Dynamic Spectrum Allocation and RF Energy Harvesting in Cognitive Radio Network

  • Pallavi ShetkarEmail author
  • Sushil Ronghe
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 898)


RF energy harvesting (EH) is a new paradigm constituted by the wireless sensor network which enables it to recharge through the directed electromagnetic energy transfer. In a practical scenario, secondary users (SUs) are unacquainted with the traffic statistics of primary users (PUs). Thus, maximizing bandwidth utilization is one of the objectives of this paper. In order to obtain reasonably accurate estimations of spectrum opportunities (channels), the modified myopic scheme is implemented in this paper. In addition, energy detection algorithm is implemented for spectrum sensing. A scheme which proficiently executes channel selection, channel allocation and energy harvesting for the system model of multiple PUs and SUs in cognitive radio network (CRN) is also proposed in this paperwork. The outcome of the paper proves that the proposed scheme maintains a satisfactory balance between accessing the spectrum and harvesting energy while maintaining the fairness among SUs.


Cognitive radio network Channel selection Spectrum sensing Spectrum allocation RF energy harvesting 


  1. 1.
    Andrews, J.G., Buzzi, S., Choi, W., Hanly, S.V., Lozano, A., Soong, A.C., Zhang, J.C.: What will 5G be? IEEE J. Sel. Areas Commun. 32(6), 1065–1082 (2014)CrossRefGoogle Scholar
  2. 2.
    Jacob, P., Sirigina, R.P., Madhukumar, A.S., Prasad, V.A.: Cognitive radio for aeronautical communications: a survey. IEEE Access 4, 3417–3443 (2016)CrossRefGoogle Scholar
  3. 3.
    Bhardwaj, P., Panwar, A., Ozdemir, O., Masazade, E., Kasperovich, I., Drozd, A.L., Varshney, P.K.: Enhanced dynamic spectrum access in multiband cognitive radio networks via optimized resource allocation. IEEE Trans. Wireless Commun. 15(12), 8093–8106 (2016)CrossRefGoogle Scholar
  4. 4.
    Rastegardoost, N., Jabbari, B.: On channel selection schemes for spectrum sensing in cognitive radio networks. In: Wireless Communications and Networking Conference (WCNC), pp. 955–959. IEEE (2015)Google Scholar
  5. 5.
    Ronghe, S.B., Kulkarni, V.P.: Modelling and performance analysis of RF energy harvesting cognitive radio networks. In: International Conference on Communication and Electronics Systems (ICCES), pp. 1–6. IEEE (2016)Google Scholar
  6. 6.
    Ali Ahmad, H., Liu, M., Javidi, T., Zhao, Q., Krishnamachari, B.: Optimality of myopic sensing in multichannel opportunistic access. IEEE Trans. Inf. Theory 55(9) (2009)MathSciNetCrossRefGoogle Scholar
  7. 7.
    Lu, X., Wang, P., Niyato, D., Kim, D.I., Han, Z.: Wireless networks with RF energy harvesting: a contemporary survey. IEEE Commun. Surv. Tutor. 17(2), 757–789 (2015)CrossRefGoogle Scholar
  8. 8.
    Chalasani, S., Conrad, J.M.: A survey of energy harvesting sources for embedded systems. In: Southeastcon, 2008, pp. 442–447. IEEE (2008)Google Scholar
  9. 9.
    Zhang, W., Mallik, R.K., Letaief, K.B.: Optimization of cooperative spectrum sensing with energy detection in cognitive radio networks. IEEE Trans. Wireless Commun. 8(12) (2009)CrossRefGoogle Scholar
  10. 10.
    Cabric, D., Tkachenko, A., Brodersen, R.W.: Experimental study of spectrum sensing based on energy detection and network cooperation. In: First International Workshop on Technology and Policy for Accessing Spectrum, p. 12 (2006)Google Scholar
  11. 11.
    Jones, S.D., Merheb, N., Wang, I.J.: An experiment for sensing-based opportunistic spectrum access in CSMA/CA networks. In: New Frontiers in Dynamic Spectrum Access Networks, 2005. DySPAN 2005, pp. 593–596. IEEE (2005)Google Scholar

Copyright information

© Springer Nature Singapore Pte Ltd. 2019

Authors and Affiliations

  1. 1.College of Engineering, PunePuneIndia

Personalised recommendations