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

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

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

Power Efficient and Secure Multiuser Communication Systems with Wireless Information and Power Transfer

In this paper, we study resource allocation algorithm design for power efficient secure communication with simultaneous wireless information and power transfer (WIPT) in multiuser communication systems. In particular, we focus on power splitting receivers which are able to harvest energy and decode information from the received signals. The considered problem is modeled as an optimization problem which takes into account a minimum required signal-to-interference-plus-noise ratio (SINR) at multiple desired receivers, a maximum tolerable data rate at multiple multi-antenna potential eavesdroppers, and a minimum required power delivered to the receivers. The proposed problem formulation facilitates the dual use of artificial noise in providing efficient energy transfer and guaranteeing secure communication. We aim at minimizing the total transmit power by jointly optimizing transmit beamforming vectors, power splitting ratios at the desired receivers, and the covariance of the artificial noise. The resulting non-convex optimization problem is transformed into a semidefinite programming (SDP) and solved by SDP relaxation. We show that the adopted SDP relaxation is tight and achieves the global optimum of the original problem. Simulation results illustrate the significant power saving obtained by the proposed optimal algorithm compared to suboptimal baseline schemes.Comment: Accepted for presentation at the IEEE International Conference on Communications (ICC), Sydney, Australia, 201