%0 Journal Article %1 EXSY:EXSY12120 %A Kwong, Chiew Foong %A Chuah, Teong Chee %A Tan, Su Wei %A Akbari-Moghanjoughi, Ayyoub %D 2016 %J Expert Systems %K A.Akbari-Moghanjoughi Handover MAC %N 1 %P 30--45 %R 10.1111/exsy.12120 %T An adaptive fuzzy handover triggering approach for Long-Term Evolution network %U http://dx.doi.org/10.1111/exsy.12120 %V 33 %X To cope with the increasing demand for efficient data delivery, self-organizing networks have been introduced in the Long Term Evolution (LTE) system to provide autonomous and flexible mobility management. The existing handover triggering scheme for LTE is not flexible enough to incorporate new performance metrics, and it introduces handover latency. There are studies on non-conventional handoff algorithms for LTE applications, for instance, the fuzzy logic approach. However, the fuzzy logic approach needs regular manual tuning to constantly produce optimal output. In this paper, we address this issue by proposing an adaptive fuzzy logic-based handoff decision algorithm, which can cope with environmental changes and improve efficiency by reducing human intervention. Performance results show that the proposed algorithm can reduce unnecessary handovers by about 20% compared with the fuzzy logic and conventional LTE handover triggering scheme, leading to reduced packet loss rates.

@article{EXSY:EXSY12120, abstract = {To cope with the increasing demand for efficient data delivery, self-organizing networks have been introduced in the Long Term Evolution (LTE) system to provide autonomous and flexible mobility management. The existing handover triggering scheme for LTE is not flexible enough to incorporate new performance metrics, and it introduces handover latency. There are studies on non-conventional handoff algorithms for LTE applications, for instance, the fuzzy logic approach. However, the fuzzy logic approach needs regular manual tuning to constantly produce optimal output. In this paper, we address this issue by proposing an adaptive fuzzy logic-based handoff decision algorithm, which can cope with environmental changes and improve efficiency by reducing human intervention. Performance results show that the proposed algorithm can reduce unnecessary handovers by about 20% compared with the fuzzy logic and conventional LTE handover triggering scheme, leading to reduced packet loss rates.}, added-at = {2017-04-17T10:53:10.000+0200}, author = {Kwong, Chiew Foong and Chuah, Teong Chee and Tan, Su Wei and Akbari-Moghanjoughi, Ayyoub}, biburl = {https://www.bibsonomy.org/bibtex/2417a44b493291c3a2502ed323f69e646/ayyoubakbari}, description = {An adaptive fuzzy handover triggering approach for Long-Term Evolution network - Kwong - 2015 - Expert Systems - Wiley Online Library}, doi = {10.1111/exsy.12120}, interhash = {8864e159a9ba0c247a02f549d358a963}, intrahash = {417a44b493291c3a2502ed323f69e646}, issn = {1468-0394}, journal = {Expert Systems}, keywords = {A.Akbari-Moghanjoughi Handover MAC}, number = 1, pages = {30--45}, timestamp = {2020-11-06T21:19:54.000+0100}, title = {An adaptive fuzzy handover triggering approach for Long-Term Evolution network}, url = {http://dx.doi.org/10.1111/exsy.12120}, volume = 33, year = 2016 }