Skip to main content

The Symbiosis of Cognitive Radio and Wireless Mesh Networks

  • Chapter
Guide to Wireless Mesh Networks

Part of the book series: Computer Communications and Networks ((CCN))

Abstract

Although wireless mesh networks (WMNs) have quickly been successfully deployed, the dual usage of wireless communication makes them very resource dependent. Proposed cognitive radio (CR) concepts appear to be a good solution to provide WMNs with additional bandwidth and improved efficiency. In addition, we believe that applying CR to WMN can be very beneficial to CR, speeding the development and acceptance of the technology.

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

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 39.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 54.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 54.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Federal Communications Commission (US). http://www.fcc.gov/

  2. Canadian Radio-television and Telecommunications Commission (CRTC). http://www.crtc.gc.ca/

  3. International Telecommunications Union (ITU). http://www.itu.int/

  4. Hazlett, T.W. (2006).The spectrum allocation debate. IEEE Internet Computing 10(5): 68–74

    Article  Google Scholar 

  5. M.A. McHenry (2005) NSF Spectrum Occupancy Measurements Project Summary. Shared Spectrum Company Report. http://www.sharedspectrum.com/

  6. Federal Communications Commission (FCC) (2002) Spectrum Policy Task Force ET Docket no. 02-135.

    Google Scholar 

  7. Mitola J. III Maguire G.Q. Jr, (1999).Cognitive radio: Making software radios more personal. IEEE Personal Communications 6(4): 13–18

    Article  Google Scholar 

  8. Mitola, J. (2000).Cognitive radio: An integrated agent architecture for software defined radio. Doctor of Technology, Royal Institute of Technology (KTH), Sweden

    Google Scholar 

  9. EEE 802.11 Working Group (2007) IEEE 802.11-1997: Wireless LAN Medium Access Control (MAC) and Physical Layer (PHY) Specifications.

    Google Scholar 

  10. Hanzo L. Tafazolli, R. (2007).A survey of QoS routing solutions for mobile ad hoc networks. IEEE Communications Surveys and Tutorials, 9(2): 50–70

    Article  Google Scholar 

  11. Kumar, S. Raghavan V.S. Deng, J. (2006).Medium access control protocols for ad hoc wireless networks: A survey, Ad Hoc Networks (Elsevier) 4:326–358

    Article  Google Scholar 

  12. Shono T. et al. (2005).IEEE 802.11 wireless LAN implemented on software defined radio with programmable architecture. IEEE Transactions on Wireless Communications 4(5): 2299–2308

    Article  Google Scholar 

  13. A. Bourdoux et al., Receiver Architectures for Software- defined Radios in Mobile Terminals: the Path to Cognitive Radios. In Proc. of 2007 IEEE Radio and Wireless Symposium (2007).

    Google Scholar 

  14. R. Wang et al., Capacity and performance analysis for adaptive multi-beam directional networking. In Proc. of MILCOM 2006 (2006).

    Google Scholar 

  15. R. Bhatia and L. Li, Throughput optimization of wireless mesh networks with MIMO links. In Proc. of IEEE Infocom (2007).

    Google Scholar 

  16. R. Ramanathan, On the performance of ad hoc networks with beam-forming antennas. In Proc. of 2001 ACM Intl. Symp. On Mobile Ad hoc Networking and Computing (2001).

    Google Scholar 

  17. D. Zhang and Z. Tian, Spatial capacity of cognitive radio networks: Narrowband versus ultra-wideband systems. In Proc. of IEEE WCNC (2007).

    Google Scholar 

  18. Z. Tian and G.B. Giannakis, A wavelet approach to wideband spectrum sensing for cognitive radios. In Proc. of 1st Cognitive Radio Oriented Wireless Networks and Communications Conference (2006).

    Google Scholar 

  19. Haykin, S. (2005).Cognitive Radio: Brain-empowered wireless communications. IEEE Journal on Selected Areas in Communications, 23(2): 201–220

    Article  Google Scholar 

  20. P. Sutton, L.E. Doyle and K.E. Nolan, A reconfigurable platform for cognitive networks. In Proc. of 1st Cognitive Radio Oriented Wireless Networks and Communications Conference (2006).

    Google Scholar 

  21. Zhu J. Liu, K.J.R. (2007).Dynamic spectrum sharing, a game theoretical overview. IEEE Communications Magazine 45(5): 88–94

    Article  Google Scholar 

  22. Noam, E.M. (1995).Taking the next step beyond spectrum auctions: open spectrum access. IEEE Communications Magazine 33(12): 66–73

    Article  Google Scholar 

  23. IEEE 802.22 WG on Wireless Regional Area Networks. http://www.ieee802.org/22/

  24. C. Cordeiro et al. IEEE 802.22: the first worldwide standard based on cognitive radios. In Proc. of IEEE DySpAN 2005 (2005).

    Google Scholar 

  25. C. Siller and R. Boutaba, Standards – A new challenge for ComSoc. IEEE Communications Magazine 43(8) (2005).

    Google Scholar 

  26. D. Maldonado et al., Cognitive radio applications to dynamic spectrum allocation: a discussion and an illustrative example. In Proc. of IEEE DySpAN 2005 (2005).

    Google Scholar 

  27. Akylidiz I.F. Wang, X. (2005).A survey on wireless mesh networks. IEEE Communications Magazine 43(9): S23–S30

    Article  Google Scholar 

  28. Jun J. Sichitiu, M.L. (2003).The nominal capacity of wireless mesh networks. IEEE Wireless Communications 10(5): 8–14

    Article  Google Scholar 

  29. D. Niculescu et al., Performance of VoIP in a 802.11 Wireless Mesh Network. In Proc. of INFOCOM (2006).

    Google Scholar 

  30. Das S.M. et al., (2006).DMesh: Incorporating directional antennas in multichannel wireless mesh networks. IEEE Journal on Selected Areas in Communications 24(11): 2028–2039

    Article  Google Scholar 

  31. H. Koubaa, Fairness-enhanced multiple control channels MAC for ad hoc networks. In Proc. of IEEE 61st Vehicular Technology Conference (2005).

    Google Scholar 

  32. J. Mo, H.W. So and J. Walrand, Comparison of multi-channel mac protocols. In Proc. of the 8th ACM/IEEE International Symposium on Modeling, Analysis and Simulation of Wireless and Mobile Systems (2005).

    Google Scholar 

  33. P. Kyanasur and N.H. Vaidya, Routing and interface assignment in multi-channel multi-interface wireless networks. In Proc. of 2005 IEEE Wireless Communications and Networking Conference (2005).

    Google Scholar 

  34. B. Aoun and R. Boutaba, Analysis of capacity improvements in multi-radio wireless mesh networks. In Proc. of 63rd IEEE Vehicular Technology Conference (2006).

    Google Scholar 

  35. D.T. Chen, On the Analysis of Using 802.16e WiMAX for point-to-point wireless backhaul. In Proc. of 2007 IEEE Radio and Wireless Symposium (2007).

    Google Scholar 

  36. X. Jing and D. Raychaudhuri, Spectrum co-existence of IEEE 802.11b and 802.16a networks using reactive and proactive etiquette policies. Journal of Mobile Networking Applications, Springer Science (2006).

    Google Scholar 

  37. Porrat, D. (2007).Information theory of wideband communications. IEEE Communication Surveys 9(2): 2–16

    Article  Google Scholar 

  38. Jafar S.A. Srinivasa, S. (2007).Capacity limits of cognitive radio with distributed and dynamic spectral activity. IEEE Journal on Selected Areas in Communications 25(3): 529–537

    Article  Google Scholar 

  39. I. Wormsbecke and C. Williamson, On channel selection strategies for multi-channel MAC Protocols in wireless ad hoc networks. In Proc. of WiMob 2006 (2006).

    Google Scholar 

  40. D. Aguayo et al., Link-level Measurements from an 802.11b Mesh Network. In Proc. of SIGCOMM (2004).

    Google Scholar 

  41. P.J. Kolodzy, Interference temperature: a metric for dynamic spectrum utilization. International Journal of Network Management, Wiley Interscience (2006).

    Google Scholar 

  42. Akyildiz I. et al., (2004).AdaptNet: An adaptive protocol suite for the next generation wireless internet. IEEE Communications Magazine 42(3): 128–136

    Article  Google Scholar 

  43. Marcus, M.J. (2005).Unlicensed cognitive sharing of TV spectrum: the controversy at the Federal Communications Commission. IEEE Communications Magazine 43(5): 24–25

    Article  Google Scholar 

  44. V.K. Varma et al., A beacon detection method for sharing spectrum between wireless access systems and fixed microwave systems. In Proc. of 1993 Vehicular Technology Conference (1993).

    Google Scholar 

  45. K. Kaemarungsi, Distribution of WLAN received signal strength indication for indoor location determination. In Proc. of 1st Intl. Symp. On Wireless Pervasive Computing (2006).

    Google Scholar 

  46. C. Savarese, J. Rabay, and K. Langendoen robust positioning algorithms for distributed ad-hoc wireless sensor networks. In Proc. of USENIX Technical Annual Conference (2002).

    Google Scholar 

  47. N. Sundaram and P. Ramanathan, Connectivity based location estimation scheme for wireless ad hoc networks. In Proc. of Globecom 2002 (2002).

    Google Scholar 

  48. Akyildiz I. et al., (2002).A survey on sensor networks. IEEE Communications Magazine 40(8): 101–114

    Article  Google Scholar 

  49. L. Jiang and G. Feng, A MAC aware cross-layer routing approach for wireless mesh network. In Proc. of WiCOM (2006).

    Google Scholar 

  50. C.J. Merlin and W.B. Heinzelman, A first look at a cross-layer facilitating architecture for wireless sensor networks. In Proc. of 2nd WiMesh Workshop (2006).

    Google Scholar 

  51. Ruiz, P.M. Botia, J.A. Gomez-Skarmeta, A. (2004).Providing QoS through machine-learning-driven adaptive multimedia applications. IEEE Transactions on Systems, Man, and Cybernetics 34(3): 1398–1411

    Article  Google Scholar 

  52. E. Stevens-Navarro and V.W.S. Wong, Comparison between vertical handoff decision algorithms for heterogeneous wireless networks. In Proc. of the 63rd IEEE Vehicular Technology Conference (2006).

    Google Scholar 

  53. G. Lee et al., A user-guided cognitive agent for network service selection in pervasive computing environments. In Proc. of IEEE PerCom'04 (2004).

    Google Scholar 

  54. X. Fu et al., Extended mobility management challenges over cellular networks combined with cognitive radio by using Multi-hop network. In Proc. of SNPD (2007).

    Google Scholar 

  55. J.B. Bernthal et al., Trends and precedents favoring a regulatory embrace of smart radio technologies. In Proc. of DySPAN (2007).

    Google Scholar 

  56. C. Raman, R.D. Yates, and N.B. Mandayam, Scheduling variable rate links via a spectrum server. In Proc. of IEEE DySpAN (2005).

    Google Scholar 

  57. S. Gandhi et al., A general framework for wireless spectrum auctions. In Proc. of IEEE DySPAN (2007).

    Google Scholar 

  58. L. Cao and H. Zheng, Distributed spectrum allocation via local bargaining. In Proc. of IEEE SECON (2005).

    Google Scholar 

  59. M. Thoppian et al., MAC-layer scheduling in cognitive radio based multi-hop wireless networks. In Proc. of IEEE WoWMoM (2006).

    Google Scholar 

  60. J.M. Peha and S. Panichpapiboon, Real-time secondary markets for spectrum. Telecommunications Policy (Elsevier) 28 (2004).

    Google Scholar 

  61. F. Capar and F. Jondral, Spectrum pricing for excess bandwidth in radio networks. In Proc. of PIMRC (2004).

    Google Scholar 

  62. Oner M. Jondral F. (2007).On the extraction of the channel allocation information in spectrum pooling systems. IEEE Journal on Selected Areas in Communications 25(3): 558–565

    Article  Google Scholar 

  63. M.K. Chirumamilla and B. Ramamurthy, Agent based intrusion detection and response system for wireless LANs. In Proc. of IEEE ICC'03 (2003).

    Google Scholar 

  64. W. Xu, P. Kamat and W. Trappe, TRIESTE, A trusted radio infrastructure for enforcing SpecTrum Etiquettes. In Proc. of 1st IEEE Workshop on Networking Technologies for Software Defined Radio Networks (2006).

    Google Scholar 

  65. J.M. Chapin and W.H. Lehr, Time-limited leases for innovative radios. In Proc. of DySPAN (2007).

    Google Scholar 

  66. A.A. Tomko, C.J. Rieser and L.H. Buell, Physical-layer intrusion detection in wireless networks. In Proc. of Military Communications Conference (2006).

    Google Scholar 

  67. Industry Canada. Radio Spectrum Allocations in Canada (Chart). http://www.ic.gc.ca/epic/site/smt-gst.nsf/en/h_sf01678e.html.

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Raouf Boutaba .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2009 Springer-Verlag London

About this chapter

Cite this chapter

Ishibashi, B., Boutaba, R. (2009). The Symbiosis of Cognitive Radio and Wireless Mesh Networks. In: Misra, S., Misra, S.C., Woungang, I. (eds) Guide to Wireless Mesh Networks. Computer Communications and Networks. Springer, London. https://doi.org/10.1007/978-1-84800-909-7_18

Download citation

  • DOI: https://doi.org/10.1007/978-1-84800-909-7_18

  • Publisher Name: Springer, London

  • Print ISBN: 978-1-84800-908-0

  • Online ISBN: 978-1-84800-909-7

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics