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All Journal JURNAL NASIONAL TEKNIK ELEKTRO Computer Science and Information Technologies
Amevi Acakpovi
Accra Technical University
Computer Science & IT Electrical & Electronics Engineering Engineering

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Journal : computer science and information technologies

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Raindrop and bit drop effects on millimeter wave network performance: a critical review Victor Dela Gordon; Amevi Acakpovi; George Kwamena Aggrey; Michael Gameli Dziwornu
Computer Science and Information Technologies Vol 7, No 1: March 2026
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/csit.v7i1.p83-92

Abstract

This PRISMA guided review examines how rain precipitation degrades 5G millimeter wave (mmWave) network performance, with emphasis on rain induced bit drop and its impact on end-to-end quality of service (QoS). From an initial corpus of 13,317 publications screened across IEEE Xplore, ACM Digital Library, ScienceDirect, Google Scholar, and ELICIT, 18 peer reviewed studies published between 2018 and 2024 met the inclusion criteria. Findings show that rainfall significantly weakens mmWave signals, with specific attenuation ranging from approximately 4 to 45 dB/km at 100 mm/h, particularly in tropical regions. When QoS outcomes are reported, these losses manifest as increased bit error rates, rain driven bit drop along the link, higher packet loss and delay, and reduced throughput. Key deficiencies identified include limited empirical validation of attenuation models against packet level QoS, lack of standardized propagation datasets for short range links, and weak treatment of bit level impairments within QoS analysis. To address these gaps, the review recommends enhancing ITU R P.530 and Mie scattering models with region specific measurements, implementing rain aware adaptive protocols, and adopting standardized benchmarking frameworks that link rain attenuation, bit drop, and QoS. This synthesis offers guidance for building climate aware mmWave systems and positions bit drop as a practical metric for precipitation resilience assessment.
A hierarchical mixed-effects modeling framework with Weibull reliability characterization for spatiotemporal throughput variability in cellular networks Victor Dela Gordon; Amevi Acakpovi
Computer Science and Information Technologies Vol 7, No 3: November 2026
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/csit.v7i3.p241-255

Abstract

Reliable cellular throughput is essential for ensuring consistent user experience in modern mobile networks, yet it exhibits significant variability across spatial and operational conditions due to propagation effects, interference, and network congestion. This study proposes a hierarchical mixed-effects modeling framework integrated with Weibull-based reliability analysis to characterize spatiotemporal throughput variability in real-world operating conditions. The analysis is based on a large-scale dataset comprising over 77,000 field measurements collected across multiple university campus locations in Ghana, enabling cross-layer evaluation of network performance using key indicators, including reference signal received power (RSRP), reference signal received quality (RSRQ), and round-trip time (RTT). Analysis results indicate that all modeled predictors significantly influence throughput performance, with signal quality emerging as the dominant factor, alongside notable spatial heterogeneity. The model explains 18.9% of variability using fixed effects and 45.1% when spatial effects are included. Reliability analysis indicates that the probability of achieving 5 Mbps and 10 Mbps is 39.7% and 22.5%, respectively. These findings demonstrate that the proposed framework effectively captures throughput variability, spatial heterogeneity, and probabilistic service reliability in operational cellular environments, providing a practical analytical framework for reliability-aware cellular network optimization and performance evaluation.
Co-Authors Francis Boafo Effah George Kwamena Aggrey Michael Gameli Dziwornu Philip Gasu Philip Okyere Victor Dela Gordon Victor Dela Gordon