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This paper introduces a novel compact ultralightweight multiband RF energy harvester fabricated on a paper substrate. The proposed rectenna is designed to operate in all recently released LTE bands (range 0.79–0.96 GHz; 1.71–2.17 GHz; and 2.5–2.69 GHz). High compactness and ease of integration between antenna and rectifier are achieved by using a topology of nested annular slots. The proposed rectifier features an RF-to-dc conversion efficiency in the range of 5%–16% for an available input power of −20 dBm in all bands of interest, which increases up to 11%–30% at −15 dBm. The rectenna has been finally tested both in laboratory and in realistic scenarios featuring a superior performance to other state-of-the-art RF harvesters on flexible substrates. [ABSTRACT FROM PUBLISHER]

This paper demonstrates the design of an 800-MHz solar-powered active wireless beacon composed of an antenna and an integrated oscillator on a low-cost paper substrate. Inkjet printing is used to fabricate the conductive circuit traces and the folded slot antenna, while the oscillator circuit is designed using off-the-shelf components mounted on the paper substrate. Flexible, low-cost, amorphous silicon (a-Si) solar cells are placed on top of the slot ground and provide autonomous operation of the active circuit eliminating the use of a battery. A prototype is built and characterized in terms of phase noise, radiation patterns, and the effect of solar irradiance. Such low-cost flexible circuits can find significant applications as beacon generator circuits for real-time identification and position purposes, wearable biomonitoring as well as solar-to-wireless power transfer topologies. The measured phase noise is -\116 dBc/\Hz at 1-MHz offset, while drain current is 4 mA and supply voltage is 1.8 V. [ABSTRACT FROM AUTHOR]

In this paper, we consider a cooperative simultaneous wireless information and power transfer (SWIPT) network with one source–destination pair and multiple energy harvesting relays. How to efficiently use these relays has been addressed in conventional cooperative networks, and this paper investigates the impact of SWIPT on the performance of such multirelay cooperative networks. In particular, the main contribution of this paper is that a closed-form expression of the outage probability achieved by the multirelay cooperative protocol is obtained, as well as its approximation at high SNR. In addition, the performance of the cooperative network with the SWIPT relays is compared with that in conventional systems with self-powered relays. [ABSTRACT FROM PUBLISHER]

This paper investigates intelligent reflecting surface based backscatter communication (IRS-BackCom), in order to realize computational task offloading of energy-constrained mobile edge computing network in a self-sustainable manner. Specifically, the system operation is divided into two phases. In the first one, the ambient signal energy from a power beacon (PB) either provides the energy supply of local computing and energy harvesting circuits, or flows into the energy storage, when reaching the IRS. In the second one, the stored energy is used to enable IRS-BackCom for partial computational data offloading and energize local computing circuit. Based on this, the maximization problem of sum computational bits is formulated. By jointly optimizing the beamforming vector at the PB, the backscatter matrix at the IRS, the time scheduling of two-phase process, as well as the time of local computing, sum computational bits are maximized. In addition, this paper proposes element clustering to realize BackCom, so as to reduce the control and computation complexity of IRS. According to different operating mechanisms, two cluster operation modes are considered, namely independent cluster operation mode and joint cluster operation mode. Simulation results demonstrate the achievable sum computational bits by the proposed IRS-BackCom schemes. [ABSTRACT FROM AUTHOR]

In this paper, we study the average throughput performance of energy beamforming in a multi-antenna wireless-powered communication network (WPCN). The considered network consists of one hybrid access point (AP) with multiple antennas and a single-antenna user. The user has no constant power supply and, thus, needs to harvest energy from the signals broadcast by the AP in the downlink (DL) before sending its data back to the AP with the harvested energy in the uplink (UL). We derive closed-form expressions of the average throughput and their asymptotic expressions at a high SNR for both delay-limited and delay-tolerant transmission modes. The optimal DL energy harvesting time, which maximizes the system throughput, is then obtained for high SNR. All analytical expressions are validated by numerical simulations. The impact of various parameters, such as the AP transmit power, the energy harvesting time, and the number of antennas, on the system throughput is also investigated. [ABSTRACT FROM AUTHOR]

This paper treats the problem of optimal resource allocation over time in a finite-horizon setting, in which the resource become available only sequentially and in incremental values, and the utility function is concave and can freely vary over time. Such resource allocation problems have direct applications in data communication networks (e.g., energy harvesting systems). This problem is studied extensively for special choices of the concave utility function (time invariant and logarithmic) in which case the optimal resource allocation policies are well-understood. This paper treats this problem in its general form and analytically characterizes the structure of the optimal resource allocation policy and devises an algorithm for computing the exact solutions analytically. An observation instrumental to devising the provided algorithm is that there exist time instances at which the available resources are exhausted, with no carryover to future. This algorithm identifies all such instances, which in turn, facilitates breaking the original problem into multiple problems with significantly reduced dimensions. Furthermore, some widely used special cases in which the algorithm takes simpler structures are characterized, and the application to the energy harvesting systems is discussed. Numerical evaluations are provided to assess the key properties of the optimal resource allocation structure and to compare the performance with the generic convex optimization algorithms. [ABSTRACT FROM AUTHOR]

The diagnostic machinery monitoring system presented in this paper coordinates the acquisition of vibration and speed estimates for an electric machine. It functions even when the machine is “off” or spinning down. This effectively turns the machine into its own mechanical network analyzer. Data from this system can be used to correlate electrical and mechanical data in order to distinguish a variety of pathologies in the machine and its mechanical mounts. The entire sensor system powers itself from surrounding magnetic fields, requiring no ohmic contact or special power wiring. The system presented in this paper presents a unique approach for fusing data from multiple sensors to create a coordinated picture of machine operation on a self-powered platform. [ABSTRACT FROM AUTHOR]

The ongoing growth of Internet of Things (IoT) traffic increasesthe emergence of Multi-Access Edge Computing (MEC), which can serve IoT devices to process edge missions properly. The power supply for IoT devices is addressed by energy harvesting (EH) technology. However, the energy arrival model obeys the unknown energy arrival process. In addition, due to the dynamical changes of network state, it is crucial to study the access control in the MEC-based green IoT system. In this paper, we propose an MEC-based access control strategy to maximize the system utility for the green IoT system, considering the spectral efficiency and the successful access ratio from the perspective of operators and users respectively. Specifically, we model the access control problem as a Constrained Markov Decision Process (CMDP), and develop a novel centralized reward-based experience replay deep convolutional Q network algorithm (RCQN) to attain the optimal access control for EH IoT devices. Additionally, to enrich the prior knowledge of access control strategy, we design a Long Short-Term Memory (LSTM) based energy prediction module to predict the energy state of IoT devices by learning the historical energy arrival information, whose output is taken as the state information of RCQN. Simulation results demonstrate that the proposed LSTM-based RCQN access control algorithm significantly improves the system utility with a proper reward design and training mechanism. [ABSTRACT FROM AUTHOR]

This paper provides radio frequency (RF) energy harvesting and coverage probability analysis using stochastic geometry in a two-hop communication network. In the first hop, terrestrial base stations (TBSs) transmit RF energy and data to the aerial base stations (ABSs) and in the second hop, ABSs forward the data to the user. Numerical results show that the energy harvesting and coverage probabilities can be maximized at almost the same altitude of the ABSs with respect to the TBSs height for low TBSs densities. However, as the density of the backhaul nodes and the energy harvesting sub-timeslot increases, energy harvesting probability improves while coverage probability monotonically decreases by increasing the ABSs height. [ABSTRACT FROM AUTHOR]

While the vehicular network enables geographically distributed cooperative computation, its mature implementation has long been constrained due to the lack of an effective management platform. In this paper, employing the security and privacy attributes of blockchain, we propose a novel Blockchain-enabled Large-scale Parked Vehicular Computing (BLPVC) architecture to utilize the potential solar energy and vehicular computational resources in the outdoor parking lot. However, the uneven green power supply and random arrival time of electric vehicles compose the highly complex environment. Accordingly, in this paper, to handle the efficient utilization of the distributed resources by blockchain technology, we propose an integrated optimization framework which leverages the green energy utilization and service latency limit among the processes of block generation, task computing, and communication, whereas such a design leads to the mixed-timescale stochastic optimization problem. To this end, corresponding to the dynamic solar energy arrival, we propose a shaped deep deterministic policy gradient (DDPG) algorithm to accelerate the learning rate of computational frequency control in the short-term stage; while in the long-term stage, for the mixed-integer programming (MIP) of task offloading and blockchain parameters adjustment, a series of transformation is employed to preserve convexity. Finally, experiments are carried out on Python demonstrating that the proposed scheme achieves a balanced performance between service latency and distributed resources, while the battery depreciation cost is heavily reduced. [ABSTRACT FROM AUTHOR]

This paper applies machine learning to optimize the transmission policies of cognitive radio inspired non-orthogonal multiple access (CR-NOMA) networks, where time-division multiple access (TDMA) is used to serve multiple primary users and an energy-constrained secondary user is admitted to the primary users’ time slots via NOMA. During each time slot, the secondary user performs the two tasks: data transmission and energy harvesting based on the signals received from the primary users. The goal of the paper is to maximize the secondary user’s long-term throughput, by optimizing its transmit power and the time-sharing coefficient for its two tasks. The long-term throughput maximization problem is challenging due to the need for making decisions that yield long-term gains but might result in short-term losses. For example, when in a given time slot, a primary user with large channel gains transmits, intuition suggests that the secondary user should not carry out data transmission due to the strong interference from the primary user but perform energy harvesting only, which results in zero data rate for this time slot but yields potential long-term benefits. In this paper, a deep reinforcement learning (DRL) approach is applied to emulate this intuition, where the deep deterministic policy gradient (DDPG) algorithm is employed together with convex optimization. Our simulation results demonstrate that the proposed DRL assisted NOMA transmission scheme can yield significant performance gains over two benchmark schemes. [ABSTRACT FROM AUTHOR]

This paper deals with measurement methodologies for establishing indicators and metrics in order to assess the performance of vibration energy scavengers. The measurement method proposed here is based on the analysis of the flow of energy through several sections of the harvester, which sometime can include complex architectures and nonlinear phenomena. It is worth noting that the proposed solution is applicable not only to linear transducers in presence of periodic vibration source, as mainly proposed in the literature, but also to nonlinear harvester with its conditioning architectures/circuits and in presence of both stochastic and periodic sources. In this context, all the features have been studied from a generalized point of view which can be applied to study a wide range of Lead Zirconate Titanate-based architectures also exploring the effect of parameters variation, transducer architecture, and its consequence in terms of output performance as function of the kinetic input energy parameters. In particular, we outline a new metric addressing the limits of current solutions which the focus on a specific prototype composed of a single transduction element. This paper develops, from theory, a metric for analyzing the implementation of a performance measurement strategy and, in order to experimentally validate this methodology, considers four case studies, which represent the most popular architectures of scavengers proposed in the literature. The metric is first introduced, than the principle of the transducers under analysis is presented, analytical models have been developed, then, numerical analyses have been performed and the obtained behaviors have been validated from an experimental point of view, including characterization and performance evaluation; a comparison as respect the current figure of merits, applied in a specific device, has also been accomplished highlighting the suitability of the proposed methodology. [ABSTRACT FROM AUTHOR]

Typical vibrational harvesters using a high-permeability beam in a cantilever configuration exploit the field generated by a couple of counter-polarized permanent magnets facing the vibrating strip at the free end. Such a canonical position of the magnets does not permit one, however, to highlight the importance of the bias field pattern. A proof of concept archetype is realized in this paper, by which the influence of the magnetization profile along the length of the vibrating ferromagnetic beam is put in evidence. It demonstrates, in particular, that significant variations, even by a factor of three, of the output power can be obtained by a modification of the magnets arrangement. We discussed in this paper the behavior of a cantilever-based generator, where an Fe–Co high-permeability beam is made to vibrate inside an inhomogeneous magnetic field generated by permanent magnets, whose arrangement can modified in order to vary the magnetization profile along the vibrating laminae. The effects of such a profile are measured and analyzed by means of a simple 2-D numerical model, showing that the generated power can be enhanced by conveniently acting on the magnets configuration. The measurements show that, with a host acceleration of $5g$ rms ( g = 9.81$ m/ \text{s}^{2} ), a 6.72 mW time average output power is obtained for operating frequencies around 60 Hz. [ABSTRACT FROM AUTHOR]

In this paper, we present a simple analytic method that can be used to predict potential energy depletion in off-grid wireless backbone network nodes serving mobile users. The instantaneous energy depletion of the batteries of the network nodes is determined by random energy arrivals and departures and modeled as a G/G/1 queue. To evaluate the online energy depletion probability (EDP), an integral-free asymptotic approach is typically used by assuming that the prediction horizon approaches infinity. However, in many practical cases, the time required by user connections can be rather short. This indicates the need for proactive resource management decisions over finite horizons so that the transmission opportunities with limited energy and time horizons are not wasted. Using Hölder's inequality, we obtain a novel finite-horizon upper bound for the EDP, and the result is compared with the infinite-horizon method. The accuracy of the proposed bound, which is addressed both analytically and numerically, proves to be better for shorter prediction horizons. The finite- and infinite-horizon methods are then applied for an energy provisioning admission control (EP-AC) framework using off-grid backbone network nodes. The key observation of this paper is that the proposed finite-horizon prediction approach admits significantly more users to the network when the connection times are relatively short, while retaining an integral-free closed-form structure suitable for the online evaluation of the EDP. [ABSTRACT FROM AUTHOR]

This paper studies a multiple-input–single-output (MISO) broadcast channel (BC) featuring simultaneous wireless information and power transfer, where a multiantenna access point (AP) delivers both information and energy via radio signals to multiple single-antenna receivers simultaneously, and each receiver implements either information decoding (ID) or energy harvesting (EH). In particular, pseudorandom sequences that are a priori known and therefore can be cancelled at each ID receiver are used as the energy signals, and the information-theoretically optimal dirty paper coding is employed for the information transmission. We characterize the capacity region for ID receivers by solving a sequence of weighted sum-rate (WSR) maximization (WSRMax) problems subject to a maximum sum-power constraint for the AP, and a set of minimum harvested power constraints for individual EH receivers. The problem corresponds to a new form of WSRMax problem in MISO-BC with combined maximum and minimum linear transmit covariance constraints (MaxLTCCs and MinLTCCs), which differs from the celebrated capacity region characterization problem for MISO-BC under a set of MaxLTCCs only and is challenging to solve. By extending the general BC–multiple-access-channel duality, which is only applicable to WSRMax problems with MaxLTCCs, and applying the ellipsoid method, we propose an efficient iterative algorithm to solve this problem globally optimally. Furthermore, we also propose two suboptimal algorithms with lower complexity by assuming that the information and energy signals are designed separately. Finally, numerical results are provided to validate our proposed algorithms. [ABSTRACT FROM PUBLISHER]

This paper deals with the medium between two reconfigurable sensor nodes characterized by radio interfaces that support multiple channels for exchanging real-time messages under energy constraints. These constraints are violated if the consumed energy in transmission is higher than the remaining quantity of energy. A reconfiguration, i.e., any addition or removal of tasks in devices and consequently of messages on the medium, can cause the violation of real-time or energy constraints at run time. To achieve a feasible scheduling in time (i.e., message deadlines will be respected) and energy (i.e., there is available energy) on the medium, we propose new dynamic solutions: Balance, Dilute, and a Combination of them to manage any addition or removal of messages. The proposed approach utilizes the energy harvesting techniques and the PowerControl algorithm to reduce the nonharvested consumed energy. The proposed strategies achieve significant improvement over existing methods and provide the highest percentage of adding messages, with a lower average in response time and energy consumption. They reach a percentage of success in adding the highest priority messages while meeting deadlines up to 85%. [ABSTRACT FROM AUTHOR]

In this paper, we investigate a two-hop simultaneous wireless information and power transfer (SWIPT) amplify-and-forward (AF) multiple-input multiple-output (MIMO) relay communication system with an energy-limited relay node. The relay node harvests energy based on the radio-frequency (RF) signal transmitted from the source node through the time-switching (TS) protocol and fully uses the harvested energy to precode and forward the information to the destination node. The non-linear energy harvesting models are considered at the relay node. With the consideration of the channel estimation error, the joint optimization of the TS factor, source and relay precoding matrices is proposed with robustness against the channel state information (CSI) mismatch to maximize the mutual information (MI) between the source and destination nodes. The optimal structure for the source and relay precoding matrices is derived to simplify the transceiver optimization problem. Numerical simulations show that the system performance provided by the proposed algorithms with robustness is better than the non-robust algorithm. [ABSTRACT FROM AUTHOR]

Computation offloading is an effective method in mobile edge computing (MEC) to relieve user equipment (UE) from the limited computation resource and battery capacity. Meanwhile, simultaneous wireless information and power transmission (SWIPT) can be applied to MEC to extend the operating time of the equipment. However, in multi-user network environment, diverse computation task requirements and changeable network channel states make it challenging to obtain offloading strategy timely and accurately. To address the issue, we propose an intelligent computation offloading scheme (iCOS) based on enhanced priority deep deterministic policy gradient (EPDDPG) algorithm to minimize the energy consumption of all the UEs by jointly optimizing the offloading decision, the central processing unit (CPU) frequency and the power split ratio in a dynamic SWIPT-MEC network. In particular, we improve the traditional fully-connected network structure to obtain both discrete and continuous action outputs, and accelerate neural network parameter updates by using prioritized experience tuples. Furthermore, we use dynamic voltage and frequency scaling (DVFS) technology to dynamically adjust the CPU frequency of local computing, and employ SWIPT technology to balance the charging and communication according to the obtained strategy. Simulation results show that the algorithm proposed in this paper can effectively reduce the energy cost of UEs, and complete more computation tasks within the delay limit. [ABSTRACT FROM AUTHOR]

This paper considers a real-time status update system in which an energy harvesting (EH)-powered transmitter node observes some physical process, and sends its sensed measurements in the form of status updates to a destination node. The status update and harvested energy packets are assumed to arrive at the transmitter according to independent Poisson processes, and the service time of each status update is assumed to be exponentially distributed. We quantify the freshness of status updates when they reach the destination using the concept of Age of Information (AoI). Unlike most of the existing analyses of AoI focusing on the evaluation of its average value when the transmitter is not subject to energy constraints, our analysis is focused on understanding the distributional properties of AoI through the characterization of its moment generating function (MGF). In particular, we use the stochastic hybrid systems (SHS) framework to derive closed-form expressions of the MGF of AoI under several queueing disciplines at the transmitter, including non-preemptive and preemptive in service/waiting strategies. Using these MGF results, we further obtain closed-form expressions for the first and second moments of AoI in each queueing discipline. We demonstrate the generality of this analysis by recovering several existing results for the corresponding system with no energy constraints as special cases of the new results. Our numerical results verify the analytical findings, and demonstrate the necessity of incorporating the higher moments of AoI in the implementation/optimization of real-time status update systems rather than just relying on its average value. [ABSTRACT FROM AUTHOR]

Energy harvesting has attracted increased attention recently. Energy sources are present all around us, such as, mechanical vibrations, stress, strain, waste heat, sunlight or room light, electromagnetic rays, and chemical or biological sources. Vibration generators based on piezoelectric elements have been highlighted as low-power sources; however, their output power is very low, around the milliwatt or microwatt level, and thus, improving their performance is necessary to make the generated power usable. This paper investigates the use of passive devices to improve output characteristics of the vibration generators. The proposed circuits are a resonator and a passive rectifier. The proposed resonator consists of a parallel inductor and capacitor for $LC$ resonance. The $LC$ resonance equivalently reduces the internal capacitor of the piezoelectric elements. As a result, the output voltage and power are increased compared with that of conventional circuits. In addition, a boost-type current-improving passive rectifier is applied as the passive rectifier. The validity of the proposed circuit is numerically and experimentally verified. [ABSTRACT FROM AUTHOR]

Numerous medical operations employ blood transfusions, requiring X-ray irradiated blood for safety concerns. Current irradiation techniques can be significantly improved by replacing standard visual indicators with wireless dosimeter tags that automate the process, reducing inefficiencies, and eliminating blood wastage. A key requirement of the proposed dosimeter tag is flexible and efficient antennas that can be mounted on blood bags. This paper presents the design of a low-cost inkjet-printed dipole antenna on flexible Kapton substrate for a 2.45 GHz radio frequency identification (RFID) dosimeter tag. The tag is to be used in a lossy blood environment, which can severely affect antenna radiation performance. To mitigate this, the concept of artificial magnetic conductor (AMC) unit cells is investigated for best impedance and gain performance. When integrated with a dipole radiator, the fabricated AMC-backed antenna maintains broadside radiation with gains of 4.1–4.8 dBi under planar and bending conditions, and on a lossy blood bag. In a rectenna configuration, the antenna can power sensors for ranges up to 1 m. Measured output dc voltages up to 1.7 V are achieved across a 25 $\text{k}\Omega $ resistor. This antenna design is flexible, compact, efficient on lossy structures, and suitable for direct integration with biomedical sensing chips. [ABSTRACT FROM AUTHOR]

Nowadays, wireless communication has become a fabric of our daily life, and it has been a universal demand for higher capacity and longer battery lifetime. For the sake of solving these problems, this paper considers taking the advantage of cooperative communication with the assistance of green relays. So, in this paper, we design an auction market that is composed of one base station (acts as the auctioneer), multiple green relays (act as sellers), and multiple mobile terminals (act as buyers). The terminals need to pay for the cooperative service, and the relays sell it for revenue. In addition, the terminals can raise their bid according to their residual energy; thus the terminals that lack energy have more opportunities to get cooperative service to avoid energy exhaustion. At the same time, the relays can reduce the price based on their instantaneous energy harvesting amount, and, hence, the relays can serve more terminals when they can harvest more energy from the environment. This paper also proposes three different auction rules to show the effect of relay selection. Furthermore, power allocation among relays and terminals is adopted to minimize the power consumption of terminals under the SNR requirement. Simulation results show that the three relay selection rules perform diversely and have their own advantages and disadvantages, but all of them can improve system capacity and prolong the lifetime of the mobile terminals effectively. And, with power allocation, the terminal can utilize the least energy to achieve its SNR requirement. [ABSTRACT FROM AUTHOR]

Energy harvesting, particularly through ambient sources, is gaining significant interest in the recent past because of the energy crisis and the pollution associated with fossil fuels. With the emergence of Internet-of-Things (IoT), where billions of IoT devices are expected to communicate with each other, energy harvesting has become even more relevant. In this vision, we have been working on energy harvesting based on magnetic materials, particularly stress-induced domain wall motion. In this paper, we present a detailed overview of our research on stress-induced domain wall motion and the demonstration of energy harvesting. We have carried out micromagnetic simulations, which indicated that an applied stress can change the magnetization direction from transverse direction to the longitudinal direction in a microwire. The experimental results on CoNi/FeCo/CoNi microwires confirmed that such change in domain structure is possible with applied stress. We have shown the details on how a transverse anisotropy is achieved in CoNi/FeCo/CoNi stack. We have also demonstrated that energy can be harvested using the methods described in this paper. The results offer a new magnetic stack, which can be used to achieve energy harvesting through ambient sources. [ABSTRACT FROM AUTHOR]

Radio-frequency (RF) energy harvesting is one of the promising technologies in wireless networks. This paper considers wireless powered communication networks (WPCNs) where one hybrid access point (H-AP) coordinates RF energy/information transmissions to/from a set of nodes. For the important type of WPCNs where the nodes have throughput requirement, we aim to minimize H-AP's energy provision (EP) via jointly optimizing the time allocation of energy/information transmissions and H-AP's transmission power while satisfying node throughput requirement. More specifically, the half-duplex WPCN is considered first. We prove that H-AP's energy transmission power must be the maximum allowed value to achieve the minimal EP, then show that the problem is convex under this condition and finally design an algorithm applying golden section search and bisection search jointly to efficiently obtain the optimal time allocation. Second, the full-duplex WPCN is considered. Its EP minimization problem is proved convex. However, due to the hardness of solving it directly, we turn to solve the feasibility problem (FP) for a given EP per unit time. We construct a convex optimization problem based on this FP and design a dual subgradient algorithm for finding its optimal solution, which indicates whether this FP is feasible. The minimal EP per unit time and its corresponding optimal solution are found by using the bisection search method. Simulation results show that, the EP-minimized schemes are able to greatly reduce H-AP's EP as compared to the baseline schemes. [ABSTRACT FROM AUTHOR]

This paper studies simultaneous wireless information and power transfer (SWIPT) techniques for point-to-point multiple-input multiple-output channels, where a multi-antenna transmitter conveys information and energy at the same time to a multi-antenna receiver equipped with time switching (TS) circuits for an energy harvesting (EH) mode and an information decoding (ID) mode. Unlike conventional uniform TS (UTS) structure where all the receive antennas at the receiver employ a single TS circuit, in this paper, we propose a general dynamic TS (DTS) receiver architecture which has an individual TS circuit for each antenna. In the proposed DTS, the operation modes of the antennas can be dynamically changed to improve SWIPT performance. We aim to identify the achievable rate–energy (R–E) tradeoff of the DTS protocol for both linear and non-linear EH models by maximizing the information rate subject to the EH constraint. This results in joint optimization of the transmit covariance matrices and the time durations for the EH and the ID modes of the receive antennas, which is jointly non-convex in general. To tackle the non-convexity of the original problem, the successive convex approximation technique is adopted by addressing a series of approximated convex problems. As a result, efficient optimization algorithms are proposed for determining the boundary points of the achievable R–E region. We also provide a low-complexity algorithm which achieves near-optimal performance with much reduced complexity. Numerical results demonstrate that the proposed DTS presents significant performance gains over conventional UTS approaches. [ABSTRACT FROM AUTHOR]

This paper proposes a broadcast strategy for the single-user slowly fading channel in which the transmission power is supplied by an energy harvesting unit. In this strategy, the channel state information (CSI) is known only to the receiver, and the transmitter is assumed to be oblivious to the CSI. The broadcast approach enables preventing outage events in the face of the lack of CSI at the transmitter. In the proposed broadcast approach, the transmitter splits its message into multiple superimposed information layers. This facilitates sustaining reliably decodable transmission rates adapted to the unknown state of the randomly-varying fading state of the channel. The objective is to characterize the optimal allocation of the randomly varying harvested power over time and across information layers in the contexts of maximizing the average communication rate and minimizing the likelihood of outage. First, the setting in which the transmitter has non-causal and complete information about the state of the energy harvesting process is considered. A closed-form characterization of the optimal allocation of power across layers is established, and an algorithm that analytically determines the exact optimal allocation of power over time is provided. Furthermore, an online algorithm is proposed for a setting in which the energy harvesting process is known only causally to the transmitter. [ABSTRACT FROM AUTHOR]

A MEMS, silicon-based device with a piezoelectric layer and an integrated magnet is presented for magnetic to electrical transduction. The cantilever structure can be configured either as an energy harvester to harvest power from an AC power line or as an AC current sensor. The positioning of the transducer with respect to the conductor is critical in both scenarios. For the energy scavenger, correct positioning is required to optimize the harvested power. For the current sensor, it is necessary to optimize the sensitivity of the sensor. This paper considers the effect of the relative position of the transducer with respect to the wire on the resulting electromagnetic forces and torques driving the device. It is shown in this paper that it is the net equivalent torque at the anchor that must be considered and not just the vertical component of the magnetic force as has been widely assumed heretofore. We show that for single wire conductors, the commonly made assumption that there exists two symmetrical power peaks at 45° either side of the wire is untrue, but rather that the net driving torque on one side of the wire can be more than an order of magnitude greater than the other. [2018-0173] [ABSTRACT FROM AUTHOR]

This paper presents a novel rectifier array for a wide dynamic range of RF-dc conversion. The rectifier array consists of multiple rectifier cells optimized for operation at different power levels and uses an adaptive power distribution method to divide the RF input power among these rectifier cells according to the RF power levels. The adaptive power distribution takes advantage of the power-dependent input impedances of the rectifier cells and is implemented with passive devices. This method both improves the rectification efficiency and minimizes the impedance mismatch as the input power level varies, and therefore, significantly enhances the dynamic range. The rectifier array can be designed using either the same type or different types of rectifying devices and can be expanded by including more cells in the network to further increase the dynamic range. In this paper, three different implementations of such rectifier array circuits are described, including a two-diode rectifier array designed with the same type of diodes, a two-diode rectifier array designed with different types of diodes, and a three-diode rectifier array with different types of diodes. The performances of these circuits are validated with measurement and compared with each other. Significant enhancement of dynamic range over conventional rectifiers is demonstrated. [ABSTRACT FROM AUTHOR]

This paper reports the fabrication of MEMS-based guided two-beam piezoelectric energy harvester for low-frequency operation. A highly c-axis-oriented zinc oxide thin film of 2.5- $\mu \text{m}$ thickness covered with 0.5- $\mu \text{m}$ plasma-enhanced chemical vapor deposition SiO2 is sandwiched between the aluminum electrodes to form split electrodes on the two beams. A pyramidal-shaped seismic mass that gives a higher electric potential is realized by bulk micromachining using CMOS compatible 25 wt% tetramethyl ammonium hydroxide wet etching. The thickness of the beams is optimized using deep reactive-ion etching to achieve a low-frequency operation. COMSOL Multiphysics has been used to study the stress distribution to optimize the dimension and placement of the split electrodes. The optimized split electrodes give a reduced resonance frequency by 4.2% when compared with previously used electrode pattern ensuring maximum electric potential generation for guided two-beam structure. The resonance frequency of the device measured experimentally using laser Doppler vibrometer comes to be 466 Hz. The packaged device exhibits a maximum sensitivity of 1.5089 mV/m/s2 in the frequency range from 160 to 1000 Hz. [ABSTRACT FROM AUTHOR]

Multiple-input multiple-output (MIMO) technology equips the transmitters with the multiple antennas. It can combine with energy harvesting (EH) to lift the spectrum efficiency and make use of a greener energy resource. A power grid is added to serve as a supplementary source to regulate the not-so-stable harvested energy supply of the system. Besides the MIMO technology being used, the power allocated to the user provided by both EH and the power grid is subject to the epoch power upper bound constraints. The background of these constraints comes from field requirements, such as avoiding the saturation of power allocated to the user(s), avoiding system-level out-of-band power leakage, and reducing interference with other transmitter(s) due to the non-linearity generated via the transmitting mechanisms to the user(s). The epoch power upper bound constraints make this problem more challenging, with the controllable power grid energy budget and its allocation. This paper applies our recently proposed geometric water-filling with group upper bounded power constraints and recursion machinery to form the proposed algorithm for solving the proposed throughput maximization problem. Our algorithm is precisely defined, and further provides the exact solution via the lower degree polynomial complexity. This point is very suitable for the massive MIMO system. To the best of our knowledge, no prior algorithm has been reported in the open literature to solve the targeted problem in this paper. [ABSTRACT FROM PUBLISHER]

This paper presents a nonlinear resonator circuit based on the Duffing equation to enhance the bandwidth of wireless power harvesting and wireless power transfer systems. The Duffing resonator circuit can be implemented with passive components. In this paper, analysis of an electrical Duffing resonator is presented. The detailed discussion of the Duffing resonator’s properties is provided. As a proof of principle, a wireless power harvester employing such a nonlinear resonator has been designed and tested. It is shown that the Duffing resonator circuit enhances the bandwidth of the harvester by 2.7 times compared with a harvester using a linear resonator with the same quality factor, while achieving a similar amplitude level near the resonance frequency. Furthermore, the bandwidth of the nonlinear resonator is independent of its quality factor ( $Q$ ). [ABSTRACT FROM PUBLISHER]

In this paper, we investigate the simultaneous wireless information and power transfer in a multiple-input multiple-output decode-and-forward relay system, where the relay is an energy harvesting (EH) multi-antenna node equipped with an EH receiver and an information decoding (ID) receiver. The relay harvests the energy from the radio frequency signals sent by the source and uses it to forward the signals to the destination. The main objective in this paper is to maximize the achievable transmission rate of the overall link by optimizing the source/relay precoders. First, we study an upper bound on the maximum achievable rate where we assume that the EH and ID receivers operate simultaneously and have access to the whole power of the received signals. Afterward, we study two practical schemes, which are the power splitting and time switching schemes, where the ID and EH receivers have partial access to the power or duration of the received signals. For each scheme, we have studied the complexity and the performance comparison. In addition, we considered the case of the imperfect channel estimation error and we have observed its impact on the achievable end-to-end rate and the harvested energy at the relay. [ABSTRACT FROM PUBLISHER]

Disguised tailing and visual monitoring of suspicious mobile targets is a promising application of security unmanned aerial vehicles (UAVs). But trajectory planning is non-trivial, especially for fixed-wing UAVs with more constrained maneuverability and dynamic models. This paper proposes a new framework to optimize collectively the propulsion power and the three-dimensional (3D) trajectory of a solar-powered, fixed-wing UAV on a disguised tailing and video surveillance mission. The multi-objective optimization strikes a balance between distance keeping, elevation variance, and power efficiency. A key aspect is that we develop a new propulsion power model of the fixed-wing UAV by analyzing the forces undergone while the UAV is ascending or descending. Another important aspect is a series of non-trivial reformulations, which convexify the multi-objective problem progressively with increasingly tightening linear approximation and solve the problem with a polynomial time-complexity. Our algorithm can control the trajectory of the UAV on-the-fly. Simulations confirm that the algorithm outperforms existing schemes in terms of visual disguise and power efficiency. The fixed-wing UAV also demonstrates its advantage of energy efficiency and sustainability to elongate the surveillance mission, over its rotary-wing counterpart. [ABSTRACT FROM AUTHOR]

With the development of 6G wireless communication technologies, various resource-intensive and delay-sensitive vehicle application tasks are generated. These application tasks can be offloaded to Mobile Edge Computing (MEC) which deploys computing resources at the edge of networks. Besides, the recent proposed Cybertwin, as the digital representation of the complicated physical end-systems, can help the terminals obtain the required services from networks. Vehicles enabled by Cybertwin can offload their tasks to MEC and achieve better performance. In this paper, we focus on the study of a hybrid energy-powered multi-server MEC system with Cybertwin. Vehicles enabled by Cybertwin and edge servers send the current network status and unprocessed vehicle application tasks to the macro base station (MBS) to achieve the better allocation of resources. Energy harvesting (EH) devices are deployed on edge servers to form a “green energy-grid” hybrid energy supply model. We formulate a stochastic offloading optimization problem, and the goal is to minimize the system cost. The stochastic optimization problem is decomposed into three sub-problems. Then, we design an efficient multi-vehicle task offloading (EMT) algorithm to achieve the trade-off between system cost and task queue length. Theoretical analysis shows that EMT algorithm can optimize the total cost of the MEC system and guarantee the system performance. According to experimental evaluation, we verify the performance of the EMT algorithm. [ABSTRACT FROM AUTHOR]

This paper studies an intelligent reflecting surface (IRS)-assisted wireless-powered communication network (WPCN), where a hybrid access point (HAP) broadcasts energy signals to multiple devices for their energy harvesting in the downlink (DL) and then the devices use the harvested energy to transmit information signals to the HAP in the uplink (UL) with the help of an IRS. In particular, we propose three types of IRS beamforming configurations, namely fully dynamic IRS beamforming (FDBF), partially dynamic IRS beamforming (PDBF), and static IRS beamforming (SBF), to strike a balance between the system performance and signaling overhead as well as implementation complexity. Moreover, we adopt a practical non-linear energy harvesting (EH) model, and leverage a power-splitting (PS) EH receiver architecture with multiple rectifiers to avoid the input radio frequency power to get stuck into the saturation regime. We aim to minimize the transmit energy consumption at the HAP by jointly optimizing the DL/UL time allocation, the HAP/devices transmit power, the PS factor, and IRS phase shifts, subject to a set of minimum throughput requirements for individual devices. To address the resulting non-convex optimization problems, a successive convex approximation (SCA) based alternating optimization algorithm is proposed. Moreover, we study the case with the ideal linear EH model and two algorithms, namely SCA-based algorithm and semidefinite relaxation (SDR) algorithm, are proposed. Simulation results demonstrate the effectiveness of our proposed designs over various benchmark schemes and also unveil the importance of the joint design of IRS beamforming and PS rectifiers for achieving energy efficient WPCNs in practice. [ABSTRACT FROM AUTHOR]

The combination of energy harvesting (EH), cognitive radio (CR), and non-orthogonal multiple access (NOMA) is a promising solution to improve energy efficiency and spectral efficiency of the upcoming beyond fifth generation network (B5G), especially for support the wireless sensor communications in Internet of things (IoT) system. However, how to realize intelligent frequency, time, and energy resource allocation to support better performances is an important problem to be solved. In this paper, we study joint spectrum, energy, and time resource management for the EH-CR-NOMA IoT systems. Our goal is to minimize the number of data packets losses for all secondary sensing users (SSU), while satisfying the constraints on the maximum charging battery capacity, maximum transmitting power, maximum buffer capacity, and minimum data rate of primary users (PU) and SSUs. Due to the non-convexity of this optimization problem and the stochastic nature of the wireless environment, we propose a distributed multidimensional resource management algorithm based on deep reinforcement learning (DRL). Considering the continuity of the resources to be managed, the deep deterministic policy gradient (DDPG) algorithm is adopted, based on which each agent (SSU) can manage its own multidimensional resources without collaboration. In addition, a simplified but practical action adjuster (AA) is introduced for improving the training efficiency and battery performance protection. The provided results show that the convergence speed of the proposed algorithm is about 4 times faster than that of DDPG, and the average number of packet losses (ANPL) is about 8 times lower than that of the greedy algorithm. [ABSTRACT FROM AUTHOR]

In this paper, a novel intelligent reflecting surface (IRS)-assisted wireless powered communication network (WPCN) architecture is proposed for power-constrained Internet-of-Things (IoT) smart devices, where IRS is exploited to improve the performance of WPCN under imperfect channel state information (CSI). We formulate a hybrid access point (HAP) transmit energy minimization problem by jointly optimizing time allocation, HAP energy beamforming, receiving beamforming, user transmit power allocation, IRS energy reflection coefficient and information reflection coefficient under the imperfect CSI and non-linear energy harvesting model. On account of the high coupling of optimization variables, the formulated problem is a non-convex optimization problem that is difficult to solve directly. To address the above-mentioned challenging problem, alternating optimization (AO) technique is applied to decouple the optimization variables to solve the problem. Specifically, through AO, time allocation, HAP energy beamforming, receiving beamforming, user transmit power allocation, IRS energy reflection coefficient and information reflection coefficient are divided into three sub-problems to be solved alternately. The difference-of-convex (DC) programming is used to solve the non-convex rank-one constraint in solving IRS energy reflection coefficient and information reflection coefficient. Numerical simulations verify the superiority of the proposed optimization algorithm in decreasing HAP transmit energy compared with other benchmark schemes. [ABSTRACT FROM AUTHOR]

In this paper, we consider a cognitive radio (CR) network that consists of multiple secondary users (SUs), each of which is equipped with an energy harvesting capability. We consider the opportunistic use of the idle spectrum, unused by primary users (PUs), through a mechanism of two-step opportunistic spectrum access for the SUs, consisting of random channel sensing followed by random channel access. Unlike the majority of previous studies, which have considered CR networks with energy harvesting under a single user setting, the goal of this paper is to investigate the joint impact of sensing probability, access probability, and energy queue capacity on the maximum achievable throughput in a multiuser CR network incorporating energy harvesting. For two extreme cases, those where the energy queue capacity is either infinite or extremely small, we show that the maximum achievable throughput is not affected by the channel access probability if the channel sensing probability is chosen appropriately and the optimal sensing probability is derived as a function of network parameters such as the energy arrival rate, channel availability probability, and number of contending SUs. [ABSTRACT FROM AUTHOR]

In this paper, state-of-the-art power electronics and energy management solutions utilized in low-power (less than 5 mW), low-voltage (less than 3 V) energy harvesting powered wireless sensors for Internet of things related applications are detailed. All aspects of an energy harvesting powered sensor system are examined, including the challenges of low-power energy harvesting sources, energy management circuits including power converters and energy storage elements, as well as the impact of wireless sensor pulsed power profiles. In particular, this paper focuses on existing voltage step-up energy management techniques, including the issues of cold-start and maximum power point tracking, as well as energy storage which is necessary for wireless sensor operation. Both academic and commercially available energy harvesting powered systems are examined to provide a comprehensive analysis of existing solutions. Issues that are limiting the current system performance are identified to help define future developments needed to enable efficient and effective energy harvesting powered wireless sensor operation. [ABSTRACT FROM AUTHOR]

In this paper, we propose an approach to the design of a magnetostrictive electric power generator for energy harvesting from traffic, and we validate it experimentally. We use the dynamic Preisach hysteresis model (DPM) for magnetostrictive materials, operating in hysteretic and time-varying nonlinear regimes to design and simulate a magnetostrictive electrical power generator. The DPM is a development of the classical Preisach model, which is able to include the dynamical features in the mathematical model of hysteresis. We measure the output power capability of the generator, and we show how it is comparable to other energy-harvesting technologies. [ABSTRACT FROM AUTHOR]

This paper addresses a wearable piezoelectric energy harvester that combines a PVDF piezoelectric charge generator with an a-Si:H dual-gate thin-film transistor as a rectifier. An analytical model and equivalent circuit elaborate their working principle and device physics. A preliminary experimental study proves the device concept and demonstrates that such a harvester is capable of generating microwatt-range power with a simple 90° finger bending action. Coupled with low-cost and largearea fabrication processes, a pixelated energy-harvesting array can be potentially achievable, making it a promising alternative to energy sources for wearable electronics. [ABSTRACT FROM AUTHOR]

Fifth generation wireless standards require much lower latency than what current wireless systems can guarantee. The main challenge in fulfilling these requirements is the development of short packet transmission, in contrast to most of the current standards, which use a long data packet structure. Since the available training resources are limited by the packet size, reliable channel and interference covariance estimation with reduced training overhead are crucial to any system using short data packets. In this paper, we propose an efficient receiver that exploits useful information available in the data transmission period to enhance the reliability of the short packet transmission. In the proposed method, the receive filter (i.e., the sample covariance matrix) is estimated using the received samples from the data transmission without using an interference training period. A channel estimation algorithm to use the most reliable data symbols as virtual pilots is employed to improve quality of the channel estimate. Simulation results verify that the proposed receiver algorithms enhance the reception quality of the short packet transmission. [ABSTRACT FROM PUBLISHER]