Improved SINR m-Coverage Probability in 6G Networks: Unveiling the Sample Point Saturation Phenomenon in Urban and Suburban Environments

This study looks at the influence of sample points on SINR-based m-coverage probability in Urban and Suburban environments within the context of 6G networks. SINR is a crucial factor impacting network coverage and reliability. While it is commonly assumed that increasing sample points enhances SINR...

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Bibliographic Details
Published in:	2024 International Conference on Science, Engineering and Business for Driving Sustainable Development Goals (SEB4SDG) pp. 1 - 7
Main Authors:	Ajaegbu, Chigozirim, Adebiyi, Abayomi A., Kanu, R.U
Format:	Conference Proceeding
Language:	English
Published:	IEEE 02-04-2024
Subjects:	6G mobile communication 6G technology Accuracy Computational efficiency Coverage Probability Heterogenous Network Interference Mathematical models Reliability Satellite Network3 Signal-Interference-Noise Ratio Unmanned Aerial Network Wireless communication
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Summary:	This study looks at the influence of sample points on SINR-based m-coverage probability in Urban and Suburban environments within the context of 6G networks. SINR is a crucial factor impacting network coverage and reliability. While it is commonly assumed that increasing sample points enhances SINR coverage probability, the relationship between sample points and coverage probability remains intricate and not well-understood. The main objective of this study was to determine the saturation point at which additional sample points only marginally improve network performance. To achieve this, advanced simulations were conducted using the Poisson point process to spatially distribute nodes in single-tier and multi-tier networking scenarios. Existing mathematical models of path-loss, interference, and coverage probability were extended, taking into account other wireless phenomena present in urban and suburban environments. The analysis indicates a positive correlation between coverage probability and increasing sample points, as expected for improved network performance. However, intriguingly, both Urban and Suburban environments exhibit a saturation point, challenging the conventional belief of continuous improvements with more sample points. The optimization of sample point numbers becomes crucial to strike the right balance between accuracy and computational efficiency in designing 6G networks. These findings offer valuable insights for network planning, ultimately enhancing the overall performance and reliability of 6G networks in dynamic environments.
DOI:	10.1109/SEB4SDG60871.2024.10629735