches in various communication regimes.Comment: 30 pages, 9 figures, submitted to IEEE TW