Hybrid Approach for Evaluation and Optimization of 5G Mobile Network Coverage Predictions
DOI:
https://doi.org/10.63746/njtd.v23i1.4512Keywords:
5G throughput, 5G coverage optimization, 5G radio planning, quality of service, beamforming technology, Signal-to-Interference-plus-Noise Ratio (SINR)Abstract
Data usage continues to surge as 5G provides the foundation for massive Internet of Things (IoT) connectivity, ultra-low latency, and high-speed data transfer. For the fact that the demand for robust and faster network connectivity and data speeds is very crucial, fixed wireless access (FWA) is bridging the gap for high-speed internet in areas like rural or under-served areas, as well as urban/suburban environments where fiber is not available, utilizing 5G networks to offer fiber-like speeds. Nevertheless, environmental factors and network load affect signal performance, thus, on 5G coverage predictions. Though 5G offers higher speeds and lower latency compared to its predecessors. Notwithstanding, its dependence on higher-frequency radio waves makes it susceptible to degradation from physical obstructions, atmospheric conditions, and high user density. Heavy rain, snow, and dense fog absorb and scatter 5G radio waves while trees and buildings obstruct. 5G technology is a significant advancement that promises unparalleled speeds, reduced latency, and enhanced connectivity crucial for modern applications. However, the current situation reveals persistent challenges in achieving these ideals across diverse environments such as environments with complex terrains, high user density, and varying user demands. There are disparities between predicted and actual network performance metrics such as throughput, latency, coverage gaps, and inconsistencies in QoS (quality of service). The study adopts a hybrid approach that combines simulation-based analysis and real-world drive test measurements for optimization of 5G network coverage predictions.
The paper presents the findings, analyzing existing 5G coverage predictions and modelling a similar network scenario on MATLAB to optimize 5G beamforming antenna coverage, and offering recommendations to have better coverage and optimal performance, providing users with more reliable and higher-quality connectivity of the 5G network.
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