Journal of Communications and Networks

The Korean Institute of Commucations and Information Sciences (한국통신학회)
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Increasing Throughput in Energy-Based Opportunistic Spectrum Access Energy Harvesting Cognitive Radio Networks

  • Yao, Yuanyuan (Beijing Key Laboratory of Network System Architecture and Convergence, Beijing University of Posts and Telecommunications) ;
  • Yin, Changchuan (Beijing Key Laboratory of Network System Architecture and Convergence, Beijing University of Posts and Telecommunications) ;
  • Song, Xiaoshi (school of Information Science and Engineering, Northeastern University) ;
  • Beaulieu, Norman C. (Beijing Key Laboratory of Network System Architecture and Convergence, Beijing University of Posts and Telecommunications)
  • Received : 2015.01.20
  • Accepted : 2015.10.15
  • Published : 2016.06.30
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Abstract

The performance of large-scale cognitive radio (CR) networks with secondary users sustained by opportunistically harvesting radio-frequency (RF) energy from nearby primary transmissions is investigated. Using an advanced RF energy harvester, a secondary user is assumed to be able to collect ambient primary RF energy as long as it lies inside the harvesting zone of an active primary transmitter (PT). A variable power (VP) transmission mode is proposed, and an energy-based opportunistic spectrum access (OSA) strategy is considered, under which a secondary transmitter (ST) is allowed to transmit only if its harvested energy is larger than a predefined transmission threshold and it is outside the guard zones of all active PTs. The transmission probability of the STs is derived. The outage probabilities and the throughputs of the primary and the secondary networks, respectively, are characterized. Compared with prior work, the throughput can be increased by as much as 29%. The energy-based OSA strategy can be generally applied to a non-CR setup, where distributed power beacons (PBs) are deployed to power coexisting wireless signal transmitters (WSTs) in a wireless powered sensor network.

Keywords

Acknowledgement

Supported by : NSFC, National Research Foundation

References

  1. H. Kim, S.-R. Lee, C. Song, and I. Lee, "Optimal power allocation for energy efficiency maximization in distributed antenna systems," in Proc. IEEE ICC, Budapest, Hungary, June 2013.
  2. A. Sinha and A. Chandrakasan, "Dynamic power management in wireless sensor networks," IEEE Design Test Comp., vol. 18, no. 2, pp. 62-74, Mar.-Apr. 2001. https://doi.org/10.1109/54.914626
  3. D. Bouchouicha, F. Dupont, M. Latrach, and L. Ventura, "Ambient RF energy harvesting," in Proc. ICREPQ, Mar. 2010.
  4. A. M. Zungeru, L. M. Ang, S. Prabaharan, and K. P. Seng, "Radio frequency energy harvesting and management for wireless sensor networks," in Green Mobile Devices and Netw.: Energy Opt. Scav. Tech., CRC Press, pp. 341-368, 2012.
  5. T. Le, K.Mayaram, and T. Fiez, "Efficient far-field radio frequency energy harvesting for passively powered sensor networks," IEEE J. Solid-State Circuits, vol. 43, no. 5, pp. 1287-1302, May 2008. https://doi.org/10.1109/JSSC.2008.920318
  6. I. Flint, X. Lu, N. Privault, D. Niyato, and P.Wang, "Performance analysis of ambient RF energy harvesting: A stochastic geometry approach," in Proc. IEEE GLOBECOM, Austin, TX, USA, Dec. 2014.
  7. R. J. M. Vullers, R. V. Schaijk, I. Doms, C. V. Hoof, and R. Mertens, "Micropower energy harvesting," Elsevier Solid-State Circuits, vol. 53, no. 7, pp. 684-693, July 2009.
  8. D. Stoyan, W. Kendall, and J. Mecke, Stochastic Geometry and Its Applications, 2nd ed. John Wiley and Sons, 1996.
  9. F. Baccelli and B. Blaszczyszyn, Stochastic Geometry and Wireless Networks. NOW: Foundations and Trends in Networking, 2010.
  10. K. Huang, "Spatial throughput of mobile ad hoc networks powered by energy harvesting," IEEE Trans. Inf. Theory, vol. 59, no. 11, pp. 7597- 7612, Nov. 2013. https://doi.org/10.1109/TIT.2013.2276811
  11. K. Huang and V. K. N. Lau, "Enabling wireless power transfer in cellular networks: Architecture, modeling, and deployment," IEEE Trans. Wireless Commun., vol. 13, no. 2, pp. 902-912, Feb. 2014. https://doi.org/10.1109/TWC.2013.122313.130727
  12. H. Dhillon, Y. Li, P. Nuggehalli, Z. Pi, and J. Andrews, "Fundamentals of heterogeneous cellular networks with energy harvesting," IEEE Trans. Wireless Commun., vol. 13, no. 5, pp. 2782-2797, May 2014. https://doi.org/10.1109/TWC.2014.040214.131201
  13. S. Haykin, "Cognitive radio: Brain-empowered wireless communications," IEEE J. Sel. Areas Commun., vol. 23, no. 2, pp. 201-220, Feb. 2005. https://doi.org/10.1109/JSAC.2004.839380
  14. K. J. Kim, K. S. Kwak, and B. D. Choi, "Performance analysis of opportunistic spectrum access protocol for multi-channel cognitive radio networks," J. Commun. and Netw., vol. 15, no. 1, pp. 77-86, Feb. 2013. https://doi.org/10.1109/JCN.2013.000013
  15. J. F. C. Kingman, Poisson Processes. Oxford University Press, 1993.
  16. D. Daley and D. V. Jones, An Introduction to the Theory of Point Processes. Springer, 1988.
  17. C. H. Lee and M. Haenggi, "Interference and outage in Poisson cognitive networks," IEEE Trans. Wireless Commun., vol. 11, no. 4, pp. 1392-1401, Apr. 2012. https://doi.org/10.1109/TWC.2012.021512.110131
  18. X. Song, C. Yin, D. Liu, and R. Zhang, "Spatial throughput characterization in cognitive radio networks with threshold-based opportunistic spectrum access," IEEE J. Sel. Areas Commun., vol. 32, no. 11, Nov. 2014.
  19. L. Xiao, P. Wang, D. Niyato, and E. Hossain, "Dynamic spectrum access in cognitive radio networks with RF energy harvesting," IEEE Wireless Commun., vol. 21, no. 3, pp. 102-110, June 2014. https://doi.org/10.1109/MWC.2014.6845054
  20. N. Pappas, J. Jeon, A. Ephremides, and A. Traganitis, "Optimal utilization of a cognitive shared channel with a rechargeable primary source node," J. Commun. Netw., vol. 14, no. 2, pp. 162-168, Apr. 2012. https://doi.org/10.1109/JCN.2012.6253064
  21. S. Park, H. Kim, and D. Hong, "Cognitive radio networks with energy harvesting," IEEE Trans. Wireless Commun., vol. 12, no. 3, pp. 1386- 1397, Mar. 2013. https://doi.org/10.1109/TWC.2013.012413.121009
  22. S. Yin, Z. Qu, and S. Li, "Optimal multi-slot spectrum sensing in energy harvesting cognitive radio systems," in Proc. IEEE GLOBECOM, Dec. 2014.
  23. S. Lee, R. Zhang, and K. Huang, "Opportunistic wireless energy harvesting in cognitive radio networks," IEEE Trans. Wireless Commun., vol. 12, no. 9, pp. 4788-4799, Sept. 2013. https://doi.org/10.1109/TWC.2013.072613.130323
  24. A. Hasan and J. Andrews, "The guard zone in wireless ad hoc networks," IEEE Trans. Wireless Commun., vol. 6, no. 3, pp. 897-906, Mar. 2007. https://doi.org/10.1109/TWC.2007.04793
  25. M. Haenggi and R. K. Ganti, "Interference in large wireless networks," Found. Trends in Netw., NOWPublishers, vol. 3, no. 2, pp. 127-248, 2008. https://doi.org/10.1561/1300000015
  26. M. Haenggi, J. Andrews, F. Baccelli, O. Dousse, and M. Franceschetti, "Stochastic geometry and random graphs for the analysis and design of wireless networks," IEEE J. Sel. Areas Commun., vol. 27, no. 7, pp. 1029-1046, Sept. 2009. https://doi.org/10.1109/JSAC.2009.090902