User Capacity Optimization Using The Mobility Load Balancing Algorithm For Downlink Data Long Term Evolution
DOI:
https://doi.org/10.33019/jurnalecotipe.v12i1.4532Keywords:
Long Term Evolution, Mobile Load Balancing, Resource, ThroughputAbstract
The increasing number of users in a Long Term Evolution (LTE) network often decreases network performance. A cell that has high traffic experiences a decline in network performance due to unavailable resources for certain users, while in cells with low traffic, the use of resources in these cells is inefficient. The mobility load balancing (MLB) algorithm balances the intercellular loads in an LTE network and improves the performance by distributing part of the load in a high traffic cell to neighboring cells that have low loads. An activated MLB will detect the network load and calculate the available resource for each cell to determine which cells are overloaded. The MLB will consider the candidate cell where the load could be distributed. MLB simulation results show that the application of MLB has succeeded in reducing the percentage of unsatisfied users by 9.4% and increasing throughput system to 5.617 Mbps.
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