Abstract
The explosive growth of communication device and user data has stressed the dense Long Term Evolution Advanced (LTE-A) network. In order to relieve communication congestion in high-load base stations (BSs) in the downlink network, it is necessary for network operators to balance these loads meanwhile guarantee the quality of service (QoS). In this work, a robust \(Min-Max\) generalized linear fractional programming (GLFP) model about power optimization under QoS constraints is established for load balancing, where signal coverage and user access are mathematically described by sigmod function and softmax function, respectively. Since GLFP is a well-known NP-hard problem, a heuristic algorithm named generalized bisection method (GBM) is proposed and its time complexity is at most \(O(MN^2\log \frac{W}{\epsilon })\). Simulation results demonstrate the effectiveness and rapidity of the proposed algorithm.
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Acknowledgments
Thanks to China Mobile Group Beijing Company Limited (CMBJ) and Datang Telecom Technology and Industry Group (DTmobile).
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Gui, J., Yang, W., Gao, S., Jiang, Z. (2018). A Robust Power Optimization Algorithm to Balance Base Stations’ Load in LTE-A Network. In: Tang, S., Du, DZ., Woodruff, D., Butenko, S. (eds) Algorithmic Aspects in Information and Management. AAIM 2018. Lecture Notes in Computer Science(), vol 11343. Springer, Cham. https://doi.org/10.1007/978-3-030-04618-7_15
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DOI: https://doi.org/10.1007/978-3-030-04618-7_15
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