Skip to main content
Log in

Optimal user scheduling and power control in multi-user cognitive broadcast systems

  • Research Paper
  • Published:
Science China Information Sciences Aims and scope Submit manuscript

Abstract

Cognitive radio systems should not only have the ability to sense and exploit “frequency spectrum holes”, but also the ability to sense and utilize “spatial spectrum holes”. In this paper, we consider the issue of maximizing the throughput of the cognitive systems by fully utilizing “spatial spectrum holes” brought in by multiple cognitive users, in the scenario where a pair of licensed users and a cognitive broadcast system share multiple spectrum bands. By exploiting the channel reciprocity under the premise that the licensed system adopts the time-division-duplexing (TDD) mode, we propose a more practical cognitive access scheme that can sense the interference at the licensed user caused by the cognitive transmitter, based on the existing feedback signals from the licensed user to the licensed base station. Taking both interferences from the licensed base station to the cognitive receiver and from the cognitive transmitter to the licensed user into consideration, we investigate the optimal user scheduling and power allocation scheme that can maximize the ergodic sum rate of the cognitive system. We show that scheduling the user whose channel gain to interference and noise ratio (CGINR) is the largest for each frequency band is optimal. We also derive the dynamic power allocation scheme meeting the three practical constraints, i.e., the transmitter’s average transmission power constraint, the power amplifier’s instantaneous transmission power constraint, and the interference power constraint at the licensed user. The result shows that in different coherent time intervals and different frequency bands, the power allocation has a multi-level waterfilling structure. Theoretical analysis shows that the strategy scheduling user with the largest CGINR introduces significant performance improvement compared with the traditional strategy scheduling user with the largest channel gain to noise ratio (CGNR). We also illustrate the impact of power constraints and the number of users on system performance by simulation.

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.

Similar content being viewed by others

References

  1. Federal Communications Commission. Spectrum Policy Task Force Report, FCC 02-155. 2002

  2. Mitola J, Maguire G Q. Cognitive radios: Making software radio more personal. IEEE Pers Commun, 1999, 6: 13–18

    Article  Google Scholar 

  3. Zhao Q, Swami A. A decision-theoretic framework for opportunistic spectrum access. IEEE Trans Wirel Commun, 2007, 14: 14–20

    Google Scholar 

  4. Ghasemi A, Sousa E S. Fundamental limits of spectrum-sharing in fading environments. IEEE Trans Wirel Commun, 2007, 6: 649–658

    Article  Google Scholar 

  5. Weiss T A, Jondral F K, Karlsruhe U. Spectrum pooling: an innovative strategy for the enhancement of spectrum efficiency. IEEE Commun Mag, 2004, 42: S8–14

    Article  Google Scholar 

  6. Geirhofer S, Tong L, Sadler B M. Cognitive Radios for dynamic spectrum access — dynamic spectrum access in the time domain: modeling and exploiting white space. IEEE Commun Mag, 2007, 45: 66–72

    Article  Google Scholar 

  7. Zhang R, Liang Y C. Exploiting multi-antennas for opportunistic spectrum sharing in cognitive radio networks. IEEE J Sel Topics Signal Process, 2008, 2: 88–102

    Article  Google Scholar 

  8. Perlaza S M, Lasaulce S, Debbah M. From spectrum pooling to space pooling:opportunistic interference alignment in MIMO cognitive networks. IEEE Trans Signal Process, 2010, 58: 3728–3741

    Article  MathSciNet  Google Scholar 

  9. Bixio L, Ottonello M, Raffetto M, et al. Cognitive radios with multiple antennas exploiting spatial opportunities. IEEE Trans Signal Process, 2010, 58: 4453–4459

    Article  MathSciNet  Google Scholar 

  10. Zhao G D, Ma J, Li G Y, et al. Spatial spectrum holes for cognitive radio with relay-assisted directional transmission. IEEE Trans Wirel Commun, 2009, 8: 5270–5279

    Article  Google Scholar 

  11. Huang S H, Ding Z, Liu X. Non-Intrusive cognitive radio networks based on smart antenna technology. In: Global Telecommunications Conference, 2007. 4862–4867

  12. Zhang R, Cui S G, Liang Y C. On ergodic sum capacity of fading cognitive multiple-access and broadcast channels. IEEE Trans Inf Theory, 2009, 55: 5161–5178

    Article  MathSciNet  Google Scholar 

  13. Ban T W, Choi W, Jung B C. Multi-user diversity in a spectrum sharing system. IEEE Trans Wirel Commun, 2009, 8: 102–106

    Article  Google Scholar 

  14. Tajer A, Wang X D. Multiuser diversity gain in cognitive networks. IEEE/ACM Trans Netw, 2010, 18: 1766–1779

    Article  Google Scholar 

  15. Zhang R, Liang Y C. Investigation on multiuser diversity in spectrum sharing based cognitive radio networks. IEEE Commun Lett, 2010, 14: 133–135

    Article  Google Scholar 

  16. Li L F, Goldsmith A J. Capacity and optimal resource allocation for fading broadcast channels-part I: ergodic capacity. IEEE Trans Inf Theory, 2001, 47: 1083–1102

    Article  MathSciNet  MATH  Google Scholar 

  17. Tse D N. Optimal power allocation over parallel Gaussian broadcast channels, 1998 [Online]. Available at http://www.eecs.berkeley.edu/?dtse/broadcast2.pdf

  18. Palomar D P, Fonollosa J R. Practical algorithms for a family of waterfilling solutions. IEEE Trans Signal Process, 2005, 53: 686–695

    Article  MathSciNet  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to QunHuan Wang.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Wang, Q., Wang, H. & Yin, Q. Optimal user scheduling and power control in multi-user cognitive broadcast systems. Sci. China Inf. Sci. 55, 1402–1414 (2012). https://doi.org/10.1007/s11432-012-4562-2

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11432-012-4562-2

Keywords

Navigation