… Handover (HO) is a critical component of next-generation (… HO optimization strategies using
machine learning models. … of machine learning methods in handover optimization and of …

… 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 …

… 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 …

… 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 …

… 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 …

… 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 …

… failures through parameter optimization of the A3RSRP in a macro-small cell scenario.
The authors of [32], [33] propose the parameter tuning of MLNs by Fuzzy logic, improving the …

… Machine learning The main goal of machine learning (ML) [16] is to find the learning
algorithm which is performed without human intervention, where the time and amount of data …

… machine learning algorithms were used in Cognitive Radio. In this paper, we studied the
handover … an an adaptive parameter handover mechanism. Due to the highly dynamic feature of …