LTE handover parameters optimization using Q-learning technique

Assem Abdelmohsen, Mohamed Abdelwahab, Mohamed Adel, M. Saeed Darweesh, Hassan Mostafa

Research output: Chapter in Book/Report/Conference proceedingConference contribution

20 Scopus citations

Abstract

Optimization of the LTE network is crucial to obtain the best performance. The handover margin (HOM) and time to trigger (TTT) should be chosen so that the system will have minimum number of handovers per user per second, minimum system delay, and maximum throughput. In this paper a new handover optimization algorithm for long term evolution (LTE) network based on Q-learning optimization is presented. The proposed algorithm operates by testing different values of HOM and TTT then observes the output performance corresponding to the values of these parameters, and it eventually selects the values that produce the best performance. The proposed handover optimization technique is evaluated and compared to previous work. Q-learning achieves minimum average number of handover per user and also has maximum throughput than the fuzzy logic optimization technique.
Original languageEnglish (US)
Title of host publication2018 IEEE 61st International Midwest Symposium on Circuits and Systems (MWSCAS)
PublisherIEEE
Pages194-197
Number of pages4
ISBN (Print)9781538673928
DOIs
StatePublished - Jan 24 2019
Externally publishedYes

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