Abstract
Energy harvesting based cognitive machine-to-machine (EH-CM2M) communication has been introduced to overcome the problem of spectrum scarcity and limited battery capacity by enabling M2M transmitters (M2M-TXs) to harvest energy from ambient radio frequency signals, as well as to reuse the resource blocks (RBs) allocated to CUs in an opportunistic manner. However, the complex interference scenarios and the stringent QoS requirements pose new challenges on resource allocation optimization. In this chapter, we consider how to maximize the energy efficiency of M2M-TXs via the joint optimization of channel selection, peer discovery, power control, and time allocation.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Feng, D., Lu, L., Yi, Y., Li, G.Y., Feng, G., Li, S.: Device-to-device communications underlaying cellular networks. IEEE Trans. Commun. 61(8), 3541–3551 (2013)
Joda, R., Lahouti, F., Erkip, E.: Distortion-power tradeoffs in quasi-stationary source transmission over delay and buffer limited block fading channels. IEEE Trans. Wireless Commun. 15(7), 4505–4520 (2016)
Ha, T., Kim, J., Chung, J.: HE-MAC: Harvest-then-transmit based modified EDCF MAC protocol for wireless powered sensor networks. IEEE Trans. Wireless Commun. 17(1), 3–16 (2018)
Saleem, U., Jangsher, S., Qureshi , H., Hassan, S.: Joint subcarrier and power allocation in the energy-harvesting-aided D2D communication. IEEE Trans. Ind. Inf. 14(6), 2608–2617 (2018)
Shih, M.j., Lin, G.Y., Wei, H.Y.: Two paradigms in cellular Internet-of-Things access for energy-harvesting machine-to-machine devices: push-based versus pull-based. IET Wireless Sensor Syst. 6(4), 121–129 (2016)
Wang, H., Ding, G., Wang, J., Wang, L., Taiftsis, T.A., Sharma, P.K.: Resource allocation for energy harvesting-powered D2D communications underlaying cellular networks. In: Proceedings of IEEE International Conference on Communications, Paris, May 2017
Zeng, M., Luo, Y., Guo, Q., Jiang, H.: Power allocation for energy harvesting-based D2D communication underlaying cellular network. In: Proceedings of Chinese Control Conference, Dalian, July 2017
Aijaz, A., Tshangini, M., Nakhai, M.R., Chu, X. Aghvami, A.: Energy-efficient uplink resource allocation in LTE networks with M2M/H2H co-existence under statistical QoS guarantees. IEEE Trans. Commun. 62(7), 2353–2365 (2014)
Ghavimi, F., Lu, Y., Chen, H.: Uplink scheduling and power allocation for M2M communications in SC-FDMA-based LTE-A networks with QoS guarantees. IEEE Trans. Veh. Technol. 66(7), 6160–6170 (2017)
Zhou, Z., Xiong, F., Xu, C., He, Y., Mumtaz, S.: Energy-efficient vehicular heterogeneous networks for green cities. IEEE Trans. Ind. Informat. 14(4), 1522–1531 (2018)
Luo, Y., Hong, P., Su, R., Xue, K.: Resource allocation for energy harvesting-powered D2D communication underlaying cellular networks. IEEE Trans. Veh. Technol. 66(11), 10486–10498 (2017)
Li, S., Ni, Q., Sun, Y., Min, G., Rubaye, S.A.: Energy-efficient resource allocation for industrial cyber-physical IoT systems in 5G era. IEEE Trans. Ind. Inf. 14(6), 2618–2628 (2018)
Trakhtenbrot, B.A.: A survey of Russian approaches to perebor (brute-force serches) algorithms. Ann. History Comput. 6(4), 121–129 (1984)
Zhou, Z., Guo, Y., He, Y., Zhao, X., Bazzi, W.M.: Access control and resource allocation for M2M communications in industrial automation. IEEE Tran. Ind. Inf. 15(5), 3093–3103 (2019)
Xu, W., Zhou, X., Lee, C., Feng, Z., Lin, J.: Energy-efficient joint sensing duration, detection threshold, and power allocation optimization in cognitive OFDM systems. IEEE Tran. Wireless Commun. 15(12), 8339–8352 (2016)
Sentelle, C., Anagnostopoulos, G.C., Georgiopoulos, M.: Efficient revised simplex method for SVM training. IEEE Trans. Neural Netw. 22(10), 1650–1661 (2011)
Zhou, Z., Ota, K., Dong, M., Xu, C.: Energy-efficient matching for resource allocation in D2D enabled cellular networks. IEEE Trans. Veh. Technol. 66(6), 5256–5268 (2017)
Pei, L., Yang, Z., Pan, C., Huang, W., Chen, M., Elkashlan, M., Nallanathan, A.: Energy-efficient D2D communications underlaying NOMA-based networks with energy harvesting. IEEE Commun. Lett. 22(5), 914–917 (2018)
Zhou, Z., Feng, J., Gu, B., Ai, B., Mumtaz, S., Rodriguez, J., Guizani, M.: When mobile crowd sensing meets UAV: energy-efficient task assignment and route planning. IEEE Trans. Commun. 66(11), 5526–5538 (2018)
Author information
Authors and Affiliations
Rights and permissions
Copyright information
© 2021 Springer Nature Switzerland AG
About this chapter
Cite this chapter
Zhou, Z., Chang, Z., Liao, H. (2021). Energy Harvesting Enabled Energy Efficient Cognitive Machine-to-Machine Communications. In: Green Internet of Things (IoT): Energy Efficiency Perspective. Wireless Networks. Springer, Cham. https://doi.org/10.1007/978-3-030-64054-5_3
Download citation
DOI: https://doi.org/10.1007/978-3-030-64054-5_3
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-030-64053-8
Online ISBN: 978-3-030-64054-5
eBook Packages: Computer ScienceComputer Science (R0)