Optimal Save-Then-Transmit Protocol for Energy Harvesting Wireless Transmitters

In this paper, the design of a wireless communication device relying exclusively on energy harvesting is considered. Due to the inability of rechargeable energy sources to charge and discharge at the same time, a constraint we term the energy half-duplex constraint, two rechargeable energy storage devices (ESDs) are assumed so that at any given time, there is always one ESD being recharged. The energy harvesting rate is assumed to be a random variable that is constant over the time interval of interest. A save-then-transmit (ST) protocol is introduced, in which a fraction of time ρ (dubbed the save-ratio) is devoted exclusively to energy harvesting, with the remaining fraction 1-ρ used for data transmission. The ratio of the energy obtainable from an ESD to the energy harvested is termed the energy storage efficiency, η. We address the practical case of the secondary ESD being a battery with η <; 1, and the main ESD being a super-capacitor with η = 1. Important properties of the optimal save-ratio that minimizes outage probability are derived, from which useful design guidelines are drawn. In addition, we compare the outage performance of random power supply to that of constant power supply over the Rayleigh fading channel. The diversity order with random power is shown to be the same as that of constant power, but the performance gap can be large. Finally, we extend the proposed ST protocol to wireless networks with multiple transmitters. It is shown that the system-level outage performance is critically dependent on the number of transmitters and the optimal save-ratio for single-channel outage minimization.

[1]  P. R. Nelson The algebra of random variables , 1979 .

[2]  Milton Abramowitz,et al.  Handbook of Mathematical Functions with Formulas, Graphs, and Mathematical Tables , 1964 .

[3]  Shuguang Cui,et al.  Throughput Maximization for the Gaussian Relay Channel with Energy Harvesting Constraints , 2011, IEEE Journal on Selected Areas in Communications.

[4]  I. M. Pyshik,et al.  Table of integrals, series, and products , 1965 .

[5]  R. Cooke Real and Complex Analysis , 2011 .

[6]  Pramod Viswanath,et al.  Capacity of Fading Gaussian Channel with an Energy Harvesting Sensor Node , 2011, 2011 IEEE Global Telecommunications Conference - GLOBECOM 2011.

[7]  Rui Zhang,et al.  Optimal save-then-transmit protocol for energy harvesting wireless transmitters , 2012, ISIT.

[8]  Ian F. Akyildiz,et al.  Sensor Networks , 2002, Encyclopedia of GIS.

[9]  Prasun Sinha,et al.  Joint Energy Management and Resource Allocation in Rechargeable Sensor Networks , 2010, 2010 Proceedings IEEE INFOCOM.

[10]  Purushottam Kulkarni,et al.  Energy Harvesting Sensor Nodes: Survey and Implications , 2011, IEEE Communications Surveys & Tutorials.

[11]  Jing Yang,et al.  Transmission with Energy Harvesting Nodes in Fading Wireless Channels: Optimal Policies , 2011, IEEE Journal on Selected Areas in Communications.

[12]  Rui Zhang,et al.  Optimal Energy Allocation for Wireless Communications With Energy Harvesting Constraints , 2011, IEEE Transactions on Signal Processing.

[13]  Vinod Sharma,et al.  Efficient energy management policies for networks with energy harvesting sensor nodes , 2008, 2008 46th Annual Allerton Conference on Communication, Control, and Computing.

[14]  D. Owen Handbook of Mathematical Functions with Formulas , 1965 .

[15]  Geoffrey Ye Li,et al.  Energy-efficient link adaptation in frequency-selective channels , 2010, IEEE Transactions on Communications.

[16]  Aylin Yener,et al.  Optimum Transmission Policies for Battery Limited Energy Harvesting Nodes , 2010, IEEE Transactions on Wireless Communications.

[17]  Aylin Yener,et al.  Optimal power policy for energy harvesting transmitters with inefficient energy storage , 2012, 2012 46th Annual Conference on Information Sciences and Systems (CISS).

[18]  Anantha Chandrakasan,et al.  Dynamic Power Management in Wireless Sensor Networks , 2001, IEEE Des. Test Comput..

[19]  Sennur Ulukus,et al.  Information-theoretic analysis of an energy harvesting communication system , 2010, 2010 IEEE 21st International Symposium on Personal, Indoor and Mobile Radio Communications Workshops.

[20]  W. Rudin Real and complex analysis, 3rd ed. , 1987 .

[21]  Candice King,et al.  Fundamentals of wireless communications , 2013, 2013 IEEE Rural Electric Power Conference (REPC).

[22]  Eytan Modiano,et al.  Optimal energy allocation and admission control for communications satellites , 2002, Proceedings.Twenty-First Annual Joint Conference of the IEEE Computer and Communications Societies.

[23]  Umberto Spagnolini,et al.  Medium Access Control Protocols for Wireless Sensor Networks with Energy Harvesting , 2011, IEEE Transactions on Communications.

[24]  Vinod Sharma,et al.  Optimal energy management policies for energy harvesting sensor nodes , 2008, IEEE Transactions on Wireless Communications.

[25]  Halim Yanikomeroglu,et al.  On the approximation of the generalized-Κ distribution by a gamma distribution for modeling composite fading channels , 2010, IEEE Transactions on Wireless Communications.

[26]  Joseph Lipka,et al.  A Table of Integrals , 2010 .

[27]  I. S. Gradshteyn,et al.  Table of Integrals, Series, and Products , 1976 .

[28]  Deniz Gündüz,et al.  A general framework for the optimization of energy harvesting communication systems with battery imperfections , 2011, Journal of Communications and Networks.

[29]  Jing Yang,et al.  Optimal Packet Scheduling in an Energy Harvesting Communication System , 2010, IEEE Transactions on Communications.

[30]  Saralees Nadarajah,et al.  Exact distribution of the product of m gamma and n Pareto random variables , 2011, J. Comput. Appl. Math..