Abstract
Communication interference and the energy limitation of nodes seriously hamper the fundamental performance of wireless sensor networks (WSN) such as throughput and network lifetime. In this paper, we focus on the Successive Interference Cancellation (SIC) aiming to realize multi-node concurrency communication and propose a heuristic power control algorithm. To prolong the network lifetime, we consider the scenario of mobile wireless charging equipment (WCE) periodically charging each node’s battery wirelessly. Time-slice scheduling scheme and energy consumption optimization protocol are adopted to design an efficient cross-layer charging strategy. Then we use a near-optimal method to transform the original problem into a linear problem which yields identical optimal value. Simulation results demonstrate that adopting SIC and WCE can greatly improve channel utilization ratio and increase network throughput by 200% to 500% while ensuring the network lifetime.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Similar content being viewed by others
References
Potdar, V., Sharif, A., Chang, E.: Wireless sensor networks: a survey. In: Proceedings of International Conference on Advanced Information Networking and Applications (AINA 2009), Bradford, UK, pp. 636–641, May 2009
Kontik, M., Coleri Ergen, S.: Distributed medium access control protocol for successive interference cancellation-based wireless ad hoc networks. IEEE Commun. Lett. 21(2), 354–357 (2017)
Haqbeen, J.A., Ito, T., Arifuzzaman, M., et al.: Joint routing, MAC and physical layer protocol for wireless sensor networks. In: TENCON 2017–2017 IEEE Region 10 Conference, Malaysia, Penang, pp. 935–940 (2017)
Zhu, Y., Li, E., Chi, K.: Encoding scheme to reduce energy consumption of delivering data in radio frequency powered battery-free wireless sensor networks. IEEE Trans. Veh. Technol. 67(4), 3085–3097 (2018)
Cai, Z., Zheng, X.: A private and efficient mechanism for data uploading in smart cyber-physical systems. IEEE Trans. Netw. Sci. Eng. (2018, in press). https://doi.org/10.1109/TNSE.2018.2830307
Kurs, A., Karalis, A., Moffatt, R., et al.: Wireless power transfer via strongly coupled magnetic resonances. Science 317(5834), 83–86 (2007)
Jiang, G., Lam, S., Sun, Y., et al.: Joint charging tour planning and depot positioning for wireless sensor networks using mobile chargers. IEEE/ACM Trans. Netw. 25(4), 2250–2266 (2017)
Ma, Z., Wu, J., Zhang, S., et al.: Prolonging WSN lifetime with an actual charging model. In: 2018 IEEE Wireless Communications and Networking Conference (WCNC), Barcelona, Spain, pp. 1–6, April 2018
Wei, Z., Liu, F., Lyu, Z., Ding, X., Shi, L., Xia, C.: Reinforcement learning for a novel mobile charging strategy in wireless rechargeable sensor networks. In: Chellappan, S., Cheng, W., Li, W. (eds.) WASA 2018. LNCS, vol. 10874, pp. 485–496. Springer, Cham (2018). https://doi.org/10.1007/978-3-319-94268-1_40
Shi, Y., Xie, L., Hou, Y.T., et al.: On renewable sensor networks with wireless energy transfer. In: Proceedings of IEEE INFOCOM 2011, Shanghai, China, pp. 1350–1358 (2011)
Xie, L., Shi, Y., Hou, Y.T., et al.: Bundling mobile base station and wireless energy transfer: modeling and optimization. In: Proceedings of IEEE INFOCOM 2013, Turin, Italy, pp. 1636–1644 (2013)
Xu, W., Liang, W., Ren, X., et al.: On-demand energy replenishment for sensor networks via wireless energy transfer. In: 2014 IEEE 25th Annual International Symposium on Personal, Indoor, and Mobile Radio Communication (PIMRC), Washington, DC, USA, pp. 1269–1273 (2014)
Ding, X., Han, J., Shi, L.: The optimization based dynamic and cyclic working strategies for rechargeable wireless sensor networks with multiple base stations and wireless energy transfer devices. Sensors 15(3), 6270–6305 (2015)
Xu, J., Yuan, X., Wei, Z., et al.: A wireless sensor network recharging strategy by balancing lifespan of sensor nodes. In: 2017 IEEE Wireless Communications and Networking Conference (WCNC), San Francisco, CA, USA, pp. 1–6 (2017)
Guo, S., Wang, C., Yang, Y.: Joint mobile data gathering and energy provisioning in wireless rechargeable sensor networks. IEEE Trans. Mob. Comput. 13(12), 2836–2852 (2014)
Chang, H., Feng, J., Duan, C., et al.: Research of recharging scheduling scheme for wireless sensor networks based on cuckoo search. In: 2018 International Joint Conference on Neural Networks (IJCNN), Rio de Janeiro, Brazil, pp. 1–7 (2018)
Wei, Z., Liu, F., Ding, X., et al.: K-CHRA: a clustering hierarchical routing algorithm for wireless rechargeable sensor networks. IEEE Access (2018, in press). https://doi.org/10.1109/ACCESS.2018.2885789
Acknowledgment
This research was funded by the National Key Research Development Program of China [No. 2016YFC0801800] and the Nation Nature Science Foundation of China [No. 61806067, No. 61701162].
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2019 Springer Nature Switzerland AG
About this paper
Cite this paper
Xu, J., Xu, X., Ding, X., Shi, L., Lu, Y. (2019). Cross-Layer Optimization on Charging Strategy for Wireless Sensor Networks Based on Successive Interference Cancellation. In: Biagioni, E., Zheng, Y., Cheng, S. (eds) Wireless Algorithms, Systems, and Applications. WASA 2019. Lecture Notes in Computer Science(), vol 11604. Springer, Cham. https://doi.org/10.1007/978-3-030-23597-0_31
Download citation
DOI: https://doi.org/10.1007/978-3-030-23597-0_31
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-030-23596-3
Online ISBN: 978-3-030-23597-0
eBook Packages: Computer ScienceComputer Science (R0)