Energy Harvesting Wireless Communications Research Articles

Maximum Throughput Analysis in Hybrid Energy Harvesting Wireless Communication Systems Based on Martingale Theory

Maximum Throughput Analysis in Hybrid Energy Harvesting Wireless Communication Systems Based on Martingale Theory

Optimum power allocation for an energy harvesting wireless communication system considering energy storage losses

Optimum power allocation for an energy harvesting wireless communication system considering energy storage losses

A Survey on Energy Harvesting Wireless Networks: Channel Capacity, Scheduling, and Transmission Power Optimization

This paper presents a survey on energy harvesting (EH) wireless communication networks focusing on channel capacity, transmission schemes, and power optimization. While many network researchers focus on energy management policies addressing the intermittency and randomness of the EH processes, but the channel capacity, and transmission power optimization have not been fully explored yet. In this paper, we provide a review and analysis of channel capacity, offline and online transmission schemes, and power optimization from an information theory perspective. By reviewing and analyzing wireless networking literature, we found that EH is a technologically feasible and economically viable paradigm for cost-effectiveness in the design and deployment of next-generation wireless networks. Finally, we identify open research problems and future research directions in the emerging field of EH wireless networks. We expect this study to stimulate more research endeavors to build energy-efficient scalable next-generation wireless network systems.

Online Power Control and Optimization for Energy Harvesting Communication System Based on State of Charge

In this paper, the online power control problem for energy harvesting wireless communication system with a finite storage capacity battery is addressed, where the channel state and energy harvesting rate are both unknown. A low complexity algorithm based online convex optimization is proposed to guarantee energy availability of energy harvesting node and maximize average long-term throughput. The proposed algorithm restricts maximum transmission power with the information of state of charge, and allocates transmission power based on historical information. In addition, energy availability constraint is given by rigorous theoretical analysis to guarantee the optimization of average long-term throughput. Simulations have been conducted to demonstrate the effectiveness of the algorithm without considering probability distribution of energy arrival or channel coefficients. The proposed algorithm outperforms counterparts in different energy harvested rates.

Organic photovoltaics for simultaneous energy harvesting and high-speed MIMO optical wireless communications

We show that organic photovoltaics (OPVs) are suitable for high-speed optical wireless data receivers that can also harvest power. In addition, these OPVs are of particular interest for indoor applications, as their bandgap is larger than that of silicon, leading to better matching to the spectrum of artificial light. By selecting a suitable combination of a narrow bandgap donor polymer and a nonfullerene acceptor, stable OPVs are fabricated with a power conversion efficiency of 8.8% under 1 Sun and 14% under indoor lighting conditions. In an optical wireless communication experiment, a data rate of 363 Mb/s and a simultaneous harvested power of 10.9 mW are achieved in a 4-by-4 multiple-input multiple-output (MIMO) setup that consists of four laser diodes, each transmitting 56 mW optical power and four OPV cells on a single panel as receivers at a distance of 40 cm. This result is the highest reported data rate using OPVs as data receivers and energy harvesters. This finding may be relevant to future mobile communication applications because it enables enhanced wireless data communication performance while prolonging the battery life in a mobile device.

Multi-slot energy harvesting wireless communication in interference environment.

Radio frequency energy harvesting (EH) technology can harvest the electromagnetic energy in the surrounding environment, and reduce the dependence of the communication devices on battery or power grid as power source, which is a very promising means of energy substitution and acquisition scheme. The random characteristics of wireless channel fading and possible co-channel interference (CCI) have great influence on EH efficiency and wireless communication performance with more complicated theoretical analysis. In this paper, the exact closed-form expressions of effective throughput of "harvest-store-use" and "harvest-use" multi-slot EH schemes with Rayleigh channel fading and CCI are derived theoretically. The simulation results show that in Rayleigh fading channels with CCI, CCI is beneficial to energy harvesting of EH device, but it will deteriorate the reception of required signals by information receiving device. Although there are obvious differences in working mechanism, working conditions and communication performance between the "harvest-store-use" scheme and the "harvest-use" scheme, the optimal time slot should be selected to balance the transmission probability and delay, minimize the interference of CCI to the desired signal, and improve the energy conversion efficiency of the energy harvester.

Cross-Layer Design for EH Systems with Finite Buffer Constraints

Energy harvesting (EH) technology in wireless communication is a promising approach to extend the lifetime of future wireless networks. A cross-layer optimal adaptation policy for a point-to-point energy harvesting (EH) wireless communication system with finite buffer constraints over a Rayleigh fading channel based on a Semi-Markov Decision Process (SMDP) is investigated. Most adaptation strategies in the literature are based on channel-dependent adaptation. However, besides considering the channel, the state of the energy capacitor and the data buffer are also involved when proposing a dynamic modulation policy for EH wireless networks. Unlike the channel-dependent policy, which is a physical layer-based optimization, the proposed cross-layer dynamic modulation policy is a guarantee to meet the overflow requirements of the upper layer by maximizing the throughput while optimizing the transmission power and minimizing the dropping packets. Based on the states of the channel conditions, data buffer, and energy capacitor, the scheduler selects a particular action corresponding to the selected modulation constellation. Moreover, the packets are modulated into symbols according to the selected modulation type to be ready for transmission over the Rayleigh fading channel. Simulations are used to test the performance of the proposed cross-layer policy scheme, which shows that it significantly outperforms the physical layer channel-dependent policy scheme in terms of throughput only.

Smart Metering for Challenging Scenarios: A Low-Cost, Self-Powered and Non-Intrusive IoT Device.

In this work, a novel current metering device was presented. This device was intended to bring current metering capabilities to a wide variety of scenarios: Developing countries, rural areas, or any situation with technological constraints. The device was designed to provide a straightforward installation with no intrusion in the electrical panels. This was achieved by applying energy harvesting techniques and wireless communication technology for data transmission. The device was able to exploit the magnetic field inducted around a wire carrying electricity as energy harvesting, thus acquiring the power it needed to work. Since very low power was harvested, an efficient treatment for the incoming power and a minimal power consumption system were essential. Although exploiting the magnetic fields inducted around a wire has been used for years, the combination of this technology for both energy harvesting and current metering in an end-user device was off-center. To work in a wide variety of scenarios, it used Sigfox for communications as this brought wide coverage and out-of-the-box functioning. The theoretical design of the device was validated by verification assessments for the joint performance of the individual parts compounding the device, including metering capabilities and wireless communication test-bench. Finally, the metering device was tested under three distinct real-world scenarios that demonstrated the viability of the system. Results show that, depending on the metering period and the average current value in the mains line, the device could work forever acquiring and sending electricity consumption data. Perpetual working was achieved with an average current of 3.1 A to meter every 15 min, and an average current of 5 A for a 5-min metering period.

Modeling and performance analysis of energy harvesting wireless communication systems with reliable energy backup

SummaryEnergy harvesting wireless communication system (EH‐WCS) has the capability of harvesting energy for system operations from the surrounding renewable energy sources. However, the randomness and instability of the harvested energy will result in the depletion of the energy consumption. To provide reliable communication services with the quality of service (QoS) guarantee, it is necessary for the EH‐WCS to use a reliable energy backup (REB) for supplying energy to the system during the failure of its primary energy source. In this paper, a novel stochastic model, i.e., the extended Markov fluid flow model, is proposed to describe the EH‐WCS with REB. The Kolmogorov forward equations of the system model are derived. By solving the corresponding equations, we obtain the stationary distributions of the key performance metrics for the EH‐WCS with REB, including the average energy consumption rate of the EH‐WCS, the residual energy distribution, the average energy supply rate by REB, the packet queue length in data buffer, the data queue delay, and the packet blocking probability. A numerical example is provided to investigate the theoretical results, and the effects of the system parameters on the performance are further studied numerically. Both the theoretical insights and the numerical analyses are believed to be important for the design of EH‐WCSs.

Multi‐objective design of energy harvesting enabled wireless networks based on evolutionary genetic optimisation

Sustainable operation of energy-restrained wireless network services requires multiple objectives to be satisfied synchronously. Among these objectives, reduced spectrum outage, energy conservation, and minimal packet transmission failures considerably affect the energy harvesting operation of these networks. These three objectives are associated with disparate protocol layers incorporating the transport, medium access control, and physical layers of traditional networking architecture. The authors investigate energy harvesting wireless communications by formulating the multi-objective optimisation problem comprising these global networking criteria, which are simultaneously optimised with the heuristic design procedure. For this, they employ a Pareto-based evolutionary genetic algorithm technique built in the wireless network design and operation to find the optimal set of all non-dominated solutions traversing the entire design search space. Besides, iterative implementation of the presented genetic optimisation model with distinct feasible integrations of crossover and mutation operations is performed to evaluate the proficiency of the proposed scheme for evaluating the Pareto-optimal frontier set. The influence of different combinations of these operations is examined and adaptively applied with appropriate genetic parameters tuning for efficient meta-heuristic search through the candidate solution space. Simulation results demonstrate that the proposed hybrid genetic mechanism outperforms the existing methods in terms of throughput, energy efficiency, and loss rate.

Modeling and Analysis of Energy Harvesting and Smart Grid-Powered Wireless Communication Networks: A Contemporary Survey

The advancements in smart power grid and the advocation of “green communications” have inspired the wireless communication networks to harness energy from ambient environments and operate in an energy-efficient manner for economic and ecological benefits. This article presents a contemporary review of recent breakthroughs on the utilization, redistribution, trading and planning of energy harvested in future wireless networks interoperating with smart grids. This article starts with classical models of renewable energy harvesting technologies. We embark on constrained operation and optimization of different energy harvesting wireless systems, such as point-to-point, multipoint-to-point, multipoint-to-multipoint, multi-hop, and multi-cell systems. We also review wireless power and information transfer technologies which provide a special implementation of energy harvesting wireless communications. A significant part of the article is devoted to the redistribution of redundant (unused) energy harvested within cellular networks, the energy planning under dynamic pricing when smart grids are in place, and two-way energy trading between cellular networks and smart grids. Applications of different optimization tools, such as convex optimization, Lagrangian dual-based method, subgradient method, and Lyapunov-based online optimization, are compared. This article also collates the potential applications of energy harvesting techniques in emerging (or upcoming) 5G/B5G communication systems. It is revealed that an effective redistribution and two-way trading of energy can significantly reduce the electricity bills of wireless service providers and decrease the consumption of brown energy. A list of interesting research directions are provided, requiring further investigation.

A Nonlinear Recursive Model Based Optimal Transmission Scheduling in RF Energy Harvesting Wireless Communications

The transmission scheduling is a critical problem in radio frequency (RF) energy harvesting communications. Existing transmission strategies in an RF-based energy harvesting system is mainly based on a classic model, in which the data transmission is scheduled in a fixed feasible energy tunnel. In this paper, we re-examine the classic energy harvesting model and show through the theoretical analysis and experimental results that the bounds of feasible energy tunnel are dynamic, which can be affected by the transmission scheduling due to the impact of residual energy on the harvested one. To describe a practical energy harvesting process more accurately, a new model is proposed by adding a feedback loop that reflects the interplay between the energy harvest and the data transmission. Furthermore, to improve network performance, we revisit the design of an optimal transmission scheduling strategy based on the new model. To handle the challenge of the endless feedback loop in the new model, a recursive algorithm is developed. The simulation results reveal that the new transmission scheduling strategy can balance the efficiency of energy reception and energy utilization regardless of the length of energy packets, achieving improved throughput performance for wireless communications.

Online and robust resource allocation for D2D communications assisted by Green relays

Device-to-device (D2D) communications in cellular networks allow proximity users to communicate directly without going through the base station. Concentrating on scenarios where the direct communication between potential D2D users may not be reliable due to poor proximity and link condition, and paying attention to energy harvesting wireless communications, this study focuses on the green relay-assisted D2D communications, where long-term evolution-advanced layer-3 relays powered by renewable energy are employed. To achieve the trade-off between system capacity maximisation and user fairness, the authors formulate an offline resource block (RB) and power allocation problem under imperfect channel information with the objective of maximising the weighted sum-rate of all users. Then, based on battery dynamics, the original problem is reformulated as an online one with energy outage avoidance. To obtain distributed solutions, the online problem is further transformed into a convex one, and the rate outage-probability requirement is also converted for tractability. Finally, applying Lagrangian duality, the distributed RB and power allocation is derived, which is globally optimal to the reformulated online problem. Comparing with a baseline scheme where all users communicate directly without assistance of relays, numerical results show the superiority of the proposed approach in terms of the average achievable data rate.

On the Energy and Data Storage Management in Energy Harvesting Wireless Communications

Energy harvesting (EH) in wireless communications has become the focus of recent transmission technology studies. Herein, energy storage modeling is one of the crucial design benchmarks that must be treated carefully. Understanding the energy storage dynamics and the throughput levels is essential especially for communication systems in which the performance depends solely on harvested energy. While energy outages should be avoided, energy overflows should also be prevented in order to utilize all harvested energy. Hence, a simple, yet comprehensive, analytical model that can represent the characteristics of a general class of EH wireless communication systems needs to be established. In this paper, invoking tools from large deviation theory along with Markov processes, a firm connection between the energy state of the battery and the data transmission process over a wireless channel is established for an EH transmitter. In particular, a simple exponential approximation for the energy overflow probability is formulated, with which the energy decay rate in the battery as a measure of energy usage is characterized. Then, projecting the energy outages and supplies on a Markov process, a discrete state model is established and an expression for the energy outage probability for given energy arrival and demand processes is provided. Finally, under energy overflow and outage constraints, the <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">average data service (transmission) rate</i> over the wireless channel is obtained and the <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">effective capacity</i> of the system, which characterizes the maximum data arrival rate at the transmitter buffer under quality-of-service (QoS) constraints imposed on the data buffer overflow probability, is derived.

Online joint power control for cooperative jamming systems with energy harvesting

To maximize the long-term time-averaged secrecy rate of an energy harvesting wireless communication system, an online power control algorithm based on the Lyapunov optimization framework is proposed. The system is composed of a source node, a cooperative jamming node, and two destination nodes. The source node and the jamming node are powered by the energy harvesting device. Information sent to the two destination nodes is mutually confidential. Using the Lyapunov optimization framework, the original stochastic optimization problem is transformed into a per-time-slot optimization problem, and the power of the signal and that of the artificial noise are determined based on the current system state such as the power level of the batteries and channel coefficients. The fairness between the two destination nodes is considered too. Simulation results demonstrate that the proposed algorithm can effectively utilize the harvested energy and significantly improve the long-term averaged secrecy rate.

RF Energy Harvesting Wireless Communications: RF Environment, Device Hardware and Practical Issues.

Radio frequency (RF) based wireless power transfer provides an attractive solution to extend the lifetime of power-constrained wireless sensor networks. Through harvesting RF energy from surrounding environments or dedicated energy sources, low-power wireless devices can be self-sustaining and environment-friendly. These features make the RF energy harvesting wireless communication (RF-EHWC) technique attractive to a wide range of applications. The objective of this article is to investigate the latest research activities on the practical RF-EHWC design. The distribution of RF energy in the real environment, the hardware design of RF-EHWC devices and the practical issues in the implementation of RF-EHWC networks are discussed. At the end of this article, we introduce several interesting applications that exploit the RF-EHWC technology to provide smart healthcare services for animals, wirelessly charge the wearable devices, and implement 5G-assisted RF-EHWC.

Power Allocation for Energy Harvesting Wireless Communications With Energy State Information

Power allocation is investigated for a wireless transceiver pair, in which the transmitter is powered by energy harvesting and some knowledge of the energy arrival process is known. We propose to perform power allocation in two levels. In the upper level, average transmit power is allocated for stages (a stage contains a number of fading blocks). In the lower level, power allocation over fading blocks is performed within each stage, given average transmit power level allocated in the upper level for the stage. Optimal solution to the lower level that aims at ergodic capacity maximization is obtained in semi-closed-form. The upper level aims at maximization of the system throughput over the stages. As the upper-level problem is nonconvex, by using an approximation, we transform the problem into a monotonic optimization problem, which can be solved by existing numerical algorithms. Simulation demonstrates that, compared to an exhaustive search method, our proposed method has significantly less running time, at the cost of a not-significant throughput loss.

A Compact Dual-Band Rectenna for GSM900 and GSM1800 Energy Harvesting

This paper presents a compact dual-band rectenna for GSM900 and GSM1800 energy harvesting. The monopole antenna consists of a longer bent Koch fractal element for GSM900 band and a shorter radiation element for GSM1800. The rectifier is composed of a multisection dual-band matching network, two rectifying branches, and filter networks. Measured peak efficiency of the proposed rectenna is 62% at 0.88 GHz 15.9 μW/cm2 and 50% at 1.85 GHz 19.1 μW/cm2, respectively. When the rectenna is 25 m away from a cellular base station, measurement result shows that the harvested power is able to power a batteryless LCD watch and achieve 1.275 V output voltage. The proposed rectenna is compact, efficient, low cost, and easy to fabricate, and it is suitable for RF energy harvesting and various wireless communication scenarios.

Lyapunov Optimization for Energy Harvesting Wireless Sensor Communications

With the development and popularity of the renewable energy harvesting devices, the energy harvesting wireless sensor communications that can make use of the energy harvested from the nearby environments have gained more and more attentions. One key problem in the energy harvesting wireless sensor communications is the transmission strategy management, i.e., how to manage the transmission strategy at each time slot to optimize the transmission performance. In this paper, we propose to use Lyapunov optimization theory to maximize the expected good bits per packet transmission for the source node in an energy harvesting wireless communication system. Considering the channel and battery states, we adapt the transmission power and modulation type to achieve such a goal. The problem is formulated as an optimization where the objective function is the long-term average good bits per packet transmission and the constraints are the bounded long-term average battery level and bit error rate. To solve the optimization, we introduce virtual queues and employ the Lyapunov optimization theory to transform the optimization with long-term average format into optimizing the drift-plus-penalty problem. The drift-plus-penalty is further upper bounded with variables only related to current time slot, which greatly simplifies the optimization problem. Theoretic analysis is also conducted to show that the optimal solution is limited by an upper bound that is independent of the operation time index. Finally, simulation results with real solar irradiance data show that the proposed algorithm can achieve much better performance than existing approaches based on Markov decision process and water-filling.

Lyapunov Optimized Cooperative Communications With Stochastic Energy Harvesting Relay

Energy harvesting (EH) wireless communications have become more and more popular due to its capability of effectively reducing the battery replacement time. In this paper, we focus on decode-and-forward-based cooperative wireless communications with an EH relay. The stochastic characteristics of the harvestable energy and the wireless channel make it difficult to optimally manage the energy harvested at the relay for better communication performance. We formulate such a problem as an optimization by minimizing the long-term average symbol error rate (SER) subject to a battery constraint. Based on the Lyapunov optimization theory, we utilize the virtual queue technique and transform the optimization problem into a drift-plus-penalty minimization. Then, we conduct theoretic analysis of the optimal energy strategy derived by the proposed scheme. Specifically, we show the convexity of the drift-plus-penalty minimization problem, and prove that the virtual queue is bounded and the battery constraint is always satisfied. We also show that the proposed optimal energy management strategy is limited by an upper bound that is independent of the operation time index, derive the closed-form expression for the asymptotical average SER, and analyze the corresponding diversity order and EH gain. Finally, simulation results using the real solar irradiance data show that the proposed algorithm can achieve much better performance in terms of both average SER and diversity order, compared with the Markov decision process-based method.