May 22, 2024 · This paper marks a novel endeavor in this domain, as it explores and evaluates a range of machine learning (ML) techniques for predicting MCS in orthogonal ...
The examined ML methods include Artificial Neural Networks (ANN), Support Vector Machine (SVM), Random Forest (RF), and Bagging with k-NN (B-kNN). These methods ...
May 22, 2024 · Some great news!! Our paper "Machine learning-based methods for MCS prediction in 5G networks " that was authored by Lefteris Tsipis, ...
A user equipment requests services (UE) are based on a key performance indicator (KPI) and key quality indicator (KQI) while selecting the network slice.
In this paper, we introduce a machine learning (ML) model used to estimate throughput in 5G and B5G networks with end-to-end (E2E) network slices.
Missing: MCS | Show results with:MCS
Channel quality feedback is very important for operation of 4G or 5G wireless complex because it allocate user equipment (UE).
The paper proposes a machine learning network slicing model based on feature selection, comprising three main components.
Missing: MCS | Show results with:MCS
ML framework for MCS prediction: flow chart of data processing–training, validation, and testing of ML methods · 5G C-RAN architecture · Developed ANN model.
People also ask
Which machine learning algorithm to use for prediction?
What is the use of machine learning in 5G?
What is mcs in 5G?
What is the machine learning approach for predicting?
This work presents an overview of machine learning methods in handover optimization and of the various data availability for evaluations.
Missing: MCS | Show results with:MCS
7 days ago · In the end, five independent machine-learning approaches were utilized. When compared to the other five ML models, Random Forest Regression ...
Missing: MCS | Show results with:MCS