Information and energy can be transferred over the same radio-frequency channel. In the power-splitting (PS) mode, they are simultaneously transmitted using the same signal by the base station (BS) and later separated at the user (UE)’s receiver by a power splitter. In the time-switching (TS) mode, they are either transmitted separately in time by the BS or received separately in time by the UE. In this paper, the BS transmit beamformers are jointly designed with either the receive PS ratios or the transmit TS ratios in a multicell network that implements wireless information and power transfer (WIPT). Imposing UE-harvested energy constraints, the design objectives include: 1) maximizing the minimum UE rate under the BS transmit power constraint, and 2) minimizing the maximum BS transmit power under the UE data rate constraint. New iterative algorithms of low computational complexity are proposed to efficiently solve the formulated difficult nonconvex optimization problems, where each iteration either solves one simple convex quadratic program or one simple second-order-cone-program. Simulation results show that these algorithms converge quickly after only a few iterations. Notably, the transmit TS-based WIPT system is not only more easily implemented but outperforms the receive PS-based WIPT system as it better exploits the beamforming design at the transmitter side.

/pdf/beamforming-design-for-wireless-information-and-power-480wcfgppz.pdf

Beamforming Design for Wireless Information and Power Transfer Systems: Receive Power-Splitting Versus Transmit Time-Switching

This paper provides an overview of multi-cell coordinated scheduling and multiple-input multiple-output (MIMO) techniques in LTE. We first discuss single-user MIMO (SU-MIMO) and multi-user MIMO (MU-MIMO) for LTE and identify potential techniques for further improving the performance of LTE, such as enhanced channel state information feedback and adaptive switching between SU-MIMO and MU-MIMO. Then, we address inter-cell interference mitigation techniques for downlink and uplink, respectively. Finally, potential research challenges and topics in the area are discussed.

Multi-Cell Coordinated Scheduling and MIMO in LTE

Energy-efficient communications has attracted much interest in the research of 5G cellular systems. In this paper, we study energy-efficient coordinated beamforming design for heterogeneous multicell multiuser downlink systems. The considered problem is formulated as maximizing the weighted sum per-cell energy efficiencies (WSPEEMax) subject to predefined per-user target rate demands, maximum leakage interference power constraints, and per-BS transmit power constraints. This formulation is more general than the conventional EE optimization problem and provides a unified way to consider the EE of heterogeneous networks. However, it is hard to tackle due to the weighted sum-of-ratios form of the objective function and the non-convex nature of per-user target rate constraints. To address it, we propose to first transform the original problem into a polynomial form optimization by introducing some auxiliary variables and then further reveal their equivalence in finding the solution. Then, an efficient block coordinate ascent optimization algorithm is developed to solve the equivalent problem by exploiting the concave nature of the considered problem with respect to each optimization variable. To further improve the network EE, we also develop an energy-efficient transmission method for each small-cell network. Finally, extensive numerical results are provided to verify the effectiveness of the proposed schemes and show that both the EE and spectral efficiency (SE) of heterogeneous network can be significantly improved by energy-efficient coordinated multiple-input multiple-output (MIMO) transmission.

Leakage-Aware Energy-Efficient Beamforming for Heterogeneous Multicell Multiuser Systems

This paper considers coordinated multicast beamforming in a multicell multigroup multiple-input single-output system. Each base station (BS) serves multiple groups of users by forming a single beam with common information per group. We propose centralized and distributed beamforming algorithms for two different optimization targets. The first objective is to minimize the total transmission power of all the BSs while guaranteeing the user-specific minimum quality-of-service targets. The semidefinite relaxation (SDR) method is used to approximate the nonconvex multicast problem as a semidefinite program (SDP), which is solvable via centralized processing. Subsequently, two alternative distributed methods are proposed. The first approach turns the SDP into a two-level optimization via primal decomposition. At the higher level, intercell interference powers are optimized for fixed beamformers, whereas the lower level locally optimizes the beamformers by minimizing BS-specific transmit powers for the given intercell interference constraints. The second distributed solution is enabled via an alternating direction method of multipliers, where the intercell interference optimization is divided into a local and a global optimization by forcing the equality via consistency constraints. We further propose a centralized and a simple distributed beamforming design for the signal-to-interference-plus-noise ratio (SINR) balancing problem in which the minimum SINR among the users is maximized with given per-BS power constraints. This problem is solved via the bisection method as a series of SDP feasibility problems. The simulation results show the superiority of the proposed coordinated beamforming algorithms over traditional noncoordinated transmission schemes, and illustrate the fast convergence of the distributed methods.

/pdf/distributed-optimization-for-coordinated-beamforming-in-3xgbipvcp7.pdf

Distributed Optimization for Coordinated Beamforming in Multicell Multigroup Multicast Systems: Power Minimization and SINR Balancing

A basic question in wireless networking is how to optimize the wireless network resource allocation for utility maximization and interference management. How can we overcome interference to efficiently optimize fair wireless resource allocation, under various stochastic constraints on quality of service demands? Network designs are traditionally divided into layers. How does fairness permeate through layers? Can physical layer innovation be jointly optimized with network layer routing control? How should large complex wireless networks be analyzed and designed with clearly-defined fairness using beamforming? This monograph provides a comprehensive survey of the models, algorithms, analysis, and methodologies using a Perron-Frobenius theoretic framework to solve wireless utility maximization problems. This approach overcomes the notorious non-convexity barriers in these problems, and the optimal value and solution of the optimization problems can be analytically characterized by the spectral property of matrices induced by nonlinear positive mappings. It also provides a systematic way to derive distributed and fast-convergent algorithms and to evaluate the fairness of resource allocation. This approach can even solve several previously open problems in the wireless networking literature. More generally, this approach links fundamental results in nonnegative matrix theory and linear and nonlinear Perron-Frobenius theory with the solvability of non-convex problems. In particular, for seemingly nonconvex problems, e.g., max-min wireless fairness problems, it can solve them optimally; for truly nonconvex problems, e.g., sum rate maximization, it can even be used to identify polynomial-time solvable special cases or to enable convex relaxation for global optimization.To highlight the key aspects, we also list several case studies of using the nonlinear Perron-Frobenius theoretic framework for applications in MIMO wireless cellular, heterogeneous small-cell and cognitive radio networks. Key implications arising from these work along with severalopen issues are discussed in this monograph.

/pdf/wireless-network-optimization-by-perron-frobenius-theory-187cgnowkg.pdf

Wireless Network Optimization by Perron-Frobenius Theory

In this paper, we address the problem of the coordinated beamforming design for multi-cell multiple input single output (MISO) downlink system subject to per-BS power constraints. The objective is taken as the maximization of the minimum signal-to-interference plus noise ratio (SINR), while a complete analysis of the duality between the multi-cell downlink and the virtual uplink optimization problems is provided. A hierarchical iterative scheme is proposed to solve the virtual uplink optimization problem, whose solution is then converted to derive the one of the multi-cell downlink beamforming problem. The proposed algorithm is proved to converge to a stable point. Additional, the complexity of the proposed algorithm is analyzed. Simulation results show that, in contrast to existing multi-cell beamforming schemes, the proposed algorithm achieves better performance in terms of both rate per energy (RPE) and the worst-user rate.

A Multi-Cell Beamforming Design by Uplink-Downlink Max-Min SINR Duality

Hydrodynamics of the traditional wedges, cylinders, and cones entering water have been heavily studied. However, the hydrodynamic characteristics of airfoils are practically unknown; the problem is inspired by the recently widely developed fixed-wing unmanned aerial-underwater vehicle, which can fly in the air, cruise in water and frequently enters and exits free water surface. In this study, the hydrodynamic characteristics and fully nonlinear free surface deformation for the water entry of airfoils have been investigated by the time domain boundary element method. First, convergence study based on the NACA0012 airfoil is considered. The time step and element size are adjusted, and the results show that the free surface elevation and pressure distribution agree well with those obtained through Reynolds-averaged Navier–Stokes equations. The results show that the higher the entry velocity, the greater the peak hydrodynamic force. Furthermore, the higher thickness ratio causes greater added mass. Gravity and velocity are found to significantly influence the hydrodynamic behavior, including the time-varying force, while thickness ratio has a great impact on added mass and pressure. 

Numerical study on the water entry of two-dimensional airfoils by BEM

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A Multi-Cell Beamforming Design by Uplink-Downlink Max-Min SINR Duality

Numerical study on the water entry of two-dimensional airfoils by BEM