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Maryam Hamidirad mhamdirad@sfu.ca CMPT 820 1
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Introduction Power Counting Mechanism Proposed Algorithm Results Conclusion Future Work 2
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Multimedia Broadcast/Multicast Service (MBMS) It provides an efficient way to broadcast data to multiple users in cellular networks It has been realized by third generation partnership project (3GPP) 3
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MBMS has two modes Point to Point (PTP) one DCH established for each UE in the Cell Point to Multipoint (PTM) one FACH covering the whole Cell and shared by all the UEs within 4
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PtP mode using DCHPtM mode using FACH 5
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Parameters retrieval Distance to base station Number of users QOS requirements Power level computation for FACH and DCH Transport channel with minimum power selected Check parameters to adapt to system dynamics 6
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Define ten ranges for each cell For each range compute the power needed to cover the range using FACH Cluster remaining nodes Compute the power to send to cluster heads Find the minimum power of all ranges 7
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Cluster nodes based on : Distance of the node to base station : Number of nodes lying in the transmission range of the node :The extent to which the cluster head lays in the same range related to other cluster heads. 8
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We have run power counting mechanism and our clustering algorithm Using MATLAB as a simulation tool Varying users population of 20 to 200 with uniform distribution Both scenarios has been tested 1000 times Run clustering algorithm for varying weights changing 0.1 each time 10
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For user population more than 30, clustering algorithm will outperform current power counting mechanism as much as 20% Increases the threshold to switch to FACH only mode which uses high power Current Power Counting Mechanism is 60 Using Clustering algorithm is 140 11
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We have proposed clustering algorithm based on parameters that consider base station power Clustering decreases the number of users that should receive MBMS from base station Cooperation of WLAN and LTE improves base station power saving as much as 20%. 13
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Using more power for user population less than 30 is an unresolved issue. Using different users distribution like Gaussian to test the results. Switching cluster heads periodically to guarantee the fairness of our approach Using NS-3 as a network simulator to verify the results we get using MATLAB 14
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