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15 March 2005
Multi-Standard Convergence in Mobile Terminals
(Master Thesis)
Presenter: Shakeel Ahmadvenue: GK Workshop Waldau, Germany.
Supervisors: M.Sc. Chunjiang YinProf. Dr. Hermann Rohling
Department of TelecommunicationTechnical University Hamburg Harburg
Presenter: Shakeel Ahmad
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Contents
• Introduction and Motivation
• Tasks
• Convergence Manager
• Simulation Scenario and Considerations
• Standard Selection Algorithms
• Implementation in MLDesigner
• Simulation Results
• Conclusions
Presenter: Shakeel Ahmad
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Introduction & Motivation
• An increased demand of mobile Internet
• A wired-like Internet service while on move… a big challenge
• The challenge seems hard to be met with pure 3G deployment
• WLAN a good candidate but suffers from low coverage
• In 4G system one proposal considers the convergence of the existing wireless standards
Convergence Manager
Presenter: Shakeel Ahmad
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Introduction & Motivation (2)
• Overall performance can be improved
• Potential benefits for end-users, network operator and the service provider
Presenter: Shakeel Ahmad
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Tasks
• Definition of a simulation scenario deploying multi-standard convergence
• Implementation of simulation scenario in MLDesigner• A quantitative analysis of the potential benefits offered
by multi-standard convergence only in mobile terminals– Standard selection algorithms and comparison
– Delay performance
– Request discarding rate performance
Presenter: Shakeel Ahmad
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Convergence Manager• Function:
– Enables the convergence of wireless standards.
• Location:– A crucial issue from architecture point of view– Some proposed locations for Convergence Manager (CM):
Only in Mobile Terminal Only in the network side Can be split into a network and Mobile Terminal part
Standard Selection
Presenter: Shakeel Ahmad
7
Simulation Scenario & Considerations• A busy road about 1.5km long in a city and is crossed by some other roads
• Technological Scenario– Two standards, HSDPA (for UMTS) and HL2 (WLAN) were considered.
– HSDPA is available throughout and HL2 is available at crossings (100 m radius)
• User Scenario– Uniform spatial distribution along the road, moving with a constant speed.
– Users make request for a service according to Poisson process
• Service Scenario
– Generic file download service
Presenter: Shakeel Ahmad
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Contents
• Introduction and Motivation
• Tasks
• Convergence Manager
• Simulation Scenario and Considerations
• Standard Selection Algorithms
• Implementation in MLDesigner
• Simulation Results
• Conclusions
Presenter: Shakeel Ahmad
9
Switched Algorithm–Upon arriving a request, the highest data rate bearer is selected. –Download starts immediately and can take place via multiple standards–Switching between standards while mid of file download (complications involved)
Standard Selection Algorithms
UMTS Only UMTS OnlyUMTS / HL2 UMTS / HL2
Request
Request
Request
Request
Request
Request
Request
RequestRequestRequest
time
time
time
Switched
Current
Location
UMTS Only
Road
Three algorithms for standard selection were considered [1]
[1] MultiStandard approach for enhanced communications service provision to rail commuter IST Mobile Communications Summit, Lyon, France.
Location Algorithm–Uses additional knowledge of users‘s mobility, geographical coverage of standards and the mean data rate, to make more intelligent decision–Download may not start immediately and always takes place via single standard
Current Algorithm–Upon arriving a request, the highest data rate bearer is selected. –Download starts immediately and takes place via single standard
Initial delay
Presenter: Shakeel Ahmad
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Contents
• Introduction and Motivation
• Tasks
• Convergence Manager
• Simulation Scenario and Considerations
• Standard Selection Algorithms
• Implementation in MLDesigner
• Simulation Results
• Conclusions
Presenter: Shakeel Ahmad
13
Multi-Standard Single-User Case• Request arrival Process is Poisson with mean rate of 1/10 requests per second, File
Size Fixed• It is supposed that user is moving with constant speed (10 m/s), Red Signal On
Probability=0.0• Mean Initial Delay Vs File Size & Mean Total File Download Time Vs File Size
Presenter: Shakeel Ahmad
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Multi-Standard Single-User Case (2)• Request arrival is Poisson with mean rate of 1/10 requests per second, File Size
Fixed• It is supposed that user is moving with constant speed (10 m/s), Red Signal On
Probability=0.0• Mean Request Discarding Rate Vs File Size
Presenter: Shakeel Ahmad
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HotSpot Effect• Request arrival Process with mean 1/10 requests per second, File Size Fixed
• It is supposed that user is moving with constant speed (10 m/s), Red Signal On Probability =0.1 (Red Signal is On for 15 sec)
• Mean Total Download Time Vs File Size
Crossing points are good place to install HL2 APs
Presenter: Shakeel Ahmad
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Multi-Standard Multi-User Case• Request arrival Process with mean 1/10 requests per second, File Size = 125 KB
• Users spatial distribution is uniform along the road,
• It is supposed that users are moving with constant speed (10 m/s), Red Signal On Probability =0.0
• Mean Total Download Time & Mean Request Discarding Rate Vs numUsers
Presenter: Shakeel Ahmad
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Problem with Location Algorithm
• Proposed Solution:
History Based Location AlgorithmMean data rate for the current file download via standard x is inferred from previous file download via standard x.
UMTS Only UMTS OnlyUMTS / HL2 UMTS / HL2
Request RequestRequestRequest
time
Location
UMTS Only
Road
• Wrong data rate estimation leads to wrong standard selection
Presenter: Shakeel Ahmad
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Performance of History Based Location Algorithm
• Improvement by applying History Based Location Algorithm
• Mean Total Download Time & Mean Request Discarding Rate Vs numUsers
Presenter: Shakeel Ahmad
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Conclusion
• Benefits of Convergence Manager– Improved QoS and System performance
– Easy to realize – no standardization efforts
• Comparison of standard selection algorithms– Switched algorithm lower bound of performance - Location algorithm closest
match
– Location Algorithm – Poor performance in multi-users
– History Based Location Algorithm-one Possible Solution
Presenter: Shakeel Ahmad
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Conclusion (2)
• Modular and Extendable Simulation Setup– A useful off-shelf component
– The framework can be easily extended e.g., for other wireless standards, new standard selection algorithms and new scheduling policies can be incorporated and tested easily
• Future Work– The assumption that CM knows precisely about user‘s mobility, location and
geographical coverage of wireless standards may not be realistic – Source of error.
– New standard-selection algorithms for different scenarios and services