MMSE-based beamforming techniques for relay broadcast channels

We propose minimum mean square error (MMSE)-based beamforming techniques for a multiantenna relay network, where a base station (BS) equipped with multiple antennas communicates with a number of single-antenna users through a multiantenna relay. We specifically solve three optimization problems, namely, 1) the sum-power minimization problem, 2) the mean-square-error (MSE) balancing problem, and 3) the mixed quality-of-service (QoS) problem. Unfortunately, these problems are not jointly convex in terms of beamforming vectors at the BS and the relay amplification matrix. To circumvent this nonconvexity issue, the original problems are divided into two subproblems, where the beamforming vectors and the relay amplification matrix are alternately optimized, whereas the other is fixed. Three iterative algorithms are developed based on convex optimization techniques and general MSE duality. Simulation results are provided to validate the convergence of the proposed algorithms

Privacy-preserving multi-class support vector machine for outsourcing the data classification in cloud

Emerging cloud computing infrastructure replaces traditional outsourcing techniques and provides flexible services to clients at different locations via Internet. This leads to the requirement for data classification to be performed by potentially untrusted servers in the cloud. Within this context, classifier built by the server can be utilized by clients in order to classify their own data samples over the cloud. In this paper, we study a privacy-preserving (PP) data classification technique where the server is unable to learn any knowledge about clients' input data samples while the server side classifier is also kept secret from the clients during the classification process. More specifically, to the best of our knowledge, we propose the first known client-server data classification protocol using support vector machine. The proposed protocol performs PP classification for both two-class and multi-class problems. The protocol exploits properties of Pailler homomorphic encryption and secure two-party computation. At the core of our protocol lies an efficient, novel protocol for securely obtaining the sign of Pailler encrypted numbers

Physical layer security jamming: Theoretical limits and practical designs in wireless networks

Physical layer security has been recently recognized as a promising new design paradigm to provide security in wireless networks. In addition to the existing conventional cryptographic methods, physical layer security exploits the dynamics of fading channels to enhance secured wireless links. In this approach, jamming plays a key role by generating noise signals to confuse the potential eavesdroppers, and significantly improves quality and reliability of secure communications between legitimate terminals. This article presents theoretical limits and practical designs of jamming approaches for physical layer security. In particular, the theoretical limits explore the achievable secrecy rates of user cooperation based jamming whilst the centralized, and game theoretic based precoding techniques are reviewed for practical implementations. In addition, the emerging wireless energy harvesting techniques are exploited to harvest the required energy to transmit jamming signals. Future directions of these approaches, and the associated research challenges are also briefly outlined

Base station beamforming technique using multiple signal-to-interference plus noise ratio balancing criteria

We propose a coordinated multicell beamforming technique for signal to interference plus noise ratio (SINR) balancing under multiple base station (BS) power constraints. Instead of balancing SINR of all users in all cells to the same level, we propose a new approach to balance SINR of users in various cells to different maximum possible values. This has the ability to allow users in cells with relatively more transmit power or better channel condition to achieve a higher balanced SINR than that achieved by users in the worst case cells. This multi-level SINR balancing problem is solved using SINR constraints based SINR balancing criterion and subgradient method. The simulation results support the optimality of the results through comparison to semidefinite programming (SDP) based optimization

Base station beamforming technique using multiple signal-to-interference plus noise ratio balancing criteria

We propose a coordinated multicell beamforming technique for signal to interference plus noise ratio (SINR) balancing under multiple base station (BS) power constraints. Instead of balancing SINR of all users in all cells to the same level, we propose a new approach to balance SINR of users in various cells to different maximum possible values. This has the ability to allow users in cells with relatively more transmit power or better channel condition to achieve a higher balanced SINR than that achieved by users in the worst case cells. This multi-level SINR balancing problem is solved using SINR constraints based SINR balancing criterion and subgradient method. The simulation results support the optimality of the results through comparison to semidefinite programming (SDP) based optimization

A joint beamforming and power-splitter optimization technique for SWIPT in MISO-NOMA system

In this paper, we propose a joint beamforming and power-splitter optimization technique for simultaneous wireless power and information transfer in the downlink transmission of a multiple-input single-output (MISO) non-orthogonal multiple access (NOMA) system. Accordingly, each user employs a power splitter to decompose the received signal into two parts, namely, the information decoding and energy harvesting. The former part is used to decode the corresponding transmitted information, whereas the latter part is utilized for harvesting energy. For this system model, we solve an energy harvesting problem with a set of design constraints at the transmitter and the receiver ends. In particular, the beamforming vector and the power splitting ratio for each user are jointly designed such that the overall harvested power is maximized subject to minimum per-user rate requirements and the available power budget constraints at the base station. As the formulated problem turns out to be non-convex in terms of the design parameters, we propose a sequential convex approximation technique and demonstrate a superior performance compared to a baseline scheme