Ekong, E. E. and Adewale, Adeyinka A. and Ben-Obaje, A. and Alalade, G. M and Ndujiuba, C. N. (2019) Performance Comparison of ANN Training Algorithms for Hysteresis Determination in LTE networks. In: International Conference on Engineering for Sustainable World, 2019, Online.
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Abstract
Long-Term Evolution (LTE) network is an improved standard for mobile telecommunication system developed by the 3rd Generation Partnership Project (3GPP) requires an efficient handover framework which would reduce hysteresis and improve quality of service (QoS) of subscribers by maximizing scarce radio resources. This paper compares the performance of two ANN prediction algorithms (Levenberg- Marquadt and Bayesian regularization) based on received signal strength (RSS) and the hysteresis margin parameters for neuro-adaptive hysteresis margin reduction algorithm. The Bayesian regularization algorithm had a lower mean error when compared with the Levenberg-Marquadt (LM) prediction algorithm and as such a better option for neuroadaptive hysteresis margin reduction algorithm.
| Item Type: | Conference or Workshop Item (Paper) |
|---|---|
| Subjects: | T Technology > TK Electrical engineering. Electronics Nuclear engineering |
| Divisions: | Faculty of Engineering, Science and Mathematics > School of Electronics and Computer Science |
| Depositing User: | Mrs Patricia Nwokealisi |
| Date Deposited: | 09 Oct 2020 12:21 |
| Last Modified: | 09 Oct 2020 12:21 |
| URI: | http://eprints.covenantuniversity.edu.ng/id/eprint/13648 |
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