Maryam Hamidirad CMPT 820 1

 Introduction  Power Counting Mechanism  Proposed Algorithm  Results  Conclusion  Future Work 2

 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

 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

PtP mode using DCHPtM mode using FACH 5

 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

 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

 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

 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

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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

 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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