Emergency Networking in Licensed Spectrum Using Cognitive Radios: Challenges and Insights

Chapter
Part of the Lecture Notes in Electrical Engineering book series (LNEE, volume 116)

Abstract

A new paradigm for emergency networking is proposed that enables reliable and high data-rate wireless multimedia communications among first responders in licensed spectrum. Such communications are essential for efficient and coordinated rescue and recovery missions in the aftermath of natural and man-made disasters. The envisioned paradigm differs from the traditional dynamic spectrum access paradigm of higher priority for licensed incumbent users compared to unlicensed users because of the need for emergency networks to reverse the role assignments based on dynamic mission policies. As an example, a highly reconfigurable mission-policy-aware cross-layer communication framework for cognitive ad hoc emergency networking is presented. It is followed with a detailed discussion about the research challenges associated with solving optimization problems in resource-constrained environments and in time-constrained emergency scenarios. Research challenges associated with translation and dissemination of the proposed dynamic mission policies and their incorporation into the communication framework are also discussed.

Keywords

Cognitive radio Licensed spectrum  Emergency networking Spectrum rules Mission policies Multiple access Cross-layering 

References

  1. 1.
    NY Officials Propose National Wireless Emergency Network. [Online]. Available: http://www.ny1.com/content/topstories/137157/ny-officialspropose-national-wireless-emergency-network
  2. 2.
    Bazelon C (2009) Too many goals: problems with the 700 MHz auction. Information Economics and Policy (Special Section on Auctions) 21(2):115–127Google Scholar
  3. 3.
    Federal Communications Commission (FCC) White Space Ruling, http://hraunfoss.fcc.gov/edocs_public/attachmatch/FCC-08-260A1.pdf
  4. 4.
    Haykin S (2005) Cognitive radio: brain-empowered wireless communications. IEEE Journal on Selected Areas in Communications (JSAC) 23(2):201–220CrossRefGoogle Scholar
  5. 5.
    Mitola J, Maguire GQ (1999) Cognitive radio: making software radios more personal. IEEE Pers Commun 6(4):13–18CrossRefGoogle Scholar
  6. 6.
    Pawelczak P, Venkatesha Prasad R, Xia L, and Niemegeers I (2005) Cognitive radio emergency networks requirements and design. In: Proceedings of IEEE international symposium on new frontiers in dynamic spectrum access networks (DySPAN), Baltimore, MD, Nov 2005Google Scholar
  7. 7.
    Zhang Q, Kokkeler A, and Smit G (2006) A Reconfigurable radio architecture for cognitive radio in emergency networks. In: Proceedings of 9th European conference on wireless technology(ECWT), Manchester, UK, Sep 2006Google Scholar
  8. 8.
    Wang W, Gao W, Bai X, Peng T, Chuai G, and Wang W (2007) A Framework of wireless emergency communications based on relaying and cognitive radio. In: Proceedings of IEEE international symposium on personal, indoor and mobile radio communications (PIMRC), Athens, Greece, Sep 2007Google Scholar
  9. 9.
    Jesuale N and Eydt B (2007) A Policy proposal to enable cognitive radio for public safety and industry in the land mobile radio bands. In: Proceedings of IEEE international symposium on new frontiers in dynamic spectrum access networks (DySPAN), Dublin, Ireland, Apr 2007Google Scholar
  10. 10.
    Bernthal B and Jesuale N (2008) Smart radios and collaborative public safety communications.In: Proceedings of IEEE international symposium on new frontiers in dynamic spectrum access networks (DySPAN), Chicago, IL, Oct 2008Google Scholar
  11. 11.
    Zhou X, Gandhi S, Suri S, and Zheng H (2008) Ebay in the sky: strategy-proof wireless spectrum auctions. In: Proceedings of the ACM international conference on mobile computing and networking (MobiCom),San Francisco, CA, Sep 2008Google Scholar
  12. 12.
    Yu H, Gao L, Li Y, Gan X, Wang X, Xu Y, Chen W, and Vasilakos AV (2009) Information sharing in spectrum auction for dynamic spectrum access In: Proceedings of the IEEE conference on global elecommunications (GLOBECOM), Honolulu, HI, Dec 2009Google Scholar
  13. 13.
    Buddhikot M, Kolodzy P, Miller S, Ryan K, and Evans J(2005) DIMSUMNET: New directions in wireless networking using coordinated dynamic spectrum. In: Proceedings of IEEE international symposium on world of wireless mobile and multimedia networks (WoWMoM), Taormina, Greece, Jun 2005Google Scholar
  14. 14.
    Brik V, Rozner E, Banerjee S, and Bahl P (2005) DSAP: A Protocol for coordinated spectrum access. In: Proceedings. of First IEEE international symposium on new frontiers in dynamic spectrum access networks (DySPAN), Baltimore, MD, Nov 2005Google Scholar
  15. 15.
    “IEEE 802 LAN/MAN Standards Committee 802.22 WG on WRANs (wireless regional area networks),” http://www.ieee802.org/22/
  16. 16.
    Yuan Y, Bahl P, Chandra R, Chou P, Ferrell J, Moscibroda T, Narlanka S, and Wu Y (2007) Knows: cognitive radio networks over white spaces. In: Proceedings IEEE international symposium on new frontiers in dynamic spectrum access networks (DySPAN), Dublin, Ireland, Apr 2007Google Scholar
  17. 17.
    Yuan Y, Bahl P, Chandra R, Moscibroda T, and Wu Y (2007) Allocating dynamic time-spectrum blocks in cognitive radio networks. In: Proceedings of the ACM international symposium on Mobile ad hoc networking and computing (MobiHoc), Montreal, Canada, Sep 2007Google Scholar
  18. 18.
    Bahl P, Chandra R, Moscibroda T, Murty R, Welsh M (2009) White space networking with wi-fi like connectivity. SIGCOMM computer commuication review 39(4):27–38CrossRefGoogle Scholar
  19. 19.
    Rahul H, Kushman N, Katabi D, Sodini C, Edalat F (2008) Learning to share: narrowband-friendly wideband networks. SIGCOMM computer communication review 38(4):147–158CrossRefGoogle Scholar
  20. 20.
    Attar A, Nakhai M, Aghvami A (2008) Cognitive radio transmission based on direct sequence mc-cdma. IEEE Trans Wireless Commun 7(4):1157–1162CrossRefGoogle Scholar
  21. 21.
    Yang L, Hou W, Cao L, Zhao BY, and Zheng H (2010) Supporting demanding wireless applications with frequency-agile radios In: Proceedings of ACM/USENIX NSDI, San Jose, CA, Apr 2010Google Scholar
  22. 22.
    Salva-Garau F and Stojanovic M (2003) Multi-cluster protocol for ad hoc mobile underwater acoustic networks In: Proceedings of MTS/IEEE conference and exhibition for ocean engineering, science and technology (OCEANS), San Francisco, CA, Sept 2003Google Scholar
  23. 23.
    Pompili D, Vuran MC, and Melodia T (2006) Cross-layer design in wireless sensor networks. Sensor network and configuration: fundamentals, techniques, platforms, and experiments, N. P. Mahalik, Ed., Springer-Verlag, Germany 2006Google Scholar
  24. 24.
    Cheng G, Liu W, Li Y, and Cheng W (2007) Joint on-demand routing and spectrum assignment in cognitive radio networks In: Proceedings of IEEE international conference on communications (ICC), Glasgow, UK, June 2007Google Scholar
  25. 25.
    Hou Y, Shi Y, and Sherali H (2007) Optimal spectrum sharing for multi-hop software defined radio networks In: Proceedings of IEEE international conference on computer communications (INFOCOM), Anchorage, AK, May 2007Google Scholar
  26. 26.
    Ding L, Melodia T, Batalama SN, Martyjas JD, Medley MJ (2010) Cross-layer routing and dynamic spectrum allocation in cognitive radio ad hoc networks. IEEE Trans Veh Technol 59(4):1969–1979CrossRefGoogle Scholar
  27. 27.
    Broomhead D, Huke J, Muldoon M (1999) Codes for spread spectrum applications generated using chaotic dynamical system. Dynam Stabil Syst 14(1):95–105MathSciNetMATHCrossRefGoogle Scholar
  28. 28.
    “ns3: Network simulator,” http://www.nsnam.org/
  29. 29.
    Lee EK, Varkey JP, and Pompili D (2011) On the impact of neighborhood discovery on geographical routing in wireless sensor networks. In: Proceedings. of IEEE sarnoff symposium, Princeton, NJ, May 2011Google Scholar
  30. 30.
    Hou TC, Li V (1986) Transmission range control in multihop packet radio networks. IEEE Trans Commun 34(1):38–44MathSciNetCrossRefGoogle Scholar
  31. 31.
    Pompili D, Melodia T, and Akyildiz IF (2006) Routing algorithms for delay-insensitive and delay-sensitive applications in underwater sensor networks. In: Proceedings of International Conference on Mobile Computing and Networking (MobiCom), Los Angeles, CA, Sep. 2006Google Scholar
  32. 32.
    Finn GG (1987) Routing and addressing problems in large metropolitanscale internetworks. Information Sciences Institute, University of Southern California, Technical Report ISI/RR-87–180, Mar. 1987Google Scholar
  33. 33.
    Mitola J III (2009) Cognitive radio policy languages. In: Proceedings of the IEEE international conference on communications (ICC), Dresden, Germany, June 2009Google Scholar
  34. 34.
    Navas JC and Imielinski T (1997) Geocast: Geographic addressing and routing. In: Proceedings of the ACM/IEEE international conference on Mobile computing and networking (MobiCom). Budapest, Hungary, Sep 1997Google Scholar
  35. 35.
    Cabric D, Mishra S, Brodersen R (2004) Implementation issues in spectrum sensing for cognitive radios, in record of the thirty-eighth asilomar conference on signals. Systems and Computers, Pacific Grove, CAGoogle Scholar
  36. 36.
    Sahai A, Hoven N and Tandra R (2004) Some fundamental limits on cognitive radio In: Forty-second Allerton conference on communication, control, and computing, Monticello, IL, Sep 2004Google Scholar
  37. 37.
    Kim H and Shin KG (2008) In-band spectrum sensing in cognitive radio networks: energy detection or feature detection?. In: Proceedings of the ACM/IEEE international conference on mobile computing and networking (MobiCom), San Francisco, CA, Sep 2008Google Scholar
  38. 38.
    Kim H and Shin KG (2008) “Efficient Discovery of Spectrum Opportunities with MAC-layer sensing in cognitive radio networks,” IEEE Transa Mobile Computi vol. 7(5) :533–545Google Scholar
  39. 39.
    Quan Z, Cui S, Poor H, Sayed A (2008) Collaborative wideband sensing for cognitive radios. IEEE Signal Process Mag 25(6):60–73CrossRefGoogle Scholar
  40. 40.
    Akyildiz F, Lee W.-Y, Chowdhury KR (2009) Crahns: cognitive radio ad hoc networks. Ad Hoc Networks Journal. 7(5):810–836CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media Dordrecht 2012

Authors and Affiliations

  1. 1.Department of Electrical and Computer EngineeringRutgers UniversityPiscatawayUSA

Personalised recommendations