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Darwinian approach for dynamic spectrum allocation in next generation systems

Darwinian approach for dynamic spectrum allocation in next generation systems

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The authors present the use of a genetic algorithm (GA) model as a solution approach to the dynamic spectrum allocation (DSA) problem considered as a difficult combinatorial optimisation problem. The proposed multi-objective GA model enhances overall spectral efficiency of the network, while optimising its own spectrum utilisation to generate accessible spectrum opportunities for other radio technologies. A novel two-dimensional encoding technique is defined to represent solutions in the problem domain and the technique enables significantly shorter convergence times. A simulation tool has been developed to model the GA-based DSA and to compare the new scheme with the conventional fixed spectrum allocation (FSA) scheme under both uniform and non-uniform traffic distributions. The proposed scheme significantly outperformed the FSA scheme both in terms of spectral efficiency gain and spectral utilisation.

Inspec keywords: combinatorial mathematics; radio networks; genetic algorithms; encoding; telecommunication traffic

Other keywords: fixed spectrum allocation; 2D encoding; genetic algorithm; multiobjective GA; spectral efficiency; radio technology; Darwinian approach; next generation system; dynamic spectrum allocation; uniform traffic distribution; combinatorial optimisation

Subjects: Radio links and equipment; Combinatorial mathematics; Optimisation techniques

References

    1. 1)
      • I.K. Akyildiz , W. Lee , M.C. Vuran , S. Mohanty . Next generation/dynamic spectrum access/cognitive radio wireless networks: a survey. Comput. Netw. , 2127 - 2159
    2. 2)
      • J. Koza , F. Bennett , D. Andre , M. Keane . (1999) Genetic programming III: Darwinian invention and problem solving.
    3. 3)
      • Thilakawardana, D., Moessner, K.: `Enhancing spectrum productivity through cognitive radios facilitating cell-by-cell dynamic spectrum allocation', Proc. Int. Conf. Software Defined Radio Technical Conf., 2007, Denver, Colorado, USA.
    4. 4)
      • D.E. Goldberg . (1999) Genetic algorithms in search, optimization and machine learning.
    5. 5)
      • P. Leaves , K. Moessner , R. Tafazolli . Dynamic spectrum allocation in composite reconfigurable wireless networks. IEEE Commun. Mag. , 72 - 81
    6. 6)
      • M. Gen , R. Cheng . (1997) Genetic algorithms and engineering design.
    7. 7)
      • ‘Spectrum efficient uni- and multicast services over dynamic multi-radio networks in vehicular environments (Over DRiVE), IST-2001-35125.
    8. 8)
      • T. Janevski . (2003) Traffic analysis and design of wireless IP networks, mobile communication series.
    9. 9)
      • A. Bar-Noy , R. Bar-Yehuda , A. Freund , J. Naor , B. Schieber . A unified approach to approximating resource allocation and scheduling. J. ACM , 5 , 1069 - 1090
    10. 10)
      • M. Gen , R. Cheng . (2000) Genetic algorithms and engineering optimization.
    11. 11)
      • Thilakawardana, D., Moessner, K.: `A genetic approach to cell-by-cell dynamic spectrum allocation for optimizing spectral efficiency in wireless mobile systems', Proc. Int. Conf. 2nd Int. Conf. Cognitive Radio Oriented Wireless Networks and Communications, August 2007, Orlando, Florida, USA.
    12. 12)
      • A. Tucker . (1994) Applied combinatorics.
    13. 13)
      • R.A. Haput . A survey of priority-rule based scheduling problems. OR Spectrum , 3 - 16
    14. 14)
      • M.L. Cheng , J.I. Chuang . Performance evaluation of distributed measurement based dynamic channel assignment in local wireless communications. IEEE J. Sel. Areas Commun. , 698 - 710
    15. 15)
      • N. Nie , C. Comaniciu . Adaptive channel allocation spectrum etiquette for cognitive radio networks. Mob. Netw. Appl. , 6 , 779 - 797
    16. 16)
      • Mitola, J.: `Cognitive radio: an integrated agent architecture for software defined radio', 2000, PhD, KTH, Stockholm, Sweden.
    17. 17)
      • Thilakawardana, D.: `An efficient genetic algorithm application in assembly line balancing', 2002, PhD, University of Surrey, Guildford, UK, p. 87–96.
    18. 18)
      • Maldonado, D., Lie, B., Hugine, A., Rondeau, T.W., Bostian, C.W.: `Cognitive radio applications to dynamic spectrum allocation', Proc. Int. Conf. IEEE DySPAN, 2005, Maryland, USA, p. 597–600.
    19. 19)
      • Dynamic Radio for IP-services in Vehicular Environments (DRiVE), IST-1999-12515, Available at: http://www.ist-drive.org/index2.html, accessed April 2007.
    20. 20)
      • Leaves, P.: `Dynamic spectrum allocation between cellular and broadcast systems', 2004, PhD, University of Surrey, UK.
    21. 21)
      • Leaves, P., Ghaheri-niri, S., Tafazolli, R.: `Dynamic spectrum allocation in a multi-radio environment: concept and algorithm, 3G mobile communication technologies', Proc. Int. Conf. IEEE 2nd Int. Conf. 3G Mobile Communications, March 2001, London, UK, p. 53–57.
    22. 22)
      • Z. Michalewicz . (1996) Genetic algorithm+data structure=evolution programs.
    23. 23)
      • S. Dehghan , D. Lister , R. Owen , P. Jones . W-CDMA capacity and planning issues. IEEE Electron. Commun. Eng. J. , 101 - 118
    24. 24)
      • J.H. Holland . (1975) Adaptation in natural and artificial systems.
    25. 25)
      • B. Fette . (2006) Cognitive radio technology (Communications Engineering).
    26. 26)
      • `Research and Development at of com', 2004/05, issued:, 24 October 2005, p. 37.
    27. 27)
      • Cabric, D., Mishra, S.M., Willkomm, D., Brodersen, R.W., Wolisz, A.: `A cognitive radio approach for usage of virtual licenced spectrum', Proc. Int. Conf. 14th IST Mobile and Wireless Communications Summit, June 2005, Dresden, Germany.
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