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RF-Based Energy Harvesting Cognitive Cellular Networks

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Handbook of Cognitive Radio
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Abstract

Recently, fundamental research has demonstrated great potentials of integrating radio frequency (RF) energy harvesting techniques into cognitive cellular networks (CCNs). Such an integration can improve spectrum utilization and energy efficiency of wireless communication services. In CCNs with RF energy harvesting capability, when cellular base stations, i.e., primary transmitters, transmit signals to their mobile devices, secondary users (SUs) can harvest energy from the cellular channel, i.e., the primary channel, and store the energy in their batteries. Then, when the cellular channel becomes idle, the SUs can use the harvested energy to transmit data to their receivers. As such, we can utilize not only the available spectrum when the channel is idle but also energy scavenging when the channel is busy. This chapter first presents an overview of RF-based energy harvesting CCNs. Then, limitations are discussed, and some new solutions using ambient backscattering communication techniques are introduced to overcome the limitations. Finally, the chapter concludes with a discussion on the development of such networks and possible research directions.

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References

  1. Maxwell JC (eds) (1881) A treatise on electricity and magnetism. Oxford, Clarendon

    MATH  Google Scholar 

  2. Ladan S, Ghassemi N, Ghiotto A, Wu K (2013) Highly efficient compact rectenna for wireless energy harvesting application. IEEE Microw Mag 14(1):117–122

    Article  Google Scholar 

  3. Kuhn V, Lahuec C, Seguin F, Person C (2015) A multi-band stacked RF energy harvester with RF-to-DC efficiency up to 84%. IEEE Trans Microw Theory Tech 63(5):1768–1778

    Article  Google Scholar 

  4. Balanis CA (eds) (2012) Antenna theory: analysis and design. New York

    Google Scholar 

  5. Rappaport TS (eds) (2001) Wireless communications: principles and practice. Upper Saddle River

    MATH  Google Scholar 

  6. Lee S, Zhang R, Huang K (2013) Opportunistic wireless energy harvesting in cognitive radio networks. IEEE Trans Wirel Commun 12(9):4788–4799

    Article  Google Scholar 

  7. Yao Y, Song X, Yin C, Huang S (2015) Opportunistic energy harvesting and energy-based opportunistic spectrum access in cognitive radio networks. In: International Conference on Cognitive Radio Oriented Wireless Networks. Springer International Publishing, pp 187–198

    Google Scholar 

  8. Park S, Heo J, Kim B, Chung W (2012) Optimal mode selection for cognitive radio sensor networks with RF energy harvesting. In: IEEE International Symposium on Personal Indoor and Mobile Radio Communications, Sydney, pp 2155–2159

    Google Scholar 

  9. Park S, Kim H, Hong D (2013) Cognitive radio networks with energy harvesting. IEEE Trans Wirel Commun 12(3):1386–1397

    Article  Google Scholar 

  10. Park S, Hong D (2014) Achievable throughput of energy harvesting cognitive radio networks. IEEE Trans Wirel Commun 13(2):1010–1022

    Article  MathSciNet  Google Scholar 

  11. Park S, Hong D (2013) Optimal spectrum access for energy harvesting cognitive radio networks. IEEE Trans Wirel Commun 12(12):6166–6179

    Article  Google Scholar 

  12. Rakovic V, Denkovski D, Hadzi-Velkov Z, Gavrilovska L (2015) Optimal time sharing in underlay cognitive radio systems with RF energy harvesting. In: IEEE International Conference on Communications, London, pp 7689–7694

    Google Scholar 

  13. Ju H, Zhang R (2014) Throughput maximization in wireless powered communication networks. IEEE Trans Wirel Commun 13(1):418–428

    Article  Google Scholar 

  14. Yin S, Zhang E, Qu Z, Yin L, Li S (2014) Optimal cooperation strategy in cognitive radio systems with energy harvesting. IEEE Trans Wirel Commun 13(9):4693–4707

    Article  Google Scholar 

  15. Li D, Yin S, Li S (2013) One-step-ahead spectrum sensing in cognitive radio systems with wireless energy harvesting. In: IEEE Global High Tech Congress on Electronics, Shenzhen, pp 130–134

    Google Scholar 

  16. Yin S, Zhang E, Yin L, Li S (2013) Optimal saving-sensing-transmitting structure in self-powered cognitive radio systems with wireless energy harvesting. In: IEEE International Conference Communications, Budapest, pp 2807–2811

    Google Scholar 

  17. Lu X, Xu W, Li S, Lin J, He Z (2014) Simultaneous information and power transfer for relay-assisted cognitive radio networks. In: IEEE International Conference on Communications Workshops, Sydney, pp 331–336

    Google Scholar 

  18. Mousavifar SA, Liu Y, Leung C, Elkashlan M, Duong TQ (2014) Wireless energy harvesting and spectrum sharing in cognitive radio. In: IEEE 80th Vehicular Technology Conference, Vancouver, pp 1–5

    Google Scholar 

  19. Yang Z, Ding Z, Fan P, Karagiannidis GK (2016) Outage performance of cognitive relay networks with wireless information and power transfer. IEEE Trans Veh Technol 65(5): 3828–3833

    Article  Google Scholar 

  20. Wang Z, Chen Z, Yao Y, Xia B, Liu H (2014) Wireless energy harvesting and information transfer in cognitive two-way relay networks. In: IEEE Global Communications Conference, Austin, pp 3465–3470

    Google Scholar 

  21. Wang Z, Chen Z, Luo L, Hu Z, Xia B, Liu H (2014) Outage analysis of cognitive relay networks with energy harvesting and information transfer. In: IEEE International Conference on Communications, Sydney, pp 4348–4353

    Google Scholar 

  22. Zheng G, Ho Z, Jorswieck EA, Ottersten B (2014) Information and energy cooperation in cognitive radio networks. IEEE Trans Signal Process 62(9):2290–2303

    Article  MathSciNet  Google Scholar 

  23. Gao Q, Jing T, Xing X, Cheng X, Huo Y, Chen D (2015) Simultaneous energy and information cooperation in MIMO cooperative cognitive radio systems. In: IEEE Wireless Communications and Networking Conference, New Orleans, pp 351–356

    Google Scholar 

  24. Li B, Xu W, Gao X (2015) Energy-efficient simultaneous information and power transfer in OFDM-based CRNS. In: IEEE Vehicular Technology Conference, Glasgow, pp 11–14

    Google Scholar 

  25. Shafie AE, Ashour M, Khattab T, Mohamed A (2015) On spectrum sharing between energy harvesting cognitive radio users and primary users. In: International Conference on Computing, Networking and Communications, California, pp 214–220

    Google Scholar 

  26. Sibomana L, Zepernick H-J, Tran H (2015) Wireless information and power transfer in an underlay cognitive radio network. In: International Conference on Signal Processing and Communication Systems, Cairns, pp 1–7

    Google Scholar 

  27. Gesbert D, Alouini MS (2004) How much feedback is multi-user diversity really worth? In: IEEE International Conference on Communications, Paris, pp 234–238

    Google Scholar 

  28. Ng DWK, Lo ES, Schober R (2016) Multi-objective resource allocation for secure communication in cognitive radio networks with wireless information and power transfer. IEEE Trans Veh Technol 65(5):3166–3184

    Article  Google Scholar 

  29. Hoang DT, Niyato D, Wang P, Kim DI (2014) Opportunistic channel access and RF energy harvesting in cognitive radio networks. IEEE J Sel Areas Commun 32(11):2039–2052

    Article  Google Scholar 

  30. Hoang DT, Niyato D, Wang P, Kim DI (2015) Performance optimization for cooperative multiuser cognitive radio networks with RF energy harvesting capability. IEEE Trans Wirel Commun 14(7):3614–3629

    Article  Google Scholar 

  31. Tse D, Viswanath P (eds) (2005) Fundamentals of wireless communication. Cambridge University Press, Cambridge

    MATH  Google Scholar 

  32. Liu V, Parks A, Talla V, Gollakota S, Wetherall D, Smith JR (2013) Ambient backscatter: wireless communication out of thin air. In: Proceedings of the ACM SIGCOMM, Hong Kong, pp 39–50

    Google Scholar 

  33. Dunne C (2013) Ambient backscatter: brings us closer to an internet of things. http://www.fastcodesign.com/3017570/ambient-backscatter-brings-us-closer-to-an-internet-of-things

  34. Parks AN, Liu A, Gollakota S, Smith JS (2014) Turbocharging ambient backscatter communication. ACM SIGCOMM Comput Commun Rev 44(4):619–630

    Article  Google Scholar 

  35. Penichet CP, Varshney A, Hermans F, Rohner C, Voigt T (2016) Do multiple bits per symbol increase the throughput of ambient backscatter communications? In: Proceedings of the International Conference on Embedded Wireless Systems and Networks, TU Graz, pp 355–360

    Google Scholar 

  36. You J, Wang G, Zhong Z (2015) Physical layer security-enhancing transmission protocol against eavesdropping for ambient backscatter communication system. In: 6th International Conference on Wireless, Mobile and Multi-Media, Beijing, pp 43–47

    Google Scholar 

  37. Lu K, Wang G, Qu F, Zhong Z (2015) Signal detection and BER analysis for RF-powered devices utilizing ambient backscatter. In: International Conference on Wireless Communications & Signal Processing, Nanjing, pp 1–5

    Google Scholar 

  38. Zhang P, Ganesan D (2014) Enabling bit-by-bit backscatter communication in severe energy harvesting environments. In: Proceedings of the 11th USENIX Conference on Networked Systems Design and Implementation, pp 345–357

    Google Scholar 

  39. Hoang DT, Niyato D, Wang P, Kim DI, Han Z (2016) The tradeoff analysis in RF-powered backscatter cognitive radio networks. In: IEEE GLOBECOM, Washington DC

    Google Scholar 

  40. Huang H, Lau VKN (2012) Decentralized delay optimal control for interference networks with limited renewable energy storage. IEEE Trans Sig Process 60(5):2552–2561

    Article  MathSciNet  Google Scholar 

  41. Kim DY, Kim DI (2010) Reverse-link interrogation range of a UHF MIMO-RFID system in Nakagami-m fading channels. IEEE Trans Ind Electron 57(4):1468–1477

    Article  Google Scholar 

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Correspondence to Dinh Thai Hoang .

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Hoang, D.T., Niyato, D. (2019). RF-Based Energy Harvesting Cognitive Cellular Networks. In: Zhang, W. (eds) Handbook of Cognitive Radio . Springer, Singapore. https://doi.org/10.1007/978-981-10-1394-2_34

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