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Cognitive radio resource management exploiting heterogeneous primary users and a radio environment map database

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Abstract

The efficient utilization of radio resources is a fundamental issue in cognitive radio (CR) networks. Thus, a novel cognitive radio resource management (RRM) is proposed to improve the spectrum utilization efficiency. An optimization framework for RRM is developed that makes the following contributions: (i) considering heterogeneous primary users (PUs) with multiple features stored in a radio environment map database, (ii) allowing variable CR demands, (iii) assuring interference protection towards PUs. After showing that the optimal solution is computationally infeasible, a suboptimal solution is consequently proposed. Performance evaluation is conducted in terms of total achieved data rate and satisfaction of CR requirements.

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References

  1. Akyildiz, I. F., Lee, W. -Y., Vuran, M. C., & Mohanty S. (2006). Next generation/dynamic spectrum access/cognitive radio wireless networks: A survey. Computer Networks 50(13), 2127–2215.

    Article  MATH  Google Scholar 

  2. Canberk, B., Akyildiz, I. F., & Oktug, S. (2011). Primary user activity modeling using first-difference filter clustering and correlation in cognitive radio networks. IEEE/ACM Transactions on Networking, 19(1), 170–183.

    Article  Google Scholar 

  3. Fitzek, F. H. P., & Reisslein, M. (2001). MPEG-4 and H.263 video traces for network performance evaluation. IEEE Network, 15(6), 40–54.

    Article  Google Scholar 

  4. Hou, Y. T., Shi, Y., & Sherali, H. D. (2008). Spectrum sharing for multi-hop networking with cognitive radios. IEEE Journal on Selected Areas in Communications, 26(1), 146–155.

    Article  Google Scholar 

  5. Hu, D., & He, L. (2010). Pilot design for channel estimation in OFDM-based cognitive radio systems. IEEE International Conference on Communications, ICC 2010, pp. 1–5.

  6. Iyengar, R., Kar, K., & Sikdar, B. (2006). Scheduling algorithms for PMP operation in IEEE 802.16 networks. RAWNET 2006 workshop, in Conjunction with WiOPT 06, Boston, MA.

  7. McHenry, M., & McCloskey, D. (2004). New York City spectrum occupancy measurements September 2004.

  8. Mohanram, C., & Bhashyam, S. (2005). A sub-optimal joint subcarrier and power allocation algorithm for multiuser OFDM. IEEE Communications Letters, 9(8), 685–687.

    Article  Google Scholar 

  9. Petrova, M., & Mahonen, P. (2007). Cognitive resource manager: a cross-layer architecture for implementing cognitive radio networks. In: F. Fittzek, & M. Katz (Eds.), Cognitive wireless networks. Berlin: Springer.

    Google Scholar 

  10. van de Beek, J., Cai, T., Grimoud, S., Mhnen, P., Nasreddine, J., Riihijrvi, J., et al. (2012). How a layered REM architecture brings cognition to today’s mobile networks. IEEE Wireless Communication Magazine, 19(4), 17–24.

    Google Scholar 

  11. Vizziello, A., Akyildiz, I. F., Agusti, R., Favalli, L., & Savazzi, P. (2010). OFDM signal type recognition and adaptability effects in cognitive radio networks. In Proceedings of the IEEE GLOBECOM 2010. Miami, Florida, USA.

  12. Vizziello, A., & Perez-Romero, J. (2011). System architecture in cognitive radio networks using a radio environment map. In Proceedigs of the CogART 2011, (invited paper). Barcelona, Spain.

  13. Vizziello, A., Akyildiz, I. F., Agusti, R., Favalli, L., & Savazzi, P. (2011). Cognitive radio resource management exploiting heterogeneous primary users. In Proceedings of the IEEE GLOBECOM 2011. Houston, Texas, USA.

  14. Wang, B., & Liu, K. J. R. (Feb. 2011). Advances in cognitive radio networks: A survey. IEEE Journal of Selected Topics in Signal Processing, 5(1), 5–23.

    Article  Google Scholar 

  15. Zhao, Y., Morales, L., Gaeddert, J., Bae, K., Um, J. -S., & Reed, J. (2007). Applying radio environment maps to cognitive wireless regional area networks. In Proceedings of the IEEE DySPAN 2007. pp. 115–118.

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Correspondence to Anna Vizziello.

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The work of Ian F. Akyildiz and Ramon Agustí was supported by the European Commission in the framework of the FP7 FARAMIR Project (Ref. ICT- 248351).

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Vizziello, A., Akyildiz, I.F., Agustí, R. et al. Cognitive radio resource management exploiting heterogeneous primary users and a radio environment map database. Wireless Netw 19, 1203–1216 (2013). https://doi.org/10.1007/s11276-012-0528-y

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