Skip to main content
Log in

Aggregate Interference of Equidistant Cognitive Radios

  • Published:
Wireless Personal Communications Aims and scope Submit manuscript

Abstract

In spite of spectrum sensing, aggregate interference from cognitive radios (CRs) remains as a deterring factor to the implementation of spectrum sharing strategies. We provide a systematic approach of evaluating the aggregate interference (I aggr) experienced at a victim primary receiver (PR). In our approach, we model the received power versus distance relations between a primary transmitter (PT), PR, and CRs. CRs can spatially reuse a channel and thus two adjacent CRs are separated by the co-channel reuse distance (R). Our analytical framework differs from the existing ones in that we have formulated I aggr in terms of R and sensing inaccuracy. Energy detector is assumed for the purpose of spectrum sensing. I aggr is expressed explicitly as a function of the number of energy samples collected (N) and the threshold SNR level used for comparison (SNR ε ). This allows us to assess their impacts on I aggr. A numerical example is constructed based on the scenario of spectrum sharing between DTV broadcast and IEEE 802.22 Wireless Regional Area Network. Our analysis demonstrates the extents of which I aggr can be restricted, by increasing R or sensing accuracy (either by increasing N or decreasing SNR ε ), and the amount of increment required. Conditioned on the example scenario, the critical {N, SNR ε , R} values that fulfill certain regulatory requirement are revealed.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9

Similar content being viewed by others

References

  1. Stevenson, C., Chouinard, G., Lei, Z., Hu, W., Shellhammer, S. J., & Caldwell, W. (2009). IEEE 802.22: The first cognitive radio wireless regional area network standard. IEEE Communications Magazine, 47(1), 130–138.

    Article  Google Scholar 

  2. Andrews, J. G., Claussen, H., Dohler, M., Rangan, S., & Reed, M. C. (2012). Femtocells: Past, present, and future. IEEE Journal on Selected Areas in Communications, 30(3), 497–508.

    Article  Google Scholar 

  3. Urkowitz, H. (1967). Energy detection of unknown deterministic signals. Proceedings of the IEEE, 55(4), 523–531.

    Article  Google Scholar 

  4. Menon, R., Buehrer, R. M., & Reed, J. H. (2008). On the impact of dynamic spectrum sharing techniques on legacy radio systems. IEEE Transactions on Wireless Communications, 7(11), 4198–4207.

    Article  Google Scholar 

  5. Chen, Z., Wang, C.-X., Hong, X., Thompson, J., Vorobyov, S. A., Ge, X., et al. (2012). Aggregate interference modeling for cognitive radio networks with power and contention control. IEEE Transactions on Communications, 60(2), 456–467.

    Article  Google Scholar 

  6. Rabbachin, A., Quek, T. Q. S., Shin, H., & Win, M. Z. (2011). Cognitive network interference. IEEE Journal on Selected Areas in Communications, 29(2), 480–493.

    Article  Google Scholar 

  7. Ghasemi, A., & Sousa, E. S. (2008). Interference aggregation in spectrum-sensing cognitive wireless networks. IEEE Journal of Selected Topics in Signal Processing, 2(1), 41–56.

    Article  Google Scholar 

  8. Mahmood, N. H., Yilmaz, F., Alouini, M.-S., & Øien, G. E. (2014). Heterogeneous next-generation wireless network interference model—And its applications. Transactions on Emerging Telecommunications Technologies, 25(5), 563–575.

    Google Scholar 

  9. Rappaport, T. S. (2001) Wireless communications: Principles and practice (2nd ed.). Prentice Hall. ISBN: 0-13-042232-0.

  10. Foo, Y.-L. (2013). Deployment of wireless regional area network and its impact on DTV service coverage. Annals of Telecommunications, 68(11–12), 691–703.

    Article  Google Scholar 

  11. Foo, Y.-L. (2013). Cooperative sensing in wireless regional area network to improve DTV coverage prediction. Wireless Personal Communications, 72(4), 2339–2360.

    Article  MathSciNet  Google Scholar 

  12. Nuttall, A. H. (1975). Some integrals involving the Q M function. IEEE Transactions on Information Theory, 21(1), 95–96.

    Article  MathSciNet  MATH  Google Scholar 

  13. Code of Federal Regulations (C.F.R.) Title 47—Telecommunication, Part 73—Radio Broadcast Services, Subpart E—Television Broadcast Stations, Section 73.623—DTV applications and changes to DTV allotments, (2012).

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Yee-Loo Foo.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Foo, YL., Takada, Ji. Aggregate Interference of Equidistant Cognitive Radios. Wireless Pers Commun 92, 1053–1069 (2017). https://doi.org/10.1007/s11277-016-3592-2

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11277-016-3592-2

Keywords

Navigation