Cluster-based wireless energy transfer for low complex energy receivers

Wireless energy transfer (WET) is potentially a promising solution to provide convenient and reliable energy supplies for energy-constrained networks, and has drawn growing interests recently. To overcome the significant propagation loss over distance, employing multi-antennas at the energy transmitter (ET) to more efficiently direct wireless energy to desired energy receivers (ERs), termed energy beamforming, is an essential technique for WET. However, the achievable gain of energy beamforming crucially depends on the available channel state information (CSI) at the ET, which needs to be acquired practically. In this paper, we study the optimal design of one efficient channel-acquisition method for a point-to-point multiple-input multiple-output (MIMO) WET system, by exploiting the channel reciprocity based on which the ET estimates the CSI via dedicated reverse-link training from the ER. Considering the limited energy availability at the ER, the training strategy should be carefully designed so that the channel can be estimated with sufficient accuracy, and yet without consuming excessive energy at the ER. To this end, we propose to maximize the net energy at the ER, which is the total energy harvested offset by that used for channel training. The optimal training design, including the number of receive antennas to be trained, as well as the training time and power allocated, is derived. Our result shows that training helps only when the following conditions are satisfied: (i) the channel coherence time is sufficiently large; (ii) the number of antennas at the ET is large enough; and (iii) the effective signal-to-noise ratio (ESNR) is sufficiently high; otherwise, no training should be applied and isotropic energy transmission is optimal.

Energy beamforming (EB) is a key technique for achieving efficient radio-frequency (RF) transmission enabled wireless energy transfer (WET). By optimally designing the waveforms from multiple energy transmitters (ETs) over the wireless channels, they are constructively combined at the energy receiver (ER) to achieve an EB gain that scales with the number of ETs. However, the optimal design of transmit waveforms requires accurate channel state information (CSI) at the ETs, which is challenging to obtain in practical WET systems. In this paper, we propose a new channel training scheme to achieve optimal EB gain in a distributed WET system, where multiple separated ETs adjust their transmit phases to collaboratively send power to a single ER in an iterative manner, based on one-bit feedback from the ER per training interval which indicates the increase/decrease of the received power level from one particular ET over two preassigned transmit phases. The proposed EB algorithm can be efficiently implemented in practical WET systems even with a large number of distributed ETs, and is analytically shown to converge quickly to the optimal EB design as the number of feedback intervals per ET increases. Numerical results are provided to evaluate the performance of the proposed algorithm as compared to other distributed EB designs.

This letter considers spectrum sharing between a multiuser multiple-input multiple-output (MIMO) wireless energy transfer (WET) system and a coexisting point-to-point MIMO wireless information transmission (WIT) system, where WET generates interference to WIT and degrades its throughput performance. We show that due to the interference, the WIT system suffers from a loss of the degrees of freedom (DoF) proportional to the number of energy beams sent by the energy transmitter (ET), which, in general, needs to be larger than one to optimize the multiuser WET with user fairness consideration. To minimize the DoF loss in WIT, we further propose a new single-beam energy transmission scheme based on the principle of time sharing, where the ET transmits one of the optimal energy beams at each time. This new scheme achieves the same optimal performance for the WET system, and minimizes the impact of its interference to the WIT system.

PurposeThis paper aims to develop mathematical models of variously compensated wireless energy transfer (WET) systems. Attention is primarily paid to the derivation of the most important energy transfer characteristics such as efficiency and amount of transferred power. This paper discusses the main advantages and disadvantages of various compensation techniques to show their possible application areas. On the basis of these results, a designer will be able to quickly identify which compensation type suites as the best solution to fulfill a given system’s requirements.Design/methodology/approachFirst, the current state in the field of mathematical modeling of WET systems is introduced. Next, the non-resonant magnetic-coupled circuit together with four most common resonant magnetic-coupled circuits is analyzed. The equivalent circuit models using loop currents methodology is applied to the analyses. The proposed methodology is experimentally verified by the laboratory measurement of selected circuit topology. The main contribution of the proposed methodology lies in its quick applicability on more complicated or extended systems while keeping a relatively good match with the real system’s behavior.FindingsThe authors have presented the usage of a simple and accurate methodology for investigating variously compensated WET systems. Electrical engineers who require effective and powerful tools for the identification of basic WET systems properties will find this methodology to be of extensive help.Research limitations/implicationsThe analyses consider only the sinusoidal type of supply voltage; so, it is valid mainly for the close range of the resonant state. Nonlinearities cannot be taken into account.Practical implicationsThis research may be applied in the field of WET systems.Originality/valueResearch in the area of power electronic systems, which provides a clear and straightforward procedure for WET system identification, will be helpful to most practical technicians who are not well versed in areas of physical-based phenomena.

The performance of two wireless power transfer scheduling schemes, time sharing (TS) and spatial multiplexing (SM), in terms of provisioning fairness among energy receivers (ERs) is studied and compared while taking into account the nonlinearity of the energy harvesters circuits. In the network, the multiple-antenna energy transmitter (ET) attempts to maximize the harvested energy by the ER which has accumulated the minimum amount of energy among all single-antenna ERs during the wireless power transfer block T-hence the max-min fairness criterion. Two network scenarios are studied: homogeneous, where the channels power coefficients are assumed to be the same for all the well-apart ERs, and heterogeneous, where the said coefficients can take arbitrary values. It is proven analytically that in the homogeneous scenario, the optimal scheduling policy is to allocate each ER the full transmit power P with uniform distribution of charging times among ERs, rather than to allocate the full power transfer block T with uniform distribution of the power among ERs. Generalization of the network to the heterogeneous scenario aims to find the optimal beamforming vector for the SM scheme and the optimal time sharing vector for the TS scheme. It is shown through extensive Monte Carlo simulations that again TS outperforms SM in terms of max-min fairness as a result of taking into account the inherent non-linear characteristics of the harvesting devices.

The current trend puts emphasis on the efficiency of the all electronics devices. For this reason, it is necessary to maximize the efficiency of the wireless energy transfer system as well as on other electronic devices. Therefore, this article deals with the most suitable working point analysis of the serial–serial WET system. The core of the article contains the simulation analysis at the various loads and various coupling coefficients. Experimental measurements were made on the existing prototype and the results were compared with the results from the simulation analysis. The main outcome of this paper is thus detailed investigation of operational point of WET system in order to meet the highest possible system efficiency together with the highest possible level of transferred power.

This letter investigates secure hybrid beamforming (HB) design for an extremely large-scale antenna array-aided simultaneous wireless information and power transfer (SWIPT) system operating in a mixed near-field (NF)/far-field (FF) environment. A base station (BS) employs HB to transmit information and artificial noise (AN) signals simultaneously to multiple FF information receivers (IRs) and NF energy receivers (ERs). The objective is to maximize the weighted sum secrecy rate for the IRs, considering both Type-I (unable to cancel AN) and Type-II (capable of canceling AN) IRs, subject to minimum energy harvesting requirements at the ERs and a BS transmit power constraint. We formulate optimization problems for both IR types and develop an efficient iterative algorithm based on successive convex approximation. Simulation results validate the proposed scheme and provide crucial insights into the security performance of mixed-field SWIPT systems, highlighting the influence of visibility regions and angular user separation.

This paper investigates the multi-cell coordinated beamforming (MCBF) design for secure simultaneous wireless information and power transfer (SWIPT) in both centralized and distributed manners. In each cell, one transmitter serves multiple information receivers (IRs) and energy receivers (ERs) with the non-linear energy harvesting (EH) model. Meanwhile, several eavesdroppers (Eves) intend to intercept the confidential information transmitted for IRs. To achieve a secure transmission, the artificial noise (AN) is embedded in the transmit signals of each transmitter. The proposed design is formulated into a power-minimization problem to guarantee the IRs’ information and ERs’ energy requirements while avoiding the information being intercepted by Eves. Since the problem is non-convex and not easy to solve, a solution method based on semi-definition relaxation (SDR) is proposed and the global optimum is proved to be guaranteed with full channel state information (CSI). We further present a distributed AN-aided MCBF for the system by using alternating direction method of multipliers (ADMM), with which each transmitter is able to calculate its own beamforming vectors and AN covariance matrix based on its local CSI. Simulation results show that our proposed distributed design converges to the global optimum obtained by the centralized one. It is also shown that by employing AN, the total required power of the system is reduced and the effect of AN on the system performance decreases with increment of transmit antennas. Compared with traditional linear EH model, optimizing the system under the non-linear EH one avoids false output power at the ERs and saves power at the transmitter.

This chapter provides an overview of the main energy harvesting (EH) technologies and their relevant role in present and future internet of things (IoT) deployments. EH technologies for wireless machine-type devices can be mainly classified into the following two categories: ambient EH, and dedicated EH. The chapter emphasizes on RF–EH, and highlights its advantages compared to competing EH technologies reduced form-factor implementation and native multi-user support. RF–wireless energy transfer (WET) systems consist of three key components: RF transmitters, medium, and EH node. It focuses on the non-decreasing EH transfer function with the incident RF waveform power as sole input. The chapter describes the general architecture of an RF–EH IoT network, and the main layouts for wireless information transfer (WIT) and WET along with potential applications. WET, as a pivotal component of RF–EH networks, is fundamental for realizing the Internet of Energy paradigm.

This chapter examines simultaneous wireless information and power transfer (SWIPT) scenarios. It discusses the main SWIPT receivers, namely, separate and co-located receivers. The chapter provides numerical examples on the performance of the designed SWIPT precoding strategy. It focuses on a co-located SWIPT system, where a HAP serves a set S of devices performing both energy harvesting and information decoding in a given frequency band. The chapter illustrates some numerical results on the performance of the time switching and power splitting protocols. It also discusses some specific promising approaches to boost the performance of SWIPT systems for general wireless energy transfer (WET)-powered internet of things networks. WET and SWIPT systems are subject to non-linear responses that are often model-intractable unless too strong assumptions are adopted. The chapter concludes with an overview of some potential techniques to enable efficient SWIPT in future networks.

Wireless power transfer networks (WPTNs) are composed of dedicated energy transmitters (ETs) that charge energy receivers (ERs) via radio frequency waves. A safe-charging WPTN should keep electromagnetic radiation below predetermined limits meanwhile maximizing the transmitted power. In this paper, we consider this requirement as an optimization problem: the maximization of harvested power by ERs subject to the electro-magnetic safety constraints. In order to provide an approximated solution to this problem, we introduce a dual ascent-like distributed charging algorithm that enables ETs to work without global information and satisfy safety constraints asymptotically. We provide an in-depth theoretical analysis of our algorithm which is supported by numerical simulations.

The effect of various parameters on the resonance-based wireless energy transfer system has been investigated to obtain the design steps for efficient wireless energy transfer. Both theoretically and experimentally, it has been observed that every system has its own strongly coupled region that is an optimum frequency band for which maximum energy transfer occurs. The frequency band of the strongly coupled region changes with the coil size, structure, physical spacing, relative location, and material properties of the wire. Based on the theoretical results, experiments have been carried out to demonstrate the effectiveness and characteristics of the resonant wireless energy transfer method. It is found that the energy transfer efficiency reaches maximum at resonant frequency. The energy transfer efficiency is further enhanced by changing the configuration of coil and through low-resistance wire with high-quality factor. The analyses will give future guidelines for designing a compact efficient wireless energy transfer system to energize macro as well as micro devices used for various applications.

This article addresses the security problem for wireless powered cognitive satellite-terrestrial network, where a multibeam satellite sub-network shares the portion of millimeter wave bands with multiple cellular networks, each consisting of a base station, several mobile users (MUs) and energy receivers (ERs). Considering that the ERs are potential eavesdroppers of the MUs, and only imperfect knowledge of the angles of departure for the wiretap channels is available, we aim at maximizing aggregated rate of the considered network while guaranteeing the signal-to-interference-plus-noise ratio requirements of the MUs, the energy harvesting thresholds and the secrecy constraints at ERs. Since the formulated optimization problem is mathematically intractable, we exploit a discretization method and the Taylor expansion method to transform the non-convex objective and constraints into convex ones, and then propose an iterative beamforming (BF) algorithm to solve the problem. Furthermore, we present a combined multibeam scheme to obtain suboptimal BF weight vectors with low computational burden. Finally, simulation results reveal that the proposed BF schemes can efficiently improve the aggregated rate with fast convergence compared to the benchmark schemes.

This letter considers wireless-powered cooperative jamming to secure communication between a transmitter (Tx) and an information receiver, in the presence of an energy receiver (ER), which is termed a potential eavesdropper. The full-duplex jammer harvests energy from the Tx's information signal and transmits jamming signal at the same time, where the jamming signal not only confounds the ER (potential eavesdropper) but also charges the ER. Our goal is to maximize the secrecy information rate by jointly optimizing the power allocation at the Tx and jammer, while maintaining the harvested energy requirement of the ER. The studied problem is non-convex and we propose the optimal solution based on the Lagrange method. Simulation results show that the proposed scheme significantly outperforms the benchmark schemes.

Accomplishing equilibrium in terms of transfer efficiency for dual-band wireless energy transfer (WET) system remains as one of key concerns particularly in the implementation of a single transmitter device which supports simultaneous energy and data transfer functionality. Three stages of design method are discussed in addressing the aforementioned concern. A single layer dual-band printed spiral resonator for non-radiative wireless energy transfer operating at 6.78 MHz and 13.56 MHz is presented. By employing multi-coil approach, measured power transfer efficiency for a symmetrical link separated at axial distance of 30 mm are 72.34% and 74.02% at the respective frequency bands. When operating distance is varied between 30 mm to 38 mm, consistency of simulated peak transfer efficiency above 50% is achievable.