User Capacity Optimization Using The Mobility Load Balancing Algorithm For Downlink Data Long Term Evolution

Authors

DOI:

https://doi.org/10.33019/jurnalecotipe.v12i1.4532

Keywords:

Long Term Evolution, Mobile Load Balancing, Resource, Throughput

Abstract

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.

Downloads

Download data is not yet available.

References

S. Chen, S. Sun, Y. Wang, G. Xiao, and R. Tamrakar, “A comprehensive survey of TDD-based mobile communication systems from TD-SCDMA 3G to TD-LTE(A) 4G and 5G directions,†2015. doi: 10.1109/CC.2015.7084401.

M. Escheikh, H. Jouini, and K. Barkaoui, “Modeling, implementation and performance analysis of mobility load balancing for lte downlink data transmission,†International Journal of Computer Networks and Communications, vol. 8, no. 5, 2016, doi: 10.5121/ijcnc.2016.8505.

E. Gures, I. Shayea, M. Ergen, M. Hadri Azmi, and A. A. El-Saleh, “Machine Learning-Based Load Balancing Algorithms in Future Heterogeneous Networks: A Survey,†IEEE Access , vol. 10, pp. 37689–37717, 2022.

M. Jaber, Z. Dawy, N. Akl, and E. Yaacoub, “Tutorial on LTE/LTE-A Cellular Network Dimensioning Using Iterative Statistical Analysis,†IEEE Communications Surveys and Tutorials, vol. 18, no. 2, 2016, doi: 10.1109/COMST.2015.2513440.

G. Ku and J. M. Walsh, “Resource allocation and link adaptation in LTE and LTE advanced: A tutorial,†IEEE Communications Surveys and Tutorials, vol. 17, no. 3, 2015, doi: 10.1109/COMST.2014.2383691.

A. Lobinger, S. Stefanski, T. Jansen, and I. Balan, “Load balancing in downlink LTE self-optimizing networks,†in IEEE Vehicular Technology Conference, 2010. doi: 10.1109/VETECS.2010.5493656.

C. Cox, An Introduction to LTE: LTE, LTE-Advanced, SAE, VoLTE and 4G Mobile Communications: Second Edition, vol. 9781118818039. 2014. doi: 10.1002/9781118818046.

S. Shukry and Y. Fahmy, “Mobility robustness self-organizing network handover scheme for LTE-Advanced,†in 2016 33rd National Radio Science Conference (NRSC), Aswan, Egypt: IEEE, Feb. 2016.

S. Rathi, N. Malik, N. Chahal, and S. Malik, “Throughput for TDD and FDD 4 G LTE Systems,†International Journal of Innovative Technology and Exploring Engineering (IJITEE), vol. 3, no. 12, pp. 73–77, May 2014.

“TDD/FDD LTE Convergence,†Feb. 2015. Accessed: Feb. 15, 2025. [Online]. Available: https://www.gtigroup.org/Uploads/File/2022/03/14/u622f1286b4ac1.pdf

S. Tanwar, H. Khujamatov, B. Turumbetov, E. Reypnazarov, and Z. Allamuratova, “Designing and Calculating Bandwidth of the LTE Network for Rural Areas,†Int J Adv Sci Eng Inf Technol, vol. 12, no. 2, pp. 437–445, 2022, doi: 10.18517/ijaseit.12.2.14950.

Downloads

Published

04/10/2025

How to Cite

[1]
M. Miranti, L. Sari, M. Doris, S. Alam, and I. Surjati, “User Capacity Optimization Using The Mobility Load Balancing Algorithm For Downlink Data Long Term Evolution”, JurnalEcotipe, vol. 12, no. 1, pp. 103–112, Apr. 2025, doi: 10.33019/jurnalecotipe.v12i1.4532.

Most read articles by the same author(s)