Performance and Analysis of WiMAX Network with Different QoS Scheduling Algorithms
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Master of Science Thesis Yiyu Zhao 19 July,2007
Advisors: Supervisor: Committee Members:
Ir. Bao Linh Dang, Dr. Rangarao Venkatesha Prasad Prof. Ignas Niemegeers Dr.Ir.Anthony Lo Dr.Ir.Nikookar
Introduction The IEEE 802.16 Standard WiMAX Modeling in OPNET Scheduling Algorithms Simulations and Results Analysis Contributions and Future Work
1 Wireless and Mobile Communications (WMC) Group Department of Electrical Engineering 2
Introduction
Introduction Motivation: • Verify the correctness of WiMAX model in OPNET • Implement the different scheduling algorithms • Compare the performance of the network with different scheduling algorithms • and verify which algorithm is suitable to a specific traffic class
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WiMAX Forum-
Worldwide Interoperability for Microware Access IEEE 802.16-2005 Standard
Last-mile wireless solution 2-60 GHz with 5 different PHY specifications QoS Support
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IEEE 802.16 Standard • • • • • •
Introduction IEEE 802.16 Standard WiMAX Modeling in OPNET Scheduling Algorithms/Architectures Simulation and Results Analysis Conclusion and Future Work
OFDMA MAC frame structure •
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Time-Frequency domain
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IEEE 802.16 Standard Scheduling Services
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-UGS: Unsolicited Grant Service(e.g. Voice) -rtPS: real-time Polling Service (e.g. Video) -nrtPS: non-real-time Polling Service (e.g. FTP) -BE: Best-effort (e.g. HTTP)
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QoS Architecture
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- The scheduler in BS is not specified in the standard
Introduction IEEE 802.16 Standard WiMAX Modeling in OPNET Scheduling Algorithms/Architectures Simulation and Results Analysis Conclusion and Future Work
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WiMAX Modeling in OPNET
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WiMAX Modeling in OPNET WiMAX MAC Process Model
WiMAX Model Structure
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Data Plane •
Data transmission
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Receive and manage all packets
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Transfer control packet to control plane
Control Plane BS Control •
Admission control
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Scheduling Bandwidth request
SS Control •
Setup/teardown uplink connection
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WiMAX Modeling in OPNET •
Validation – compare the theoretical and simulation maximum throughput
Introduction IEEE 802.16 Standard WiMAX Modeling in OPNET Scheduling Algorithms/Architectures Simulation and Results Analysis Conclusion and Future Work
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Scheduling Algorithm-WRR
Scheduling Algorithm-EDF
Weighted Round-Robin
Earliest Deadline First
•Principle: based on Weight •Weight =
Wi = ri / ∑ ri
•Principle: Earliest Deadline scheduled
( ri =min_reserved_traffic_rate)
•Dealine = Max latency = Max delay
•QoS parameter : Min reserved traffic rate
q1
q2
•QoS Parameter : Max latency
•1st round: q1
q3
q1
q2
q3
•2nd round: q2
•1st : q3
•3nd round: q3
•2nd: q1 •3rd: q2
Whole Bandwidth Whole Bandwidth
w1=50%
w2=20%
w3=30%
d1= 20
d2= 40
d3=10
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Scheduling Algorithm-MDRR
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Scheduling Algorithm-UPS
Modified Deficit Round-Robin
Uplink Packet Scheduling
•Based on Deficit Round-Robin
• Strict scheduling Algorithm
•Deficit counter: the remaining credits of queue
• Integrate different scheduling algorithms
•Principle: Deficit counter is enough to transmit a packet •1st packet size=300 -> q2, dc2 = 450-300 = 150
q1
q2
q3
•2nd packet size =200 -> q1, dc1 = 200-200 = 0
Whole Bandwidth
dc1= 200
dc2= 450
dc3=100
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Simulation and Results Analysis Scenario1:
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real-time Polling Service (rtPS)
Service Class and QoS parameter: Max-latency • Gold1- 30ms • Gold2- 70ms
Introduction IEEE 802.16 Standard WiMAX Modeling in OPNET Scheduling Algorithms/Architectures Simulation and Results Analysis Conclusion and Future Work
Introduction IEEE 802.16 Standard WiMAX Modeling in OPNET Scheduling Algorithms/Architectures Simulation and Results Analysis Contributions and Future Work
• Verify the correctness of the OPNET WiMAX model • Implement various scheduling algorithms/architectures for WiMAX • Examine and verify EDF is suitable for rtPS, WRR is suitable for nrtPS • Examining the UPS outperforms MDRR
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Future Work WiMAX Model part: • Optimize the backoff mechanism for BE traffic in WiMAX model Algorithm part: • Optimize UPS algorithm to provide fairness between different traffics
Thanks for your attention!
Simulation part: • Observe more different and complex scenarios • Analyses other performance metrics, like bandwidth utilization