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Finitehorizon optimal transmission policies for energy harvesting sensors
 in International Conference on Acoustics, Speech, and Signal Processing (ICASSP). IEEE
, 2014
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Energy Harvesting Wireless Communications: A Review of Recent Advances
"... Abstract—This paper summarizes recent contributions in the broad area of energy harvesting wireless communications. In particular, we provide the current state of the art for wireless networks composed of energy harvesting nodes, starting from the informationtheoretic performance limits to transmis ..."
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Abstract—This paper summarizes recent contributions in the broad area of energy harvesting wireless communications. In particular, we provide the current state of the art for wireless networks composed of energy harvesting nodes, starting from the informationtheoretic performance limits to transmission scheduling policies and resource allocation, medium access, and networking issues. The emerging related area of energy transfer for selfsustaining energy harvesting wireless networks is considered in detail covering both energy cooperation aspects and simultaneous energy and information transfer. Various potential models with energy harvesting nodes at different network scales are reviewed, as well as models for energy consumption at the nodes. Index Terms—Energy harvesting communications, energy cooperation, simultaneous wireless information and energy transfer. I.
Long term throughput and approximate capacity of transmitterreceiver energy harvesting channel with fading
 IEEE ICCS
, 2014
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A crosslayer perspective on energy harvesting aided green communications over fading channel
 Proc. the 2nd IEEE INFOCOM Workshop on Communications and Control for Smart Energy Systems (CCSES 2013
, 2013
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EnergyHarvesting Active Networked Tags (EnHANTs) will be a ne...
"... This article focuses on a new type of wireless devices in the domain between RFIDs and sensor networks— EnergyHarvesting Active Networked Tags (EnHANTs). Future EnHANTs will be small, flexible, and selfpowered devices that can be attached to objects that are traditionally not networked (e.g., book ..."
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This article focuses on a new type of wireless devices in the domain between RFIDs and sensor networks— EnergyHarvesting Active Networked Tags (EnHANTs). Future EnHANTs will be small, flexible, and selfpowered devices that can be attached to objects that are traditionally not networked (e.g., books, furniture, toys, produce, and clothing). Therefore, they will provide the infrastructure for various tracking applications and can serve as one of the enablers for the Internet of Things. We present the design considerations for the EnHANT prototypes, developed over the past 4 years. The prototypes harvest indoor light energy using custom organic solar cells, communicate and form multihop networks using ultralowpower UltraWideband Impulse Radio (UWBIR) transceivers, and dynamically adapt their communications and networking patterns to the energy harvesting and battery states. We describe a smallscale testbed that uniquely allows evaluating different algorithms with tracebased light energy inputs. Then, we experimentally evaluate the performance of different energyharvesting adaptive policies with organic solar cells and UWBIR transceivers. Finally, we discuss the lessons learned during the prototype and testbed design process.
Computing WorstCase Performance Guarantees of Scheduling Algorithms Maximizing Weighted Throughput in EnergyHarvesting Networks
"... Energy harvesting has recently emerged as a technique to enable longer operating time of sensor networks. However, due to harvesting energy’s notcompletelypredictable stochastic nature, some packets may still fail to be transmitted due to insufficient energy supply. Also, packets in sensor network ..."
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Energy harvesting has recently emerged as a technique to enable longer operating time of sensor networks. However, due to harvesting energy’s notcompletelypredictable stochastic nature, some packets may still fail to be transmitted due to insufficient energy supply. Also, packets in sensor networks are usually associated with sensitive timecritical information. Based on these observations, we theoretically study algorithms scheduling weighted packets with deadlines in energyharvesting networks. In our model, packets arrive in an online manner, each packet has a value representing its priority and a value representing its deadline. Harvesting energy is gathered over time and transmitting one packet takes a unit of energy. The objective is to maximize the total value of the packets sent, subject to energy and deadline constraints. In this paper, we design both offline and online algorithms maximizing weighted throughput. We analyze these algorithms ’ performance guarantees against their worstcase scenarios and empirically compare them with the conventional and classic scheduling algorithms. The simulation results show that our online algorithms have far better performance than conventional ones.
Throughput Maximization in Wireless Powered Communication Networks with Energy Saving
"... Abstract—This paper considers a time division multiple access scenario where a wireless access point transmits to a group of users which harvest the energy and then use this energy to transmit back to the access point. Past approaches have found the optimal time allocation to maximize sum throughput ..."
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Abstract—This paper considers a time division multiple access scenario where a wireless access point transmits to a group of users which harvest the energy and then use this energy to transmit back to the access point. Past approaches have found the optimal time allocation to maximize sum throughput under the assumption that the users must use all of their harvested power in each block of the “harvestthentransmit ” protocol. This paper considers optimal time and energy allocation to maximize the sum throughput for the case when the nodes can save energy for later blocks. To maximize the sum throughput over a finite horizon, the initial optimization problem is separated into two subproblems and finally can be formulated into a standard boxconstrained optimization problem, which can be solved efficiently. A tight upper bound is derived by relaxing the energy harvesting causality. Simulation results are also provided to demonstrate the “harvestthentransmit ” protocol with energy saving provides improved sum throughput increasing with the number of transmission blocks. Index Terms—wireless power transfer, energy harvesting, sum throughput maximization I.
1Optimal policies for twouser Energy Harvesting Device networks with imperfect StateofCharge knowledge
"... Abstract—Energy Harvesting Devices (EHDs) are enjoying continuously increasing popularity in Wireless Sensor Network research, due to their ability to “harvest ” energy from the environment, thus allowing longterm and autonomous operation. Traditional approaches generally assume that the exact ener ..."
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Abstract—Energy Harvesting Devices (EHDs) are enjoying continuously increasing popularity in Wireless Sensor Network research, due to their ability to “harvest ” energy from the environment, thus allowing longterm and autonomous operation. Traditional approaches generally assume that the exact energy value of the StateofCharge (SOC) of an EHD is known. In reality, batteries are practically composed by electrochemical rechargeable elements or supercapacitors, where the estimation of the energy levels is a complex task. In this paper, we analyze operation policies able to maximize the longterm reward for a network consisting of a pair of EHDs and a central controller (CC), under imperfect knowledge of the SOC. More precisely, we suppose that the CC only knows whether each EHD is “LOW” or “HIGH, ” and has to determine the amount of energy devoted to the transmission over a shared wireless channel. We show that the performance degradation due to the imperfect knowledge of the SOC decreases with the battery capacity of the two nodes, and is practically negligible when this value is sufficiently high. I.
1Optimal Adaptive Random Multiaccess in Energy Harvesting Wireless Sensor Networks
"... Wireless sensors can integrate rechargeable batteries and energyharvesting (EH) devices to enable longterm, autonomous operation, thus requiring intelligent energy management to limit the adverse impact of energy outages. This work considers a network of EH wireless sensors, which report packets w ..."
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Wireless sensors can integrate rechargeable batteries and energyharvesting (EH) devices to enable longterm, autonomous operation, thus requiring intelligent energy management to limit the adverse impact of energy outages. This work considers a network of EH wireless sensors, which report packets with random utility value to a fusion center (FC) over a shared wireless channel. We design decentralized access schemes, where each node performs a local decision to transmit/discard the packet, based on an estimate of the packet’s utility, its own energy level, and the scenario state of the EH process, with the objective to maximize the average longterm aggregate utility of the packets received at the FC. Due to the nonconvex structure of the problem, we develop an approximate optimization by resorting to a mathematical artifice based on a game theoretic formulation of the multiaccess problem, where the nodes do not behave strategically, but rather attempt to maximize a common network utility with respect to their own policy. We characterize the symmetric Nashequilibrium (SNE), where all nodes employ the same policy, we prove its uniqueness, and show that it is a local maximum of the original problem. We present an algorithm to compute the SNE and propose a heuristic scheme, which is optimal for large battery capacity. We show numerically that the SNE achieves nearoptimal performance, within 3 % of the optimal policy, at a fraction of the complexity, and identify two operational regimes of EHnetworks: an energylimited scenario, where energy is scarce and the channel is underutilized, and a networklimited scenario, where energy is abundant and the shared wireless channel represents the bottleneck of the system. I.