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Outline of the talk

Call Admission Control in Mobile Cellular CDMA Systems using Fuzzy Associative Memory Rupenaguntla Naga Satish Dilip Sarkar Computer Science University of Miami. Outline of the talk. What is QoS? Review of CAC Algorithms Proposed CAC System Assumptions

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Outline of the talk

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  1. Call Admission Control in Mobile Cellular CDMA Systems using Fuzzy Associative Memory Rupenaguntla Naga SatishDilip SarkarComputer ScienceUniversity of Miami Uinversity of Miami

  2. Outline of the talk What is QoS? Review of CAC Algorithms Proposed CAC System Assumptions Design of FAM for Mobile Cellular Systems Operation of the FAM-based CAC System Evaluation of the FAM-based CAC System Conclusion Uinversity of Miami

  3. What is QoS? • QoS parameters • Blocking probability • Handoff failure probability • Forced termination or dropping probability • All of these parameters cannot be improved simultaneously • Our objectives • Keep forced termination rate below a desired level • Maximize channel utilization Uinversity of Miami

  4. Review of CAC Algorithms: • Handoff prioritization Schemes • Guard channels • Early channel reservation Uinversity of Miami

  5. Review: Call Pre-blocking Scheme New alls may be pre-blocking even when resource is available: Uinversity of Miami

  6. Review: Call Pre-blocking scheme Forced termination prob. at or below desired level Very high channel utilization Uinversity of Miami

  7. Review: Call pre-blocking scheme variable call holding time Uinversity of Miami

  8. Review: Call pre-blocking scheme Variable cell dwell time Uinversity of Miami

  9. Call Preblocking Criteria for CDMA systems Pft = (λ, η, μ, C) C is the capacity of a cell using CDMA and is given by C = (W/Rα)/(Eb/N0) – (NTW)/S + 1, where • W is the available bandwidth • R is the data rate • S is the signal strength • NT is thermal noise spectral density • Eb/N0 is the ratio of bit energy to noise power spectral density Uinversity of Miami

  10. Call Preblocking Criteria for CDMA systems • TIM : total interference margin TIM = (C + 1)NTW • CIM: current interference margin CIM = IC((C + 1) – N)/(C - N) CIM < TIM for avoiding outage of ongoing calls Uinversity of Miami

  11. Proposed CAC: Variable Parameters • Call arrival rate • Call holding time • Cell dwell time Number of channels/codes remains constant Uinversity of Miami

  12. Proposed CAC System using FAM Uinversity of Miami

  13. Design assumption:Parameter values change gradually, not abruptly Pft Load Uinversity of Miami

  14. Fuzzification of call holding time Membership functions Uinversity of Miami

  15. FAM: Fuzzy Associative Memory Uinversity of Miami

  16. Inference rules from the FAM IF <fuzzy proposition> THEN <fuzzy proposition> Example: IF cell dwell time is VerySmall and call holding time is High THEN slope shall be VeryVeryHigh Uinversity of Miami

  17. Operation of the System • Estimation of the parameters • Fuzzification of call holding time and cell dwell time • Firing of fuzzy rules using FAM inference mechanism • Estimation of pre-blocking load’s slope • Computation of pre-blocking load from the estimated slope Uinversity of Miami

  18. Firing of Rules, and Inference • Cell dwell time = 18 sec, call holding time = 120 sec • IF cell dwell time is Small and call holding time is Medium THEN slope shall be High 1.0 0.7 0.7 Uinversity of Miami

  19. Defuzzification Uinversity of Miami

  20. Evaluation of the FAM-based CAC System: variable call holding time Uinversity of Miami

  21. Evaluation of the FAM-based CAC scheme: Variable cell dwell time Uinversity of Miami

  22. Conclusion and Future directions • FAM-based CAC System can • Keep forced termination at or below desired level FOR • variable call arrival rate • variable call holding time • variable cell dwell time • Future directions • Extend for multiple service classes voice, data, video, and multimedia • Extend for CDMA systems Uinversity of Miami

  23. THANK YOU Uinversity of Miami

  24. ? Comments!!! Uinversity of Miami

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