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Adaptive limited fractional guard channel algorithms: A learning automata approach

Beigy, H ; Sharif University of Technology

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  1. Type of Document: Article
  2. DOI: 10.1142/S0218488509006315
  3. Abstract:
  4. In this paper, two learning automata based adaptive limited fractional guard channel algorithms for cellular mobile networks are proposed. These algorithms try to minimize the blocking probability of new calls subject to the constraint on the dropping probability of the handoff calls. To evaluate the proposed algorithms, computer simulations are conducted. The simulation results show that the performance of the proposed algorithms are close to the performance of the limited fractional guard channel algorithm for which prior knowledge about traffic parameters are needed. The simulation results also show that the proposed algorithms outperforms the recently introduced dynamic guard channel algorithms. © 2009 World Scientific Publishing Company
  5. Keywords:
  6. Adaptive limited fractional guard channel ; Learning automata ; Limited fractional guard channel ; Call admission control ; Cellular mobile networks ; Dropping probability ; Guard channels ; Handoff call ; Learning Automata ; Non-stationary environment ; Prior knowledge ; Simulation result ; Traffic parameters ; Adaptive control systems ; Automata theory ; Blocking probability ; Computer simulation ; Education ; Robots ; Translation (languages) ; Wireless networks ; Wireless telecommunication systems ; Learning algorithms
  7. Source: International Journal of Uncertainty, Fuzziness and Knowlege-Based Systems ; Volume 17, Issue 6 , 2009 , Pages 881-913 ; 02184885 (ISSN)
  8. URL: http://www.worldscientific.com/doi/abs/10.1142/S0218488509006315