Performance Enhancement of Multirate IEEE WLANs with Geographically Scattered Stations 1 Duck-Yong Yang, 2 Tae-Jin Lee, 3 Kyunghun Jang, 3 Jin-Bong Chang, and 4 Sunghyun Choi 1 Information Technology lab, LG Enectronics 2 School of Information and Communication Engineering, Sungkyunkwan University 3 Communications and Networking Lab, Samsung 4 School of Electrical Engineering, Seoul National University IEEE Tran. on Mobile Computing, Vol. 5, No. 7, July 2006

Outline Introduction Introduction Modeling of scattered stations in WLANs Modeling of scattered stations in WLANs Proposed protocol Proposed protocol Performance evaluation Performance evaluation Simulation results Simulation results Conclusion Conclusion

3 Introduction The performance of a WLAN is degraded by stations using low rate transmission The performance of a WLAN is degraded by stations using low rate transmission Performance of stations with high rate transmission is heavily degraded Performance of stations with high rate transmission is heavily degraded –Performance anomaly

Goal of this paper This paper interests in This paper interests in –Modeling the WLAN incorporating stations with multiple transmission rate –Analyzing performance anomaly

Mathematical model

A WLAN with geographically scattered stations

Retry count vs. backoff stages i : group k : backoff stage w i : backoff window u i : max backoff stage

State transmission probabilities of the Markov chain Decrease backoff counter by 1 (idle) Sense busy Transmission Collision Successful transmission Drop a frame

Steady state distribution ( 穩 態分佈 ) of a Markov chain Collision probability in group i

Probability of a station in i transmits or senses busy during a slot

Probability of a station in i has transmission collision

Probability that the channel is busy in a slot All stations in each group do not transmit

Probability of a successful transmission

Collisions among different groups

Upper i-heterogeneous collisions

Lower i-heterogeneous collisions

Probability of i- homogeneous collisions

Probability of i- heterogeneous collisions

Other equations involve in mathematical model

Proposed protocol

1. Different initial backoff window size for different group 2. Different frame size for different group 3. Different max backoff stage 4. Combination of 1. and 2.

Performance evaluation

A network topology for performance evaluation

Parameters used in performance evaluation

Saturation throughput of each group with different backoff window

Total throughput with different backoff window

Throughput of each group with different frame size

Total throughput with different frame size

Throughput with different max backoff stage

Total throughput with different max backoff stage

Throughput with different initial backoff window and frame size

Total throughput with different initial backoff window and frame size

Summary Throughput gain is not significant when reducing the size of the frames for low-rate stations Throughput gain is not significant when reducing the size of the frames for low-rate stations Different max backoff stages for different groups have very little impact Different max backoff stages for different groups have very little impact

Simulation results

environments OPNET 10.0A OPNET 10.0A RTS threshold=3000 B RTS threshold=3000 B –RTS/CTS are disable Retry limit is 7 Retry limit is 7

Throughput: analysis and simulation results

BSS with one station moving away from AP

Throughput when there is one moving station

Total throughput when there is one moving station

Throughput as the traffic load increases from 0.5 to 4 Mbps

Total throughput as the traffic load increases from 0.5 to 4 Mbps

Throughput vs. IEEE e with TXOP

Conclusions This paper This paper –investigates the phenomenon analytically using a Markov chain –Derives the saturation throurghput –Proposes remedies to mitigate the performance anomaly

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