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Performance Testing of Rate Adaptation Algorithms in WLAN

Performance Testing of Rate Adaptation Algorithms in WLAN. Author: Muhammad Sohail Khan Supervisor: Prof. Rikku J ä ntti Comm Lab TKK. Wireless Local Area Networks. Growing popularity and demand due to mobility Easy to deploy with low costs Operates in Unlicensed band

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Performance Testing of Rate Adaptation Algorithms in WLAN

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  1. Performance Testing of Rate Adaptation Algorithms in WLAN Author: Muhammad Sohail Khan Supervisor: Prof. Rikku Jäntti Comm Lab TKK

  2. Wireless Local Area Networks • Growing popularity and demand due to mobility • Easy to deploy with low costs • Operates in Unlicensed band • Provide access to high speed data and multimedia services

  3. IEEE 802.11 Multirate Capability • IEEE 802.11 standard is most mature and accepted technology for broadband access • Current specifications provides multiple transmission rates at PHY layer • 802.11b PHY supports 1,2,5.5 and 11 Mbps • 802.11a/g PHY support 6,9,12,18,24,36,48 and 54 Mbps

  4. Optimal Data Rate Selection • Different Modulation Schemes for the PHY Data Rates • SNR and BER requirement • Highly volatile nature of Wireless channel due to pathloss, fading and interference • Data rate selection in WLAN • Fixed • Auto

  5. Contribution to Thesis • Experimental Testing of three Rate Adaptation Algorithms • Designing of a realistic testbed • Channel Simulator • 802.11 Task Group n Channel Models • Analyze throughput performance under varying channel conditions

  6. Rate Adaptation Mechanism • Selection of optimal PHY Data Rate according to Varying wireless Channel conditions • Estimation of channel • Data Rate selection • No specifications in 802.11 standard • Implementation manufacturer specific

  7. Rate Adaptation Mechanisms • Statistics Based Mechanisms • Decision at sender • Estimators : frame errors, throughput calculation • Examples: ARF, AARF • SNR Based Mechanisms • Decision at receiver • Estimators: SNR, RSSI • Examples: RBAR

  8. Onoe • Belongs to Statistics based mechanism • Uses credits as a function of number of Successful and erroneous transmission/retransmission over an observation period • Implementation detail • starts at 24 Mbps for 802.11a/g and 11Mbps for 802.11b • Updates credits in fixed observation period of 1 second • Credits incremented if less then 10% packets needed retry else decrease the credits • Switch to next higher Data Rate when credits value reaches 10

  9. Sample Rate • Throughput based mechanism • Increases throughput by sending packets at Data Rate with minimum average transmission time • Implementation Detail • Starts with highest Data Rate • If more then 4 retransmissions decrease until packet is sent • Periodically sends 10th packet at randomly selected Data Rate • Calculate average transmission time for probe packets • Switch to Data Rate with lowest average transmission time

  10. AMRR (Adaptive Multi Rate Retry) • Retry Based Mechanism which adaptively increases threshold for rate increase • Uses Binary Exponential Backoff to adapt length of period for rate and transmission parameter • Implementation Detail • Uses 4 pairs of Data Rate and Transmission Counters (r0/c0, r1/c1, r2/c2 and r3/c3) • Starts with r0 and if transmission fails retry c0 times and switch to r1 • r3 always minimum rate • r1 and r2 set to immediate lower rate then r0

  11. Experimental Testbed • Reliable and Controlled test environment through use of PROPSim C2 Channel Simulator • Configurable • Repetitive • Open Source MadWiFi Drivers for WLAN Adaptors • Traffic generation tool IPerf

  12. Experimental Testbed

  13. Channel Models • Channel Models Proposed by 802.11 Task Group n • Delay Profile of the Channel Models • Model A: representative of a typical office environment, non-line of sight (NLOS) conditions with 50 ns rms delay spread • Model B: representative of a large open space and office environment, NLOS conditions with 100 ns rms delay spread. • Model C: representative of large open space (indoor and outdoor), NLOS conditions with 150 ns rms delay spread. • Model D: representative of large open space (indoor and outdoor), same as Model C, but for LOS conditions. A 10 dB spike at zero delay with rms delay spread of 140 ns.

  14. UDP Throughput vs Pathloss For Channel Models A,B,C and D

  15. Loss Ratio and TCP throughput vs Pathloss for Channel Model C

  16. Conclusions • AMRR gives worst performance in terms of throughput. • Switches between too many Data Rates • Onoe Performs better at low pathloss value • Conservative in nature. • Sample outperforms Onoe and AMRR at High pathloss value

  17. The End Thank You!

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