Secure Beamforming For MIMO Broadcasting With Wireless Information And Power Transfer

This paper considers a basic MIMO information-energy (I-E) broadcast system, where a multi-antenna transmitter transmits information and energy simultaneously to a multi-antenna information receiver and a dual-functional multi-antenna energy receiver which is also capable of decoding information. Due to the open nature of wireless medium and the dual purpose of information and energy transmission, secure information transmission while ensuring efficient energy harvesting is a critical issue for such a broadcast system. Assuming that physical layer security techniques are applied to the system to ensure secure transmission from the transmitter to the information receiver, we study beamforming design to maximize the achievable secrecy rate subject to a total power constraint and an energy harvesting constraint. First, based on semidefinite relaxation, we propose global optimal solutions to the secrecy rate maximization (SRM) problem in the single-stream case and a specific full-stream case where the difference of Gram matrices of the channel matrices is positive semidefinite. Then, we propose a simple iterative algorithm named inexact block coordinate descent (IBCD) algorithm to tackle the SRM problem of general case with arbitrary number of streams. We proves that the IBCD algorithm can monotonically converge to a Karush-Kuhn-Tucker (KKT) solution to the SRM problem. Furthermore, we extend the IBCD algorithm to the joint beamforming and artificial noise design problem. Finally, simulations are performed to validate the performance of the proposed beamforming algorithms.Comment: Submitted to journal for possible publication. First submission to arXiv Mar. 14 201

Symbol-level and Multicast Precoding for Multiuser Multiantenna Downlink: A State-of-the-art, Classification and Challenges

Precoding has been conventionally considered as an effective means of mitigating or exploiting the interference in the multiantenna downlink channel, where multiple users are simultaneously served with independent information over the same channel resources. The early works in this area were focused on transmitting an individual information stream to each user by constructing weighted linear combinations of symbol blocks (codewords). However, more recent works have moved beyond this traditional view by: i) transmitting distinct data streams to groups of users and ii) applying precoding on a symbol-per-symbol basis. In this context, the current survey presents a unified view and classification of precoding techniques with respect to two main axes: i) the switching rate of the precoding weights, leading to the classes of block-level and symbol-level precoding, ii) the number of users that each stream is addressed to, hence unicast, multicast, and broadcast precoding. Furthermore, the classified techniques are compared through representative numerical results to demonstrate their relative performance and uncover fundamental insights. Finally, a list of open theoretical problems and practical challenges are presented to inspire further research in this area

Probabilistically Robust SWIPT for Secrecy MISOME Systems

This paper considers simultaneous wireless information and power transfer (SWIPT) in a multiple-input single-output (MISO) downlink system consisting of one multi-antenna transmitter, one single-antenna information receiver (IR), multiple multi-antenna eavesdroppers (Eves) and multiple single-antenna energy-harvesting receivers (ERs). The main objective is to keep the probability of the legitimate user's achievable secrecy rate outage as well as the ERs' harvested energy outage caused by channel state information (CSI) uncertainties below some prescribed thresholds. As is well known, the secrecy rate outage constraints present a significant analytical and computational challenge. Incorporating the energy harvesting (EH) outage constraints only intensifies that challenge. In this paper, we address this challenging issue using convex restriction approaches which are then proved to yield rank-one optimal beamforming solutions. Numerical results reveal the effectiveness of the proposed schemes.Comment: This is an open access article accepted for publication as a regular paper in the IEEE Transactions on Information Forensics & Security. Copyright (c) 2016 IEEE. Personal use of this material is permitted. However, permission to use this material for any other purposes must be obtained from the IEEE by sending a request to [email protected]

Optimization of secure wireless communications for IoT networks in the presence of eavesdroppers

The problem motivates this paper is that securing the critical data of 5G based wireless IoT network is of significant importance. Wireless 5G IoT systems consist of a large number of devices (low-cost legitimate users), which are of low complexity and under strict energy constraints. Physical layer security (PLS) schemes, along with energy harvesting, have emerged as a potential candidate that provides an effective solution to address this issue. During the data collection process of IoT, PHY security techniques can exploit the characteristics of the wireless channel to ensure secure communication. This paper focuses on optimizing the secrecy rate for simultaneous wireless information and power transfer (SWIPT) IoT system, considering that the malicious eavesdroppers can intercept the data. In particular, the main aim is to optimize the secrecy rate of the system under signal to interference noise ratio (SINR), energy harvesting (EH), and total transmits power constraints. We model our design as an optimization problem that advocates the use of additional noise to ensure secure communication and guarantees efficient wireless energy transfer. The primary problem is non-convex due to complex objective functions in terms of transmit beamforming matrix and power splitting ratios. We have considered both the perfect channel state information (CSI) and the imperfect CSI scenarios. To circumvent the non-convexity of the primary problem in perfect CSI case, we proposed a solution based on the concave-convex procedure (CCCP) iterative algorithm, which results in a maximum local solution for the secrecy rate. In the imperfect CSI scenario, we facilitate the use of S-procedure and present a solution based on the iterative successive convex approximation (SCA) approach. Simulation results present the validations of the proposed algorithms. The results provide an insightful view that the proposed iterative method based on the CCCP algorithm achieves higher secrecy rates and lower computational complexity in comparison to the other algorithms

Higher-rank Transmit Beamforming Using Space Time Block Coding

With the rapid development of wireless communications, there has been a massive growth in the number of wireless communications users and progressively more new high data rate wireless services will emerge. With these developments taking place, wireless spectral resources are becoming much more scarce and precious. As a result, research on spectrally efficient transmission techniques for current and future communication networks attracts considerable interest. As a promising multi-antenna communication technique, transmit beamforming is widely recognized as being able to improve the capacity of wireless systems without requiring additional spectral resources. In conventional (rank-one) beamforming, each user is served by a single beamformer. For certain transmit beamforming applications, the beamforming performance may be poor if the degrees of freedom in the conventional beamformer design become insufficient. The scope of this thesis is to address the beamforming performance degradation problems induced by the insufficient degrees of freedom in the beamformer design in certain practical scenarios. In this thesis, a fundamentally new idea of higher-rank (>1) transmit beamforming is proposed to improve the beamforming performance. Instead of a single beamformer assigned to each user, multiple beamformers are designed and correspondingly the degrees of freedom in the beamformer design are multiplied, i.e., the increase of the degrees of freedom consists in the increase of the number of design variables. To implement higher-rank beamforming, the central idea is to combine beamforming with different space time block coding (STBC) techniques. Conventionally, STBCs are used to exploit the transmit diversity resulting from the independent fading for different transmit antennas. However, the use of STBCs in the higher-rank beamforming approaches is not for the sake of transmit diversity, but for the sake of design diversity in the sense of degrees of freedom in the beamformer design. The single-group multicast beamforming problem of broadcasting the same information to all users is firstly considered in the thesis. It is assumed that the transmitter knows the instantaneous channel state information (CSI) which describes the short-term channel conditions of a communication link and can be estimated in modern communication systems. In the conventional approach, a single beamforming weight vector is designed to steer the common information to all users. In the case of a large number of users, the performance of the conventional approach usually degrades severely due to the limited degrees of freedom offered by a single beamformer. In order to mitigate this drawback, a rank-two beamforming approach is proposed in which two independent beamforming weight vectors are designed. In the rank-two beamforming approach, single-group multicast beamforming is combined with the two dimentional Alamouti STBC, and each user is simultaneously served with two Alamouti coded symbols from two beamformers. The degrees of freedom in the beamformer design are doubled and significant performance improvement is achieved. The multi-group multicast beamforming problem of transmitting the same information to users in the same group while transmitting independent information to users in different groups, is studied next in the thesis, also assuming that instantaneous CSI is available at the transmitter. The rank-two beamforming approach, originally devised for single-group multicasting networks that are free of multiuser interference, is extended to multi-group multicasting networks, where multiuser interference represents a major challenge. By combining multi-group multicast beamforming with Alamouti STBC, two independent beamforming weight vectors are assigned to each user and the degrees of freedom in the beamformer design are doubled resulting in drastically improved beamforming performance. Then, the multiuser downlink beamforming problem of delivering independent information to different users with additional shaping constraints is investigated in the thesis, also assuming instantaneous CSI at the transmitter. Additional shaping constraints are used to incorporate a variety of requirements in diverse applications. When the number of shaping constraints is large, the degrees of freedom in the beamformer design can be rather deficient. In order to address this problem, a general rank beamforming approach is proposed in which multiuser downlink beamforming is combined with high dimensional (>2) real-valued orthogonal space time block coding (OSTBC). In the general rank beamforming approach, the number of beamforming weight vectors for each user and the associated degrees of freedom in the beamformer design are multiplied by up to eight times, which lead to significantly increased flexibility for the beamformer design. Since instantaneous CSI can be difficult to acquire in certain scenarios, the use of statistical CSI describing the long-term statistical characteristics of the channel can be more practical in these scenarios. The rank-two beamformer designs based on instantaneous CSI can be straightforwardly applied in the case of statistical CSI. However, it is impossible to extend the general rank beamforming approach for the multiuser downlink beamforming problem with additional shaping constraints based on instantaneous CSI to the case of statistical CSI straightforwardly. Therefore, multiuser downlink beamforming with additional shaping constraints using statistical CSI at the transmitter is then studied and an alternative general rank beamforming approach is proposed in the thesis. In the general rank beamforming approach using statistical CSI, multiuser downlink beamforming is combined with quasi-orthogonal space time block coding (QOSTBC). The increased number of beamforming weight vectors and the associated degrees of freedom are much beyond the limits that can be achieved by Alamouti STBC in the beamformer design. Simulation results demonstrate that the proposed higher-rank transmit beamforming approaches can achieve significantly improved performance as compared to the existing approaches

Regularized Channel Inversion for Simultaneous Confidential Broadcasting and Power Transfer: A Large System Analysis

We propose for the first time new transmission schemes based on linear precoding to enable simultaneous confidential broadcasting and power transfer (SCBPT) in a multiuser multi-input single-output (MISO) network, where a BS with N antennas simultaneously transmits power and confidential messages to K single-antenna users. We first design two transmission schemes based on the rules of regularized channel inversion (RCI) for both power splitting (PS) and time switching (TS) receiver architectures, namely, RCI-PS and RCI-TS schemes. For each scheme, we derive channel-independent expressions to approximate the secrecy sum rate and the harvested power in the large-system regime where K, N → ∞ with a fixed ratio β = K/N. Based on the large-system results, we jointly optimize the regularization parameter of the RCI and the PS ratio or the TS ratio such that the secrecy sum rate is maximized subject to an energy-harvesting constraint. We then present the tradeoff between the secrecy sum rate and the harvested power achieved by each scheme, and find that neither scheme always outperforms the other one. Motivated by this fact, we design an RCI-hybrid scheme based on the RCI and a newly proposed hybrid receiver architecture. The hybrid receiver architecture takes advantages of both the PS and TS receiver architectures. We show that the RCI-hybrid scheme outperforms both the RCI-PS and RCI-TS schemes.ARC Discovery Projects Grant DP15010390

Advanced Symbol-level Precoding Schemes for Interference Exploitation in Multi-antenna Multi-user Wireless Communications

The utilization of multi-antenna transmitters relying on full frequency reuse has proven to be an effective strategy towards fulfilling the constantly increasing throughput requirements of wireless communication systems. As a consequence, in the last two decades precoding has been a prolific research area, due to its ability to handle the interference arising among simultaneous transmissions addressed to different co-channel users. The conventional precoding strategies aim at mitigating the multi-user interference (MUI) by exploiting the knowledge of the channel state information (CSI). More recently, novel approaches have been proposed where the aim is not to eliminate the interference, but rather to control it so as to achieve a constructive interference effect at each receiver. In these schemes, referred to as symbol-level precoding (SLP), the data information (data symbols) is used together with the CSI in the precoding design, which can be addressed following several optimization strategies. In the context of SLP, the work carried out in this thesis is mainly focused on developing more advanced optimization strategies suitable to non-linear systems, where the per-antenna high-power amplifiers introduce an amplitude and phase distortion on the transmitted signals. More specifically, the main objective is to exploit the potential of SLP not only to achieve the constructive interference at the receivers, but also to control the per-antenna instantaneous transmit power, improving the power dynamics of the transmitted waveforms. In fact, a reduction of the power variation of the signals, both in the spatial dimension (across the different antennas) and in the temporal dimension, is particularly important for mitigating the non-linear effects. After a detailed review of the state of the art of SLP, the first part of the thesis is focused on improving the power dynamics of the transmitted signals in the spatial dimension, by reducing the instantaneous power imbalances across the different antennas. First, a SLP per-antenna power minimization scheme is presented, followed by a related max-min fair formulation with per-antenna power constraints. These approaches allow to reduce the power peaks of the signals across the antennas. Next, more advanced SLP schemes are formulated and solved, with the objective of further improving the spatial dynamics of the signals. Specifically, a first approach performs a peak power minimization under a lower bound constraint on the per-antenna transmit power, while a second strategy minimizes the spatial peak-to-average power ratio. The second part of this thesis is devoted to developing a novel SLP method, referred to as spatio-temporal SLP, where the temporal variation of the transmit power is also considered in the SLP optimization. This new model allows to minimize the peak-to-average power ratio of the transmitted waveforms both in the spatial and in the temporal dimensions, thus further improving the robustness of the signals to non-linear effects. Then, this thesis takes one step further, by exploiting the developed spatio-temporal SLP model in a different context. In particular, a spatio-temporal SLP scheme is proposed which enables faster-than-Nyquist (FTN) signaling over multi-user systems, by constructively handling at the transmitter side not only the MUI but also the inter-symbol interference (ISI). This strategy allows to benefit from the increased throughput provided by FTN signaling without imposing additional complexity at the user terminals. Extensive numerical results are presented throughout the thesis, in order to assess the performance of the proposed schemes with respect to the state of the art in SLP. The thesis concludes summarizing the main research findings and identifying the open problems, which will constitute the basis for the future work