Implications of Energy Profile and Storage on Energy Harvesting Sensor Link Performance

Energy harvesting sensors (EHS), which harvest energy from the environment in order to sense and then communicate their measurements over a wireless link, provide the tantalizing possibility of perpetual lifetime operation of a sensor network. The wireless communication link design problem needs to be revisited for these sensors as the energy harvested can be random and small and not available when required. In this paper, we develop a simple model that captures the interactions between important parameters that govern the communication link performance of a EHS node, and analyze its outage probability for both slow fading and fast fading wireless channels. Our analysis brings out the critical importance of the energy profile and the energy storage capability on the EHS link performance. Our results show that properly tuning the transmission parameters of the EHS node and having even a small amount of energy storage capability improves the EHS link performance considerably.

Optimal Sleep-Wake Policies for an Energy Harvesting Sensor Node

We study a sensor node with an energy harvesting source. In any slot,the sensor node is in one of two modes: Wake or Sleep. The generated energy is stored in a buffer. The sensor node senses a random field and generates a packet when it is awake. These packets are stored in a queue and transmitted in the wake mode using the energy available in the energy buffer. We obtain energy management policies which minimize a linear combination of the mean queue length and the mean data loss rate. Then, we obtain two easily implementable suboptimal policies and compare their performance to that of the optimal policy. Next, we extend the Throughput Optimal policy developed in our previous work to sensors with two modes. Via this policy, we can increase the through put substantially and stabilize the data queue by allowing the node to sleep in some slots and to drop some generated packets. This policy requires minimal statistical knowledge of the system. We also modify this policy to decrease the switching costs.

Joint Power Control, Scheduling and Routing for Multihop Energy Harvesting Sensor Networks

We study wireless multihop energy harvesting sensor networks employed for random field estimation. The sensors sense the random field and generate data that is to be sent to a fusion node for estimation. Each sensor has an energy harvesting source and can operate in two modes: Wake and Sleep. We consider the problem of obtaining jointly optimal power control, routing and scheduling policies that ensure a fair utilization of network resources. This problem has a high computational complexity. Therefore, we develop a computationally efficient suboptimal approach to obtain good solutions to this problem. We study the optimal solution and performance of the suboptimal approach through some numerical examples.

Voluntary Energy Harvesting Relays and Selection in Cooperative Wireless Networks

The use of energy harvesting (EH) nodes as cooperative relays is a promising and emerging solution in wireless systems such as wireless sensor networks. It harnesses the spatial diversity of a multi-relay network and addresses the vexing problem of a relay's batteries getting drained in forwarding information to the destination. We consider a cooperative system in which EH nodes volunteer to serve as amplify-and-forward relays whenever they have sufficient energy for transmission. For a general class of stationary and ergodic EH processes, we introduce the notion of energy constrained and energy unconstrained relays and analytically characterize the symbol error rate of the system. Further insight is gained by an asymptotic analysis that considers the cases where the signal-to-noise-ratio or the number of relays is large. Our analysis quantifies how the energy usage at an EH relay and, consequently, its availability for relaying, depends not only on the relay's energy harvesting process, but also on its transmit power setting and the other relays in the system. The optimal static transmit power setting at the EH relays is also determined. Altogether, our results demonstrate how a system that uses EH relays differs in significant ways from one that uses conventional cooperative relays.

Structural and electrical properties of radio frequency magnetron sputtered tantalum oxide films: Influence of post-deposition annealing

The as-deposited and annealed radio frequency reactive magnetron sputtered tantalum oxide (Ta2O5) films were characterized by studying the chemical binding configuration, structural and electrical properties. X-ray photoelectron spectroscopy and X-ray diffraction analysis of the films elucidate that the film annealed at 673 K was stoichiometric with orthorhombic beta-phase Ta2O5. The dielectric constant values of the tantalum oxide capacitors with the sandwich structure of Al/Ta2O5/Si were in the range from 14 to 26 depending on the post-deposition annealing temperature. The leakage current density was < 20 nA cm(-2) at the gate bias voltage of 0.04 MV/cm for the annealed films. The electrical conduction mechanism observed in the films was Poole-Frenkel. (C) 2010 Elsevier Ltd. All rights reserved.

Profile-Based Load Scheduling in Wireless Energy Harvesting Sensors for Data Rate Maximization

In this paper, power management algorithms for energy harvesting sensors (EHS) that operate purely based on energy harvested from the environment are proposed. To maintain energy neutrality, EHS nodes schedule their utilization of the harvested power so as to save/draw energy into/from an inefficient battery during peak/low energy harvesting periods, respectively. Under this constraint, one of the key system design goals is to transmit as much data as possible given the energy harvesting profile. For implementational simplicity, it is assumed that the EHS transmits at a constant data rate with power control, when the channel is sufficiently good. By converting the data rate maximization problem into a convex optimization problem, the optimal load scheduling (power management) algorithm that maximizes the average data rate subject to energy neutrality is derived. Also, the energy storage requirements on the battery for implementing the proposed algorithm are calculated. Further, robust schemes that account for the insufficiency of battery storage capacity, or errors in the prediction of the harvested power are proposed. The superior performance of the proposed algorithms over conventional scheduling schemes are demonstrated through computations using numerical data from solar energy harvesting databases.

Throughput Maximization of Delay-Constrained Traffic in Wireless Energy Harvesting Sensors

A wireless Energy Harvesting Sensor (EHS) needs to send data packets arriving in its queue over a fading channel at maximum possible throughput while ensuring acceptable packet delays. At the same time, it needs to ensure that energy neutrality is satisfied, i.e., the average energy drawn from a battery should equal the amount of energy deposited in it minus the energy lost due to the inefficiency of the battery. In this work, a framework is developed under which a system designer can optimize the performance of the EHS node using power control based on the current channel state information, when the EHS node employs a single modulation and coding scheme and the channel is Rayleigh fading. Optimal system parameters for throughput optimal, delay optimal and delay-constrained throughput optimal policies that ensure energy neutrality are derived. It is seen that a throughput optimal (maximal) policy is packet delay-unbounded and an average delay optimal (minimal) policy achieves negligibly small throughput. Finally, the influence of the harvested energy profile on the performance of the EHS is illustrated through the example of solar energy harvesting.

Coupled electro-mechanical response of an electroactive polymer cantilever structure and its application in energy harvesting

Ionic polymer-metal composites (IPMC), piezoelectric polymer composites and nematic elastomer composites are materials, which exhibit characteristics of both sensors and actuators. Large deformation and curvature are observed in these systems when electric potential is applied. Effects of geometric non-linearity due to the chargeinduced motion in these materials are poorly understood. In this paper, a coupled model for understanding the behavior of an ionic polymer beam undergoing large deformation and large curvature is presented. Maxwell's equations and charge transport equations are considered which couple the distribution of the ion concentration and the pressure gradient along length of a cantilever beam with interdigital electrodes. A nonlinear constitutive model is derived accounting for the visco-elasto-plastic behavior of these polymers and based on the hypothesis that the presence of electrical charge stretches/contracts bonds, which give rise to electrical field dependent softening/hardening. Polymer chain orientation in statistical sense plays a role on such softening or hardening. Elementary beam kinematics with large curvature is considered. A model for understanding the deformation due to electrostatic repulsion between asymmetrical charge distributions across the cross-sections is presented. Experimental evidence that Silver(Ag) nanoparticle coated IPMCs can be used for energy harvesting is reported. An IPMC strip is vibrated in different environments and the electric power against a resistive load is measured. The electrical power generated was observed to vary with the environment with maximum power being generated when the strip is in wet state. IPMC based energy harvesting systems have potential applications in tidal wave energy harvesting, residual environmental energy harvesting to power MEMS and NEMS devices.

Measurement of Electron Spin Lifetime and Optical Orientation Efficiency in Germanium Using Electrical Detection of Radio Frequency Modulated Spin Polarization

We propose and demonstrate a technique for electrical detection of polarized spins in semiconductors in zero applied magnetic fields. Spin polarization is generated by optical injection using circularly polarized light which is modulated rapidly using an electro-optic cell. The modulated spin polarization generates a weak time-varying magnetic field which is detected by a sensitive radio-frequency coil. Using a calibrated pickup coil and amplification electronics, clear signals were obtained for bulk GaAs and Ge samples from which an optical spin orientation efficiency of 4.8% could be determined for Ge at 1342 nm excitation wavelength. In the presence of a small external magnetic field, the signal decayed according to the Hanle effect, from which a spin lifetime of 4.6 +/- 1.0 ns for electrons in bulk Ge at 127 K was extracted.

High sensitivity detection of radio-frequency modulated magnetic moment in semiconductors

An experimental setup has been realized to measure weak magnetic moments which can be modulated at radio frequencies (similar to 1-5 MHz). Using an optimized radio-frequency (RF) pickup coil and lock-in amplifier, an experimental sensitivity of 10(-15) Am(2) corresponding to 10(-18) emu has been demonstrated with a 1 s time constant. The detection limit at room temperature is 9.3 x 10(-16) Am(2)/root Hz limited by Johnson noise of the coil. The setup has been used to directly measure the magnetic moment due to a small number (similar to 7 x 10(8)) of spin polarized electrons generated by polarization modulated optical radiation in GaAs and Ge. (C) 2011 American Institute of Physics. [doi: 10.1063/1.3654229]

Power and Discrete Rate Adaptation for Energy Harvesting Wireless Nodes

Energy Harvesting (EH) nodes, which harvest energy from the environment in order to communicate over a wireless link, promise perpetual operation of a wireless network with battery-powered nodes. In this paper, we address the throughput optimization problem for a rate-adaptive EH node that chooses its rate from a set of discrete rates and adjusts its power depending on its channel gain and battery state. First, we show that the optimal throughput of an EH node is upper bounded by the throughput achievable by a node that is subject only to an average power constraint. We then propose a simple transmission scheme for an EH node that achieves an average throughput close to the upper bound. The scheme's parameters can be made to account for energy overheads such as battery non-idealities and the energy required for sensing and processing. The effect of these overheads on the average throughput is also analytically characterized.

Optimal energy management policies for energy harvesting sensor nodes

We study a sensor node with an energy harvesting source. The generated energy can be stored in a buffer. The sensor node periodically senses a random field and generates a packet. These packets are stored in a queue and transmitted using the energy available at that time. We obtain energy management policies that are throughput optimal, i.e., the data queue stays stable for the largest possible data rate. Next we obtain energy management policies which minimize the mean delay in the queue. We also compare performance of several easily implementable sub-optimal energy management policies. A greedy policy is identified which, in low SNR regime, is throughput optimal and also minimizes mean delay.

Dual-Stage Power Management Algorithms for Energy Harvesting Sensors

In this paper, we propose power management algorithms for maximizing the utility of energy harvesting sensors (EHS) that operate purely on the basis of energy harvested from the environment. In particular, we consider communication (i.e., transmission and reception) power management issues for EHS under an energy neutrality constraint. We also consider the fixed power loss effects of the circuitry, the battery inefficiency and its storage capacity, in the design of the algorithms. We propose a two-stage structure that exploits the inherent difference in the timescales at which the energy harvesting and channel fading processes evolve, without loss of optimality of the resulting solution. The outer stage schedules the power that can be used by an inner stage algorithm, so as to maximize the long term average utility and at the same time maintain energy neutrality. The inner stage optimizes the communication parameters to achieve maximum utility in the short-term, subject to the power constraint imposed by the outer stage. We optimize the algorithms for different transmission schemes such as the truncated channel inversion and retransmission strategies. The performance of the algorithms is illustrated via simulations using solar irradiance data, and for the case of Rayleigh fading channels. The results demonstrate the significant performance benefits that can be obtained using the proposed power management algorithms compared to the energy efficient (optimum when there is no storage) and the uniform power consumption (optimum when the battery has infinite capacity and is perfectly efficient) approaches.

Bond Graph Modeling for Energy-Harvesting Wireless Sensor Networks

Researchers can use bond graph modeling, a tool that takes into account the energy conservation principle, to accurately assess the dynamic behavior of wireless sensor networks on a continuous basis.