LTE Fallback Optimization Using Decision Tree

被引:0
|
作者
Al Dorai, Hussein
Al Irkhis, Luay Ali
机构
关键词
LTE; VoLTE; CSFB; DAS; Decision Tree; Machine learning;
D O I
暂无
中图分类号
TP301 [理论、方法];
学科分类号
081202 ;
摘要
The voice call performance is still a challenge in the current 4G networks, providing the most perfect reliability and accessibility of the voice call is the target that all networks are looking for. Most of the networks have 3G layer that is sorted as backup layer for 4G layer, because 4G layer has less coverage which comes as consequence of mainly two reasons: First reason is the 4G frequency is high in order to have greater bandwidth; second reason is the delay of the sites' civil deployment. 5G networks will add more aggressive effects to these two reasons, such as some operators plan to jump directly from 3G to 5G which means more challenges because 5G needs more bandwidth to achieve super performance that can be done only on very high frequencies which have a small footprint. That means the operators are still in need of 3G. This paper develops a new voice call scenario for 4G layer to fallback. The new scenario will shorten the time of mobile-to-mobile setup time which is one of the main keys that operators compete with each other. The call performance will be found in advance to be a condition in order to roll over the new scenario, and that is optimized and based on individual call process by using the decision tree to have optimal decision.
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页码:26 / 30
页数:5
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