Optimal Multiuser Scheduling Schemes for Simultaneous Wireless Information and Power Transfer

In this paper, we study the downlink multiuser scheduling problem for systems with simultaneous wireless information and power transfer (SWIPT). We design optimal scheduling algorithms that maximize the long-term average system throughput under different fairness requirements, such as proportional fairness and equal throughput fairness. In particular, the algorithm designs are formulated as non-convex optimization problems which take into account the minimum required average sum harvested energy in the system. The problems are solved by using convex optimization techniques and the proposed optimization framework reveals the tradeoff between the long-term average system throughput and the sum harvested energy in multiuser systems with fairness constraints. Simulation results demonstrate that substantial performance gains can be achieved by the proposed optimization framework compared to existing suboptimal scheduling algorithms from the literature.Comment: Accepted for presentation at the European Signal Processing Conference 201

Energy-Efficient Resource Allocation in Multiuser OFDM Systems with Wireless Information and Power Transfer

In this paper, we study the resource allocation algorithm design for multiuser orthogonal frequency division multiplexing (OFDM) downlink systems with simultaneous wireless information and power transfer. The algorithm design is formulated as a non-convex optimization problem for maximizing the energy efficiency of data transmission (bit/Joule delivered to the users). In particular, the problem formulation takes into account the minimum required system data rate, heterogeneous minimum required power transfers to the users, and the circuit power consumption. Subsequently, by exploiting the method of time-sharing and the properties of nonlinear fractional programming, the considered non-convex optimization problem is solved using an efficient iterative resource allocation algorithm. For each iteration, the optimal power allocation and user selection solution are derived based on Lagrange dual decomposition. Simulation results illustrate that the proposed iterative resource allocation algorithm achieves the maximum energy efficiency of the system and reveal how energy efficiency, system capacity, and wireless power transfer benefit from the presence of multiple users in the system.Comment: 6 pages. The paper has been accepted for publication at the IEEE Wireless Communications and Networking Conference (WCNC) 2013, Shanghai, China, Apr. 201

Wireless Power Charging Control in Multiuser Broadband Networks

Recent advances in wireless power transfer (WPT) technology provide a cost-effective solution to charge wireless devices remotely without disruption to the use. In this paper, we propose an efficient wireless charging control method for exploiting the frequency diversity in multiuser broadband wireless networks, to reduce energy outage and keep the system operating in an efficient and sustainable state. In particular, we first analyze the impact of charging control method to the operating lifetime of a WPT-enabled broadband system. Based on the analysis, we then propose a multi-criteria charging control policy that optimizes the transmit power allocation over frequency by jointly considering the channel state information (CSI) and the battery state information (BSI) of wireless devices. For practical implementation, the proposed scheme is realized by a novel limited CSI estimation mechanism embedded with partial BSI, which significantly reduces the energy cost of CSI and BSI feedback. Simulation results show that the proposed method could significantly increase the network lifetime under stringent transmit power constraint. Reciprocally, it also consumes lower transmit power to achieve near-perpetual network operation than other single-criterion based charging control methods.Comment: This paper had been accepted by IEEE ICC 2015, Workshop on Green Communications and Networks with Energy Harvesting, Smart Grids, and Renewable Energie

Resource Allocation for Secure Communication in Systems with Wireless Information and Power Transfer

This paper considers secure communication in a multiuser multiple-input single-output (MISO) downlink system with simultaneous wireless information and power transfer. We study the design of resource allocation algorithms minimizing the total transmit power for the case when the receivers are able to harvest energy from the radio frequency. In particular, the algorithm design is formulated as a non-convex optimization problem which takes into account artificial noise generation to combat potential eavesdroppers, a minimum required signal-to-interference-plus-noise ratio (SINR) at the desired receiver, maximum tolerable SINRs at the potential eavesdroppers, and a minimum required power delivered to the receivers. We adopt a semidefinite programming (SDP) relaxation approach to obtain an upper bound solution for the considered problem. The tightness of the upper bound is revealed by examining a sufficient condition for the global optimal solution. Inspired by the sufficient condition, we propose two suboptimal resource allocation schemes enhancing secure communication and facilitating efficient energy harvesting. Simulation results demonstrate a close-to-optimal performance achieved by the proposed suboptimal schemes and significant transmit power savings by optimization of the artificial noise generation.Comment: 7 pages, 5 figures, and 1 table. Submitted for possible conference publicatio

Power Allocation and Scheduling for SWIPT Systems with Non-linear Energy Harvesting Model

In this paper, we design a resource allocation algorithm for multiuser simultaneous wireless information and power transfer systems for a realistic non-linear energy harvesting (EH) model. In particular, the algorithm design is formulated as a non-convex optimization problem for the maximization of the long-term average total harvested power at EH receivers subject to quality of service requirements for information decoding receivers. To obtain a tractable solution, we transform the corresponding non-convex sum-of-ratios objective function into an equivalent objective function in parametric subtractive form. This leads to a computationally efficient iterative resource allocation algorithm. Numerical results reveal a significant performance gain that can be achieved if the resource allocation algorithm design is based on the non-linear EH model instead of the traditional linear model.Comment: Accepted for presentation at the IEEE ICC 201