Asian Journal of Research and Reviews in Physics

Statistical Approaches to Environmental and Atmospheric Influences on Fifth-generation Mobile Signal Propagation in Tropical Regions: A Critical Review

Sirajo Abdullahi, Adebayo S. Adewumi, Efua O. Anthony — Wed, 02 Sep 2026 00:00:00 +0000

Tropical and equatorial territories combine the most intense sustained rainfall on the planet with an accelerating rollout of fifth-generation mobile networks in the centimetre and millimetre wave bands. The statistical apparatus used to translate environmental and atmospheric measurements into propagation predictions, however, was assembled largely from temperate-latitude datasets and from fixed links considerably longer than the urban small cells that dominate contemporary deployment. This review critically evaluates how statistical methods have been applied to environmental and atmospheric parameters governing fifth-generation propagation in the tropics, and asks whether the resulting evidence supports the confidence routinely placed in it. Five method families are examined: the estimation of point rainfall rate distributions and the conversion of long integration-time records to the one-minute reference; the regression of specific attenuation on rainfall rate through power-law coefficients derived from drop size spectra; the spatial statistics embedded in path reduction factors, effective rainfall rate formulations and site diversity models; the correlational and regression treatment of water vapour, temperature, refractivity, wind and vegetation; and supervised learning applied to path loss and attenuation time series. Convergent evidence establishes that rainfall rates exceeded for one hundredth of one per cent of an average year in equatorial sites are roughly an order of magnitude above temperate values, and that standard international recommendations systematically misestimate attenuation on paths shorter than one kilometre. Beyond this, the evidence weakens sharply. Reported model rankings rest on single-year records from a small number of sites, are assessed with inconsistent error statistics and almost never carry uncertainty intervals, so apparent superiority is frequently indistinguishable from sampling variation. Studies of non-precipitation parameters report correlations that reverse sign between seasons and regression models that explain little of the observed variance, yet these are often interpreted causally. Machine learning results are constrained by small, spatially autocorrelated datasets, by evaluation protocols that permit optimistic bias, and in some cases by reliance on simulator output as ground truth. Progress requires coordinated multi-site campaigns, open data, formal uncertainty quantification and validation protocols that test transfer rather than fit.

Evaluation and Calibration of Downward Longwave Radiation Models under Clear Sky Condition across the Sahelian Region of Nigeria

Tue, 01 Sep 2026 00:00:00 +0000

Downward longwave radiation (DLR) is a major component of the surface energy budget, yet the transferability of empirical clear-sky DLR models across Nigeria’s Sahelian climatic zone remains uncertain. This study evaluated eleven existing empirical DLR models and five locally calibrated modifications for Kano and Sokoto. Monthly mean relative humidity, air temperature, and DLR data covering 1984–2023 were used, with 1984–2015 allocated to model development and 2016–2023 reserved for validation. Model performance was assessed using Mean Bias Error, Root Mean Square Error, Mean Percentage Error, t-test, Index of Agreement, correlation coefficient for the modified models, and an overall ranking procedure. Among the existing models, the Idso formulation ranked first at both locations. For Kano, the modified Guest model was the best-performing calibrated model and also ranked ahead of the existing Idso model in the direct comparison. For Sokoto, the modified Idso model ranked first among the calibrated models; however, the existing Idso model retained the better overall rank in the direct comparison. Seasonal analysis showed higher DLR during the rainy season and lower values during the dry Harmattan season, with relative humidity and atmospheric moisture varying concurrently with DLR. The results indicate that local calibration can improve empirical DLR estimation, although the benefit depends on location and model formulation.

Empirical Measurement of 5G Mobile Signal Path Loss in Southern and Northern Urban Metropolis of Nigeria

Sirajo Abdullahi, A. S. Adewumi, O. Olabisi, M. M. Labbo — Thu, 03 Sep 2026 00:00:00 +0000

Accurate characterisation of large-scale radio attenuation is important for fifth-generation (5G) network planning, particularly in heterogeneous urban environments. This study reports a drive-test assessment conducted in Lagos and Ibadan in southern Nigeria and Abuja and Kano in northern Nigeria at 3.5-3.6 GHz. The reported measurement configuration used a receiver height of 1.5 m, a transmitting-antenna height of approximately 40-45 m, and transmitter-receiver separations of about 50-500 m. Reference Signal Received Power, Reference Signal Received Quality, signal-to-noise ratio, throughput, and Global Positioning System coordinates were logged using TEMS Investigation, a 5G signal analyser, and a vehicle-mounted measurement setup. A locally calibrated log-distance relation with city-specific intercept terms was graphically juxtaposed with Okumura-Hata, COST-231 Hata, Egli, and the ITU-R P.833-9 vegetation-attenuation formulation. The plots show substantial divergence among model families and among city/operator panels, demonstrating that model choice and local calibration assumptions materially affect predicted attenuation trends. The ITU-R P.833-9 series is interpreted only as a vegetation-attenuation benchmark rather than a complete urban path-loss model. The results do not support a universal north-south ranking of propagation loss; instead, they indicate site-, route-, and configuration-dependent behaviour. Because complete route-level residuals, uncertainty estimates, and all fitted model parameters are not available for every panel, the comparison is intentionally descriptive and does not claim statistical superiority of one model. The findings support cautious, measurement-informed calibration of 5G propagation models for Nigerian urban deployments.