xiaodong wang, jun yin and dharma p. agrawal university of cincinnati, cincinnati, ohio

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Effects of Contention Window and Packet Size on the Energy Efficiency of Wireless Local Area Network Xiaodong Wang, Jun Yin and Dharma P. Agrawal University of Cincinnati, Cincinnati, Ohio. IEEE WCNC 2005

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Effects of Contention Window and Packet Size on the Energy Efficiency of Wireless Local Area Network. Xiaodong Wang, Jun Yin and Dharma P. Agrawal University of Cincinnati, Cincinnati, Ohio. IEEE WCNC 2005. Outlines. Introduction Analysis methods Packet transmission probability - PowerPoint PPT Presentation

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Page 1: Xiaodong Wang, Jun Yin and Dharma P. Agrawal University of Cincinnati,  Cincinnati, Ohio

Effects of Contention Window and Packet Size on the Energy Efficiency of

Wireless Local Area Network

Xiaodong Wang, Jun Yin andDharma P. Agrawal

University of Cincinnati, Cincinnati, Ohio.

IEEE WCNC 2005

Page 2: Xiaodong Wang, Jun Yin and Dharma P. Agrawal University of Cincinnati,  Cincinnati, Ohio

Outlines

• Introduction

• Analysis methods– Packet transmission probability– Energy efficiency analysis– Packet error probability

• Simulations

• Conclusions

Page 3: Xiaodong Wang, Jun Yin and Dharma P. Agrawal University of Cincinnati,  Cincinnati, Ohio

Introduction

• Technology in battery capacity hasn’t a big advance in recent years

• Energy efficiency is one of the most important challenging problems in wireless communications

Page 4: Xiaodong Wang, Jun Yin and Dharma P. Agrawal University of Cincinnati,  Cincinnati, Ohio

Introduction (cont.)

• 802.11 standard specifies a power saving mode (PSM)– Synchronized

• This paper concentrate on 802.11 DCF protocol

Page 5: Xiaodong Wang, Jun Yin and Dharma P. Agrawal University of Cincinnati,  Cincinnati, Ohio

Introduction (cont.)

• In 802.11 DCF, energy could be consumed by– Idle listening– Transmission / Receiving

• Packet size

– Collision• Exponential backoff procedure (CW)

Page 6: Xiaodong Wang, Jun Yin and Dharma P. Agrawal University of Cincinnati,  Cincinnati, Ohio

Goal

• Optimize energy efficiency by the analytical model– Optimal contention window– Optimal packet size

Page 7: Xiaodong Wang, Jun Yin and Dharma P. Agrawal University of Cincinnati,  Cincinnati, Ohio

Packet transmission probability

• The probability to send a packet successfully after i times of unsuccessful transmission is Pi

where pu indicates the unsuccessful probability

Page 8: Xiaodong Wang, Jun Yin and Dharma P. Agrawal University of Cincinnati,  Cincinnati, Ohio

• With maximum backoff stage m and retry count m ’

when m’ ≦ m

when m’ > m

Packet transmission probability

Page 9: Xiaodong Wang, Jun Yin and Dharma P. Agrawal University of Cincinnati,  Cincinnati, Ohio

• τis the average probability of each node to send a packet if the medium is idle

• Collision probability p

• Transmission error probability

Packet transmission probability

Page 10: Xiaodong Wang, Jun Yin and Dharma P. Agrawal University of Cincinnati,  Cincinnati, Ohio

• Probabilities of – transmission in one of the other (n-1) node– contends successfully of any other (n-1) node– transmits successfully of any other (n-1) node

Packet transmission probability

Page 11: Xiaodong Wang, Jun Yin and Dharma P. Agrawal University of Cincinnati,  Cincinnati, Ohio

• Average number of unsuccessful transmission

Energy efficiency analysis

Collision

Error

Page 12: Xiaodong Wang, Jun Yin and Dharma P. Agrawal University of Cincinnati,  Cincinnati, Ohio

• Time of success / collision

• Total energy consumption of a successful transmission

Energy efficiency analysis

Backoff Freeze Collision Error Success

Page 13: Xiaodong Wang, Jun Yin and Dharma P. Agrawal University of Cincinnati,  Cincinnati, Ohio

• Time of backoff period

Energy efficiency analysis

Page 14: Xiaodong Wang, Jun Yin and Dharma P. Agrawal University of Cincinnati,  Cincinnati, Ohio

• Average number of transmission overhead can be expressed by

we could get E_FR

Energy efficiency analysis

Page 15: Xiaodong Wang, Jun Yin and Dharma P. Agrawal University of Cincinnati,  Cincinnati, Ohio

• E_SU can simply expressed by

• Finally, we get η

Energy efficiency analysis

Page 16: Xiaodong Wang, Jun Yin and Dharma P. Agrawal University of Cincinnati,  Cincinnati, Ohio

Simulations

• System parameters

Page 17: Xiaodong Wang, Jun Yin and Dharma P. Agrawal University of Cincinnati,  Cincinnati, Ohio

Energy efficiency of DCF under ideal and non-ideal environment

n=20CWmin=32PKT = 1000B

Page 18: Xiaodong Wang, Jun Yin and Dharma P. Agrawal University of Cincinnati,  Cincinnati, Ohio

Effects of CWmin on the energy efficiency of DCF

n=20PKT = 1000B

Page 19: Xiaodong Wang, Jun Yin and Dharma P. Agrawal University of Cincinnati,  Cincinnati, Ohio

Effects of packet size on the energy efficiency of DCF with RTS/CTS

n=20

Page 20: Xiaodong Wang, Jun Yin and Dharma P. Agrawal University of Cincinnati,  Cincinnati, Ohio

Comparison of optimal packet size and optimal CWmin

Page 21: Xiaodong Wang, Jun Yin and Dharma P. Agrawal University of Cincinnati,  Cincinnati, Ohio

Conclusions

• This paper present the analysis of the energy efficiency in 802.11 DCF– Compare the impact of CW and Packet

size

• Packet size can effect the energy efficiency under error-prone channel