EMPIRICAL ASSESSMENT OF FM RADIO SIGNAL STRENGTH VARIATIONSWITH DISTANCE AND WEATHER CONDITIONS IN WARRI, NIGERIA
DOI:
https://doi.org/10.33003/fjs-2026-1001-4534Keywords:
FM Radio Propagation, Received Signal Strength (RSSI), Weather-Induced Signal Variation, Temperature and Humidity, Tropical Climate Propagation, Warri, NigeriaAbstract
Reliable frequency modulation (FM) broadcast coverage depends significantly on signal strength variations with distance and short-term environmental conditions. This study presents an exploratory field investigation of Received Signal Strength Indicator (RSSI) variations from four FM radio stations - Mega FM, Crown FM, Current FM, and DBS Warri - in Warri, Delta State, Nigeria. Observational field measurements were obtained at distances between 1 km and 10 km during morning, afternoon, and evening periods in a one-day pilot campaign conducted in June 2024. Alongside RSSI, temperature and humidity were recorded to examine their associations with short-term signal propagation. The results show a clear decay of RSSI with increasing distance and consistent diurnal variability across all stations. Correlation analysis indicates that humidity exhibits a stronger negative association with RSSI (–0.45 to –0.61) than temperature (+0.12 to –0.22). To further quantify these relationships, a pooled ordinary least squares regression incorporating station-specific effects was performed. Distance emerged as a statistically significant predictor of RSSI, while humidity showed a weak negative influence and temperature was not statistically significant within the short observation window. Station-dependent differences in RSSI were also evident, reflecting variations in transmitter characteristics. As a temporally limited pilot study, the findings indicate associations rather than causal relationships, but they demonstrate the value of combining distance-based measurements with environmental parameters and station-specific effects in FM propagation analysis within tropical urban environments. The study provides a foundation for extended multi-day measurements and future predictive modelling of FM broadcast signal behaviour.
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Copyright (c) 2026 Akpevwe Ejiro Ohworho, Jude Oruaode Vwavware, Ezekiel Onoriode Abriku

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