Browsing by Author "Faruk N"

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    Large-scale radio propagation path loss measurements and predictions in the VHF and UHF bands
    (2021) Faruk N; Abdulrasheed IY; Surajudeen-Bakinde NT; Adetiba E; Oloyede AA; Abdulkarim A; Sowande O; Ifijeh AH; Atayero AA
    For decades now, a lot of radio wave path loss propagation models have been developed for predictions across different environmental terrains. Amongst these models, empirical models are practically the most popular due to their ease of application. However, their prediction accuracies are not as high as required. Therefore, extensive path loss measurement data are needed to develop novel measurement-oriented path loss models with suitable correction factors for varied frequency, capturing both local terrain and clutter information, this have been found to be relatively expensive. In this paper, a large-scale radio propagation path loss measurement campaign was conducted across the VHF and UHF frequencies. A multi-transmitter propagation set-up was employed to measure the strengths of radio signals from seven broadcasting transmitters (operating at 89.30, 103.5, 203.25, 479.25, 615.25, 559.25 and 695.25 MHz respectively) at various locations covering a distance of 145.5 km within Nigerian urban environments. The measurement procedure deployed ensured that the data obtained strictly reflect the shadowing effects on radio signal propagation by filtering out the small-scale fading components. The paper also, examines the feasibilities of applying Kriging method to predict distanced-based path losses in the VHF and UHF bands. This method was introduced to minimize the cost of measurements, analysis and predictions of path losses in built-up propagation environments.
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    Path loss predictions for multi-transmitter radio propagation in VHF bands using Adaptive Neuro-Fuzzy Inference System
    (2018) Surajudeen-Bakinde NT; Faruk N; Popoola SI; Salman MA; Oloyede AA; Olawoyin LA; Calafate CT
    Path loss prediction is an important process in radio network planning and optimization because it helps to understand the behaviour of radio waves in a specified propagation environment. Although several models are currently available for path loss predictions, the adoption of these models requires a trade-off between simplicity and accuracy. In this paper, a new path loss prediction model is developed based on an Adaptive Neuro-Fuzzy Inference System (ANFIS) for multi-transmitter radio propagation scenarios and applicable to the Very High Frequency (VHF) bands. Field measurements are performed along three driving routes used for testing within the urban environment in Ilorin, Kwara State, Nigeria, to obtain the strength values of radio signals received from three different transmitters. The transmitters propagate radio wave signals at 89.3 MHz, 103.5 MHz, and 203.25 MHz, respectively. A simple five-layer optimized ANFIS network structure is trained based on the back-propagation gradient descent algorithm so that given values of input variables (distance and frequency) are correctly mapped to corresponding path loss values. The adoption of the Pi membership function ensures better stability and faster convergence at minimum epoch. The developed ANFIS-based path loss model produced a low prediction error with Root Mean Square Error (RMSE), Standard Deviation Error (SDE), and correlation coefficient (R) values of 4.45 dB, 4.47 dB, and 0.92 respectively. When the ANFIS-based model was deployed for path loss predictions in a different but similar propagation scenario, it demonstrated a good generalization ability with RMSE, SDE, and R values of 4.46 dB, 4.49 dB, and 0.91, respectively. In conclusion, the proposed ANFIS-based path loss model offers desirable advantages in terms of simplicity, high prediction accuracy, and good generalization ability, all of them critical features for radio coverage estimation and interference feasibility studies during multi-transmitter radio network planning in the VHF bands.