• DocumentCode
    128487
  • Title

    Spectrum handoff model based on Hidden Markov model in Cognitive Radio Networks

  • Author

    Chuan Pham ; Tran, Nghi H. ; Do, Cuong T. ; Moon, Seung Il ; Choong Seon Hong

  • Author_Institution
    Dept. of Comput. Eng., Kyung Hee Univ., Yongin, South Korea
  • fYear
    2014
  • fDate
    10-12 Feb. 2014
  • Firstpage
    406
  • Lastpage
    411
  • Abstract
    Cognitive Radio Network (CRN) is one of technologies to enhance the spectrum utilization by allowing unlicensed users to exploit the spectrum in an opportunistic manner. In CRN, the spectrum handoff function is a necessary component to provide a resilient service for the unlicensed users. This function is used to discover spectrum holes in a licensed network and avoid interference between unlicensed users and licensed users. Due to the randomness of the appearance of Primary users, disruptions to communications of Secondary users are often difficult to prevent and lead to low throughput of CRN. In our paper, we analyze the status of channels and propose the spectrum handoff model based on Hidden Markov model (HMM) to optimize the spectrum handoff scheme for CRN. Moreover, we compare our method with the random channel selection in the simulation.
  • Keywords
    Markov processes; cognitive radio; mobility management (mobile radio); telecommunication channels; CRN; HMM; cognitive radio networks; hidden Markov model; interference avoidance; licensed users; random channel selection; spectrum handoff function; spectrum handoff model; spectrum handoff scheme; unlicensed users; Algorithm design and analysis; Analytical models; Cognitive radio; Heuristic algorithms; Hidden Markov models; Sensors; Switches; Cognitive Radio; Cognitive radio network; Forwardbackward procedure; Hidden Markov Models; Spectrum sensing; Viterbi Algorithm;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Information Networking (ICOIN), 2014 International Conference on
  • Conference_Location
    Phuket
  • Type

    conf

  • DOI
    10.1109/ICOIN.2014.6799714
  • Filename
    6799714