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06-09-2018

Battery and supercapacitor imperfections modeling and comparison for RF energy harvesting wireless sensor network

Authors: Arpita Jaitawat, Arun Kumar Singh

Published in: Wireless Networks | Issue 2/2020

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Abstract

In an energy harvesting communication system, the main challenge is to improve network lifetime and maximize throughput by allocating optimal power over a finite span of time, with varying channel and energy. Considering (1) causal state information (SI) of channel and energy (CSI and ESI) and (2) energy storage device imperfections, the problem of power allocation is solved using dynamic programming. As compared to the battery, the supercapacitor is a good alternative for network lifetime improvement, but the imperfections hinder the performance. In this paper, imperfections (storage inefficiency and energy leakage equation) are modeled for supercapacitor and battery. We consider a constant leakage rate for battery. Also, the imperfections of battery and supercapacitor are compared to find which imperfection of supercapacitor is a bottleneck in system performance in different settings (varying channel conditions). The analysis is supported by numerical results.

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Ashraphijuo, M., Aggarwal, V., & Wang, X. (2015). Energy harvesting communication using limited battery with efficiency. In 53rd Annual Allerton Conference on Communication, Control, and Computing (Allerton), 2015 (pp. 301–306). IEEE.

Biason, A., & Zorzi, M. (2016). On the effects of battery imperfections in an energy harvesting device. In 2016 International Conference on Computing, Networking and Communications (ICNC) (pp. 1–7). IEEE.

Bu-802b: What does elevated self-discharge do? http://batteryuniversity.com/learn/article/elevating_self_discharge.

Conway, B. E. (2013). Electrochemical supercapacitors: Scientific fundamentals and technological applications. Berlin: Springer.

Cover, T. M., & Thomas, J. A. (2006). Introduction and preview. Elements of information theory (pp. 1–11). New York: Wiley.

Devillers, B., & Gündüz, D. (2012). A general framework for the optimization of energy harvesting communication systems with battery imperfections. Journal of Communications and Networks, 14(2), 130–139.CrossRef

Hall, P. J., & Bain, E. J. (2008). Energy-storage technologies and electricity generation. Energy Policy, 36(12), 4352–4355.CrossRef

Heinzelman, W. R., Chandrakasan, A., & Balakrishnan, H. (2000). Energy-efficient communication protocol for wireless microsensor networks. In Proceedings of the 33rd Annual Hawaii International Conference On System Sciences, 2000 (p. 10). IEEE.

Ho, C. K., & Zhang, R. (2012). Optimal energy allocation for wireless communications with energy harvesting constraints. IEEE Transactions on Signal Processing, 60(9), 4808–4818.MathSciNetCrossRef

10.

Huang, C., Zhang, R., & Cui, S. (2014). Optimal power allocation for outage probability minimization in fading channels with energy harvesting constraints. IEEE Transactions on Wireless Communications, 13(2), 1074–1087.CrossRef

11.

Jog, V., & Anantharam, V. (2014). An energy harvesting awgn channel with a finite battery. In 2014 IEEE International Symposium on Information Theory (ISIT) (pp. 806–810). IEEE.

12.

Kansal, A., Hsu, J., Zahedi, S., & Srivastava, M. B. (2007). Power management in energy harvesting sensor networks. ACM Transactions on Embedded Computing Systems (TECS), 6(4), 32.CrossRef

13.

Kaus, M., Kowal, J., & Sauer, D. U. (2010). Modelling the effects of charge redistribution during self-discharge of supercapacitors. Electrochimica Acta, 55(25), 7516–7523.CrossRef

14.

Kowal, J., Avaroglu, E., Chamekh, F., Šenfelds, A., Thien, T., Wijaya, D., et al. (2011). Detailed analysis of the self-discharge of supercapacitors. Journal of Power Sources, 196(1), 573–579.CrossRef

15.

Kuila, P., & Jana, P. K. (2014). Energy efficient clustering and routing algorithms for wireless sensor networks: Particle swarm optimization approach. Engineering Applications of Artificial Intelligence, 33, 127–140.CrossRef

16.

Ku, M. L., Li, W., Chen, Y., & Liu, K. R. (2016). Advances in energy harvesting communications: Past, present, and future challenges. IEEE Communications Surveys and Tutorials, 18(2), 1384–1412.CrossRef

17.

Kumar, S., et al. (2015). Energy efficient clustering algorithm for wsn. In 2015 2nd International Conference on Signal Processing and Integrated Networks (SPIN) (pp. 990–993). IEEE.

18.

Lew, A., & Mauch, H. (2006). Dynamic programming: A computational tool (Vol. 38). Berlin: Springer.MATH

19.

Li, H., Xu, J., Zhang, R., & Cui, S. (2015). A general utility optimization framework for energy-harvesting-based wireless communications. IEEE Communications Magazine, 53(4), 79–85.CrossRef

20.

Minasian, A., ShahbazPanahi, S., & Adve, R. S. (2014). Energy harvesting cooperative communication systems. IEEE Transactions on Wireless Communications, 13(11), 6118–6131.CrossRef

21.

Musolino, V., Tironi, E., & di Milano, P. (2010). A comparison of supercapacitor and high-power lithium batteries. In: Electrical Systems for Aircraft, Railway and Ship Propulsion (ESARS) (pp. 1–6). IEEE (2010)

22.

Panasonic electric double layer capacitors hw series datasheet. http://www.mouser.com/ds/2/315/ABC0000CE8-462878.pdf.

23.

Pell, W. G., Conway, B. E., Adams, W. A., & de Oliveira, J. (1999). Electrochemical efficiency in multiple discharge/recharge cycling of supercapacitors in hybrid ev applications. Journal of Power Sources, 80(1), 134–141.CrossRef

24.

Puterman, M. L. (2014). Markov decision processes: Discrete stochastic dynamic programming. New York: Wiley.MATH

25.

Shafieirad, H., Adve, R. S., & ShahbazPanahi, S. (2017). Throughput maximization with an energy outage constraint for energy harvesting links. In Wireless Communications and Networking Conference Workshops (WCNCW), 2017 IEEE (pp. 1–6). IEEE.

26.

Tutuncuoglu, K., Yener, A., & Ulukus, S. (2015). Optimum policies for an energy harvesting transmitter under energy storage losses. IEEE Journal on Selected Areas in Communications, 33(3), 467–481.CrossRef

27.

Wang, X., Gong, J., Hu, C., Zhou, S., & Niu, Z. (2015). Optimal power allocation on discrete energy harvesting model. EURASIP Journal on Wireless Communications and Networking, 2015(1), 48.CrossRef

28.

Wu, Q., Tao, M., Chen, W., & Wu, J. (2014). Optimal energy-efficient transmission for fading channels with an energy harvesting transmitter. In Global Communications Conference (GLOBECOM), 2014 IEEE (pp. 4294–4299). IEEE.

29.

Yang, H., & Zhang, Y. (2011). Self-discharge analysis and characterization of supercapacitors for environmentally powered wireless sensor network applications. Journal of Power Sources, 196(20), 8866–8873.CrossRef

30.

Zenaidi, M. R., Rezki, Z., & Alouini, M. S. (2016). On communications under stochastic energy harvesting with noisy channel state information. In Global Communications Conference (GLOBECOM), 2016 IEEE (pp. 1–6). IEEE.

31.

Zenaidi, M. R., Rezki, Z., & Alouini, M. S. (2017). Performance limits of online energy harvesting communications with noisy channel state information at the transmitter. IEEE Access, 5, 1239–1249.CrossRef

32.

Zhang, H., Du, J., Cheng, J., Long, K., & Leung, V. C. (2018). Incomplete csi based resource optimization in swipt enabled heterogeneous networks: A non-cooperative game theoretic approach. IEEE Transactions on Wireless Communications, 17(3), 1882–1892.CrossRef

33.

Zhang, H., Huang, S., Jiang, C., Long, K., Leung, V. C., & Poor, H. V. (2017). Energy efficient user association and power allocation in millimeter-wave-based ultra dense networks with energy harvesting base stations. IEEE Journal on Selected Areas in Communications, 35(9), 1936–1947.CrossRef

34.

Zhang, Y., & Yang, H. (2011). Modeling and characterization of supercapacitors for wireless sensor network applications. Journal of Power Sources, 196(8), 4128–4135.CrossRef

Title: Battery and supercapacitor imperfections modeling and comparison for RF energy harvesting wireless sensor network
Authors: Arpita Jaitawat
Arun Kumar Singh
Publication date: 06-09-2018
Publisher: Springer US
Published in: Wireless Networks / Issue 2/2020
Print ISSN: 1022-0038
Electronic ISSN: 1572-8196
DOI: https://doi.org/10.1007/s11276-018-1831-z

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