… We analyze and optimize five parameters namely A5-time to … received power (RSRP), handover
success rate (HOSR) and load … complexity, we leverage machine learning to quantify the …

… In this research, we propose a learning-based handover optimization for the Internet of …
To accomplish this, we make use of machine learning algorithms to learn from vehicle interac…

… 1) VISUAL DATA AIDED HANDOVER OPTIMIZATION Successive generations of cellular …
, received power, etc., for network design and optimization. However, the use of mm-wave and …

… validate and evaluate handover algorithms that … machine learning backed, proactive,
handover algorithm that uses multiple metrics to predict the future state of the network and optimize …

… a machine learning method for learning the optimal time and destination for handovers in
5G radio networks, as well as how to use the learned model to trigger handovers based on the …

… topology, random mobility, and irregular deployment of small cells, and we show that the
proposed algorithm can transiently optimize handover parameters to guarantee the target …

… In this context, solutions based on Machine Learning appear particularly promising, since
they can … and infer the future state of the network to achieve the global network optimization. …

… The usage of artificial intelligence (AI) methodologies for carrying out automatic decision
making in the cellular network have been modelled in recent time for optimizing handover …

… Afterwards, we transform this problem into a machine learning … The handover management
and resource allocation optimization problem have been transformed to a machine learning …

… In this work, a machine learning technique is used to solve the KPI function. Neural
Networks Multilayer Perception (MLP) is used to perform KPI function estimation. The multilayer …