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P-DCF :Enhanced Backoff Scheme for the IEEE802.11 DCF

P-DCF :Enhanced Backoff Scheme for the IEEE802.11 DCF. Author: Nakiung Choi, Yongho Seok , Yanghee Choi, Korea. 林奐均 , 96th, MCSE, TMUE. I. INTRODUCTION. The original IEEE802.11 DCF suffers from frequent packet collisions under high traffic load.

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P-DCF :Enhanced Backoff Scheme for the IEEE802.11 DCF

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  1. P-DCF :Enhanced Backoff Scheme for the IEEE802.11 DCF Author: Nakiung Choi, Yongho Seok , Yanghee Choi, Korea 林奐均, 96th, MCSE, TMUE

  2. I. INTRODUCTION • The original IEEE802.11 DCF suffers from frequent packet collisions under high traffic load. • There have been several backoff schemes to improve CSMA/CA, such like : • MACAN • EIED (Exponential Increase Exponential Decrease ) , • MIMD (Multiplicative Increase and Multiplicative Decrease) • LMILD (Linear/Multiplicative Increase and Linear Decrease)

  3. I. INTRODUCTION • However, most of previous studies focus on setting Contention Window. • This paper proposed a novel backoff scheme that overhearing others’ transmission and utilizing the transmission history . • This scheme called : P-DCF (Predictive DCF)

  4. II. MOTIVATION

  5. Node B [24(31-7), 31] III.PREDICTIVE DCF Supposed CW is 31 • A. Basic Operation • Utilizes the past history of successful transmissions. • Calculates the number of idle time slots (ITS) • Backoff time Range: [CW-ITS, CW] • Assuming that a mobile node adjusts its current contention window depending on the number of competing node. Node C [27(31-4), 31]

  6. III.PREDICTIVE DCF • B. Optimizing P-DCF • Getting information of channel usage by overhearing others’ transmission in its neighborhood. • Each node has its own (Predictive backoff counting table) • The mobile node divide its range into several • Sub-range has different packet collision probability P-BCT sub-range

  7. III.PREDICTIVE DCF

  8. III.PREDICTIVE DCF

  9. IV.PERFORMANCE EVALUATION

  10. V.CONCLUSION • Advantage of this scheme: reduce the collision probability by predicting other’s backoff times • Better throughput up to 17% • A study on how to derive the predictive distribution from a mobile node’s P-BCT is in progress • Further research maybe required to optimize P-DCF.

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