Multi-Standard Convergence in Mobile Terminals

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Information about Multi-Standard Convergence in Mobile Terminals
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Published on September 25, 2007

Author: lokesht

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Multi-Standard Convergence in Mobile Terminals(Master Thesis)Presenter: Shakeel Ahmadvenue: GK Workshop Waldau, Germany.Supervisors: M.Sc. Chunjiang YinProf. Dr. Hermann RohlingDepartment of TelecommunicationTechnical University Hamburg Harburg:  15 March 2005 Multi-Standard Convergence in Mobile Terminals (Master Thesis) Presenter: Shakeel Ahmad venue: GK Workshop Waldau, Germany. Supervisors: M.Sc. Chunjiang Yin Prof. Dr. Hermann Rohling Department of Telecommunication Technical University Hamburg Harburg Contents:  Contents Introduction and Motivation Tasks Convergence Manager Simulation Scenario and Considerations Standard Selection Algorithms Implementation in MLDesigner Simulation Results Conclusions Introduction & Motivation:  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 Introduction & Motivation (2):  Introduction & Motivation (2) Overall performance can be improved Potential benefits for end-users, network operator and the service provider Tasks:  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 Convergence Manager:  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 Simulation Scenario & Considerations:  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 Contents:  Contents Introduction and Motivation Tasks Convergence Manager Simulation Scenario and Considerations Standard Selection Algorithms Implementation in MLDesigner Simulation Results Conclusions Standard Selection Algorithms:  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 Only UMTS / HL2 UMTS / HL2 Request Request Request Request Request Request Request Request Request Request 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 Implementation in MLDesigner:  Implementation in MLDesigner Simulation Scenario Implementation in MLDesigner (2):  Implementation in MLDesigner (2) An instance of Mobile Terminal Contents:  Contents Introduction and Motivation Tasks Convergence Manager Simulation Scenario and Considerations Standard Selection Algorithms Implementation in MLDesigner Simulation Results Conclusions Multi-Standard Single-User Case:  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 Multi-Standard Single-User Case (2):  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 HotSpot Effect:  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 Multi-Standard Multi-User Case:  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 Problem with Location Algorithm:  Problem with Location Algorithm Proposed Solution: History Based Location Algorithm Mean data rate for the current file download via standard x is inferred from previous file download via standard x. UMTS Only UMTS Only UMTS / HL2 UMTS / HL2 Request Request Request Request time Location UMTS Only Road Wrong data rate estimation leads to wrong standard selection Performance of History Based Location Algorithm:  Performance of History Based Location Algorithm Improvement by applying History Based Location Algorithm Mean Total Download Time & Mean Request Discarding Rate Vs numUsers Conclusion:  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 Conclusion (2):  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 Slide21:  Thanks for listening

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