Predikce CQI v mobilních sítí 5G NR

Abstract

The diploma thesis aims to cover the research area related to the CQI (Channel Quality Indicator) prediction for MCS (Modulation and Coding Schemes) adaptation. The theoretical part will focus on the CSI (Channel State Information) mechanism, CSI report components (including CQI), CQI parameter importance in cellular networks, and the issue of CSI/CQI aging due to user mobility. In the practical part, the NS3 (Network Simulator) Simulator 3) will be used for CQI data generation; the LENA-5G module will be utilized. Then the obtained dataset will be used as the input for creating the CQI prediction method utilizing the ML (machine learning)/DL (deep learning) approaches. The main goal of the practical part is to develop the CQI prediction module for accurate downlink scheduling in the 5G NR (New Radio) cellular systems, as it reduces The negative impact of the outdated CQI and MCS leads to the degradation of the network performance (especially in high-speed scenarios).The outputs will be technically described and presented as the output of the master's thesis.

The diploma thesis aims to cover the research area related to the CQI (Channel Quality Indicator) prediction for MCS (Modulation and Coding Schemes) adaptation. The theoretical part will focus on the CSI (Channel State Information) mechanism, CSI report components (including CQI), CQI parameter importance in cellular networks, and the issue of CSI/CQI aging due to user mobility. In the practical part, the NS3 (Network Simulator) Simulator 3) will be used for CQI data generation; the LENA-5G module will be utilized. Then the obtained dataset will be used as the input for creating the CQI prediction method utilizing the ML (machine learning)/DL (deep learning) approaches. The main goal of the practical part is to develop the CQI prediction module for accurate downlink scheduling in the 5G NR (New Radio) cellular systems, as it reduces The negative impact of the outdated CQI and MCS leads to the degradation of the network performance (especially in high-speed scenarios).The outputs will be technically described and presented as the output of the master's thesis.