Advertisement

Wireless Personal Communications

, Volume 69, Issue 4, pp 1749–1772 | Cite as

Spatial Spectrum Reuse for Opportunistic Spectrum Access in Infrastructure-Based Systems

  • Dimitris Tsolkas
  • Nikos Passas
  • Lazaros Merakos
Article

Abstract

Opportunistic spectrum access (OSA) receives a constantly growing interest due to its potential to mitigate spectrum scarcity and meet the increasing communication needs of mobile users. OSA refers to identifying and exploiting spatiotemporal unused portions of licensed spectrum to allow communication among unlicensed–secondary users (SUs) without adverse impact to the licensees (primary users—PUs). Key parameters in OSA are the spectrum opportunities detection method used by the SUs, and the interference level perceived by the PUs. A spatial spectrum reuse framework is proposed, where broadcast messages of an infrastructure-based primary system are exploited and combined with location-aware methods to detect spectrum opportunities and establish interference-free secondary links. The study of secondary link establishment probabilities revealed a spectrum reuse of up to 25% for omni-directional and up to 90% for directional antennas. Moreover, increased throughput is achieved in both cases, with directional antennas attaining significantly better performance.

Keywords

Cognitive radios Opportunistic spectrum access Spatial spectrum reuse Uplink opportunities Geometric analysis 

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 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 Journal (Elsevier) 50(3): 2127–2159zbMATHCrossRefGoogle Scholar
  2. 2.
    Mitola, J. (1999). Cognitive radio for flexible mobile multimedia communication. In Proceedings of IEEE international workshop on mobile multimedia communications (MoMuC), San Diego, November 15–17, 1999 (pp. 3–10).Google Scholar
  3. 3.
    Zhao Q., Sadler B. (2007) A survey of dynamic spectrum access. IEEE Signal Processing Magazine 24(3): 79–89CrossRefGoogle Scholar
  4. 4.
    Yucek T., Arslan H. (2007) A survey of spectrum sensing algorithms for cognitive radio applications. IEEE Communication Surveys and Tutorials 11(1): 116–130CrossRefGoogle Scholar
  5. 5.
    Zhao Q., Tong L., Swami A., Chen Y. (2007) Decentralized cognitive MAC for opportunistic spectrum access in ad hoc networks: A POMDP framework. IEEE Journal on Selected Areas in Communications 2007 25(3): 589–600CrossRefGoogle Scholar
  6. 6.
    Xiang J., Zhang Y., Skeie T. (2010) Medium access control protocols in cognitive radio networks. Wireless Communications and Mobile Computing 10(1): 31–49CrossRefGoogle Scholar
  7. 7.
    Jia J., Zhang Q., Shen X. (2008) HC-MAC: A hardware-constrained cognitive MAC for efficient spectrum management. IEEE Journal on Selected Areas in Communications 26(1): 106–117CrossRefGoogle Scholar
  8. 8.
    Su, H., & Zhang, X. (2008). CREAM-MAC: An efficient cognitive radio enabled multi-channel MAC protocol for wireless networks. In Proceedings of international symposium on a world of wireless, mobile and multimedia networks (WoWMoM 2008), Newport Beach, June 23–26, 2008 (pp. 1–8).Google Scholar
  9. 9.
    Hamdaoui B., Shin K. (2008) OS-MAC: An efficient MAC protocol for spectrum-agile wireless networks. IEEE Transactions on Mobile Computing 7(8): 915–930CrossRefGoogle Scholar
  10. 10.
    Ma, L., Han, X., & Shen, C.-C. (2005). Dynamic open spectrum sharing MAC protocol for wireless ad hoc networks. In Proceedings of the IEEE DySPAN 2005, Baltimore, November 8–11, 2005 (pp. 203–213).Google Scholar
  11. 11.
    Kondareddy, Y., & Agrawal, P. (2008). Synchronized MAC protocol for multi-hop cognitive radio networks. In Proceedings of IEEE international conference on communications 2008 (ICC ’08), Beijing, 19–23 May, 2008 (pp. 3198–3202).Google Scholar
  12. 12.
    Huang K., Lau V. K. N., Chen Y. (2009) Spectrum sharing between cellular and mobile ad hoc networks: Transmission-capacity trade-off. IEEE Journal on Selected Areas in Communications 27(7): 1256–1267CrossRefGoogle Scholar
  13. 13.
    Tsolkas, D., Passas, N., & Merakos, L. (2011). Increasing spectrum utilization in wireless infrastructure-based systems. In Proceedings of the 16th IEEE symposium on computers and communications 2011 (ISCC’11), Corfu, Greece, 28 June–1 July, 2011.Google Scholar
  14. 14.
    Wang L.-C., Chen A. (2009) Effects of location awareness on concurrent transmissions for cognitive ad hoc networks overlaying infrastructure based systems. IEEE Transactions on Mobile Computing 8(5): 577–589CrossRefGoogle Scholar
  15. 15.
    Andrews J. G., Ghosh A., Muhamed R. (2007) Fundamentals of WiMAX: Understanding Broadband Wireless Networking. Upper Saddle River, NJ: Prentice HallGoogle Scholar
  16. 16.
    Mark B. L., Nasif A. O. (2009) Estimation of interference-free power for opportunistic spectrum access. IEEE Transactions on Wireless Communications 8(5): 2505–2513CrossRefGoogle Scholar
  17. 17.
    Kim, S., Jeon, H., & Ma, J. (2007). Robust localization with unknown transmission power for cognitive radio. In Proceedings of IEEE internatioanal conference on military communications (Milcom’07), Orlando, October 29–31, 2007 (pp. 1–6).Google Scholar
  18. 18.
    Porretta M., Nepa P., Manara G., Giannetti F., Dohler M., Allen B. et al (2004) A novel single base station location technique for microcellular wireless networks: Description and validation by a deterministic propagation model. IEEE Transactions on Vehicular Technology 53(5): 1502–1514CrossRefGoogle Scholar
  19. 19.
    Leu E., McHenry M., Mark B. L. (2006) Modeling and analysis of interference in listen-before-talk spectrum access schemes. International Journal of Network Management 16(2): 131–147CrossRefGoogle Scholar
  20. 20.
    IEEE standard for wireless LAN medium access control (MAC) and physical layer (PHY) specifications, P802.11, June 2007.Google Scholar
  21. 21.
    Bianchi G. (2000) Performance analysis of the IEEE 802.11 distributed coordination function. IEEE Journal on Selected Area in Communications 18(3): 535–547CrossRefGoogle Scholar
  22. 22.
    Chatzimisios P., Boucouvalas A. C., Vitsas V. (2005) Performance analysis of the IEEE 802.11 MAC protocol for wireless LANs. Wiley International Journal of Communication Systems 18(6): 545–569CrossRefGoogle Scholar
  23. 23.
    Pei Y., Liang Y.-C., The K., Li K. (2009) How much time is needed for wideband spectrum sensing?. IEEE Transactions on Wireless Communications 8(11): 5466–5471CrossRefGoogle Scholar
  24. 24.
    Kim H., Shin K. G. (2010) In-band spectrum sensing in IEEE 802.22 WRANs for incumbent protection. IEEE Transactions on Mobile Computing 9(12): 1766–1779MathSciNetCrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media, LLC. 2012

Authors and Affiliations

  • Dimitris Tsolkas
    • 1
  • Nikos Passas
    • 1
  • Lazaros Merakos
    • 1
  1. 1.Department of Informatics and TelecommunicationsUniversity of AthensAthensGreece

Personalised recommendations