KSII Transactions on Internet and Information Systems (TIIS)

Korean Society for Internet Information (한국인터넷정보학회)
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Capacity of Spectrum Sharing Cognitive Radio with MRC Diversity under Delay Quality-of-Service Constraints in Nakagami Fading Environments

  • Zhang, Ping (Key Laboratory of Universal Wireless Communications, Ministry of Education Beijing University of Posts and Telecommunications) ;
  • Xu, Ding (Key Laboratory of Universal Wireless Communications, Ministry of Education Beijing University of Posts and Telecommunications) ;
  • Feng, Zhiyong (Key Laboratory of Universal Wireless Communications, Ministry of Education Beijing University of Posts and Telecommunications)
  • Received : 2012.06.12
  • Accepted : 2013.04.02
  • Published : 2013.04.30
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Abstract

The paper considers a spectrum sharing cognitive radio (CR) network coexisting with a primary network under the average interference power constraint. In particular, the secondary user (SU) is assumed to carry delay-sensitive services and thus shall satisfy a given delay quality-of-service (QoS) constraint. The secondary receiver is also assumed to be equipped with multiple antennas to perform maximal ratio combining (MRC) to enhance SU performance. We investigate the effective capacity of the SU with MRC diversity under aforementioned constraints in Nakagami fading environments. Particularly, we derive the optimal power allocation to achieve the maximum effective capacity of the SU, and further derive the effective capacity in closed-form. In addition, we further obtain the closed-form expressions for the effective capacities under three widely used power and rate adaptive transmission schemes, namely, optimal simultaneous power and rate adaptation (opra), truncated channel inversion with fixed rate (tifr) and channel inversion with fixed rate without truncation (cifr). Numerical results supported by simulations are presented to consolidate our studies. The impacts on the effective capacity of various system parameters such as the number of antennas, the average interference power constraint and the delay QoS constraint are investigated in detail. It is shown that MRC diversity can significantly improve the effective capacity of the SU especially for cifr transmission scheme.

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References

  1. 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
  2. R. Zhang, "On peak versus average interference power constraints for protecting primary users in cognitive radio networks," IEEE Trans. Wireless Commun., vol. 8, no. 4, pp. 2112-2120, Apr. 2009. https://doi.org/10.1109/TWC.2009.080714
  3. D. Wu and R. Negi, "Effective capacity: a wireless link model for support of quality of service," IEEE Trans. Wireless Commun., vol. 2, no. 4, 2003.
  4. L. Musavian and S. Aissa, "Quality-of-service based power allocation in spectrum-sharing channels," in Proc. of IEEE Global Telecommunications Conference (GLOBECOM), Dec. 2008, pp. 1-5.
  5. L. Musavian and S. Aissa, "Effective capacity of delay-constrained cognitive radio in nakagami fading channels," IEEE Trans. Wireless Commun., vol. 9, no. 3, pp. 1054-1062, Mar. 2010. https://doi.org/10.1109/TWC.2010.03.081253
  6. S. Akin and M. Gursoy, "Effective capacity analysis of cognitive radio channels for quality of service provisioning," IEEE Trans. Wireless Commun., vol. 9, no. 11, pp. 3354-3364, 2010. https://doi.org/10.1109/TWC.2010.092410.090751
  7. S. Akin and M. Gursoy, "Cognitive radio transmission under interference limitations and qos constraints," in Proc. of IEEE International Conference on Communications (ICC), 2010, pp. 1-5.
  8. D. Xu, Z. Feng, and P. Zhang, "Protecting primary users in cognitive radio networks with effective capacity loss constraint," IEICE Trans. Commun., vol. 95, no. 1, pp. 349-353, 2012.
  9. D. Xu, Z. Feng, and P. Zhang, "Effective capacity of delay quality-of-service constrained spectrum sharing cognitive radio with outdated channel feedback," Science China Information Sciences, 2013.
  10. R. Duan, M. Elmusrati, R. Jantti, and R. Virrankoski, "Capacity for spectrum sharing cognitive radios with MRC diversity at the secondary receiver under asymmetric fading," in Proc. of IEEE Global Telecommunications Conference (GLOBECOM), 2010, pp. 1-5.
  11. R. Duan, R. Jantti, M. Elmusrati, and R. Virrankoski, "Capacity for spectrum sharing cognitive radios with MRC diversity and imperfect channel information from primary user," in Proc. of IEEE Global Telecommunications Conference (GLOBECOM), 2010, pp. 1-5.
  12. D. Li, "Performance analysis of MRC diversity for cognitive radio systems," IEEE Trans. Veh. Technol., vol. 61, no. 2, pp. 849-853, Feb. 2012. https://doi.org/10.1109/TVT.2012.2182787
  13. V. Blagojevic and P. Ivanis, "Ergodic capacity for TAS/MRC spectrum sharing cognitive radio," IEEE Commun. Lett., vol. 16, no. 3, pp. 321-323, Mar. 2012. https://doi.org/10.1109/LCOMM.2012.011312.111488
  14. V.M. Blagojevic and P.N. Ivanis, "Ergodic capacity of spectrum sharing cognitive radio with MRC diversity and Nakagami fading," in Proc. of IEEE Wireless Communications and Networking Conference (WCNC), 2012, pp. 2797-2801.
  15. D. Xu, Z. Feng, and P. Zhang, "Minimum average ber power allocation for fading channels in cognitive radio networks," in Proc. of IEEE Wireless Communications and Networking Conference (WCNC), 2011, pp. 78-83.
  16. E. Al-Hussaini and A. Al-Bassiouni, "Performance of MRC diversity systems for the detection of signals with Nakagami fading," IEEE Trans. Commun., vol. 33, no. 12, pp. 1315-1319, 1985. https://doi.org/10.1109/TCOM.1985.1096243
  17. I. Gradshteyn and I. Ryzhik, Table of integrals, series, and products, 7th ed. Academic Pr, 2007.
  18. A. Goldsmith and P. Varaiya, "Capacity of fading channels with channel side information," IEEE Trans. Inf. Theory, vol. 43, no. 6, pp. 1986-1992, 1997. https://doi.org/10.1109/18.641562
  19. A. Ghasemi and E. Sousa, "Fundamental limits of spectrum-sharing in fading environments," IEEE Trans. Wireless Commun., vol. 6, no. 2, pp. 649-658, 2007. https://doi.org/10.1109/TWC.2007.05447
  20. S. Boyd and L. Vandenberghe, Convex optimization. Cambridge, U.K.: Cambridge Univ. Press, 2004.