Channel modeling and Propagation Prediction for RIS-Assisted 6G Mobile Communication Systems
DOI:
https://doi.org/10.29284/kwgy1d39Keywords:
IRS (Intelligent Reflecting Surface), Channel Modeling, Path-loss, Propagation Prediction, 6G Application, computer simulation, Base Station Side Scheme, Mobile Communication System, Coverage Maximization Algorithm.Abstract
Many of the issues and constraints that impair mobile radio systems' performance are primarily caused by the propagation channel. Reconfigurable Intelligent Surfaces (RIS) are expected to play a central role in emerging 6G wireless networks by enhancing coverage and improving energy efficiency. This paper presents a simplified technique for hierarchical beam-training that manipulates electromagnetic waves to establish dominant transmission paths in RIS-assisted propagation prediction. The integration of RIS in near-field at 6G mobile scenarios introduces significant complexity due to the large number of reflecting elements and the inherent structure of the channel through MATLAB-based simulation environment. Extensive simulations are conducted to analyze the path-loss characteristics and spectral efficiency of the RIS Assisted 6G Mobile Communication Systems in comparison with conventional systems over various distances. Several statistical parameters such as, Frequency Bands, average duration of fade, Received Power were performed from the total received signal to characterize the channel modeling and propagation prediction. The results show that the propagation prediction approach accurately captures the RIS beamforming gain and by means of increasing the size of RIS surface is significantly improving the SNR in an effective method and improve the coverage performance of the 6G THz communication system and strongly guarantee the support of the ultra-large bandwidth of THz
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