Nazmat T. Surajudeen-Bakinde

Improved path-loss model for predicting TV coverage for secondary access

Path-loss model is essential for proper planning of emerging technologies in the broadcast frequency band. Characterisation of the radio channel is paramount for accurate prediction of TV coverage, and achievement of peaceful coexistence between the TV (primary users) and other new infrastructures (secondary users). In this paper, field strength measurements are conducted along six routes that spanned through urban, suburban and rural areas of Kwara State, Nigeria. The measurement results are compared with path-loss prediction of eight widely used empirical models. Least squares and linear iterative methods are employed to optimise Hata-Davidsons model, as it showed best fit compared with other models. The predictions of the tuned model are compared with other models in terms of relative error, mean error, skewness, root mean square errors and normalised error probability density function. Results of the simulations indicate that the optimised model gives better values for the metrics considered.

Adaptive Neuro-Fuzzy model for path loss prediction in the VHF band

Path loss prediction models are essential in the planning of wireless systems, particularly in build-up environments. However, the efficacies of the models depend on the local ambient characteristics of the environments. This paper proposed the Neuro-Fuzzy (NF) model for path loss prediction for Ilorin in the VHF band. Received signal strengths along four different routes were measured using NTA Ilorin transmitter which operates at a frequency of 203.25 MHz as a reference. The predictions of the proposed model was compared to Hata, COST 231, Egli and ECC-33 models which are considered standard and widely used empirical path loss models. The Root Mean Square Error (RMSE) was used as a measure of merit for their performances. Across all the routes visited, an average RMSE of 5.253 dB, 9.487 dB, 14.264 dB, 18.696 dB, and 27.890 dB were obtained respectively for the NF, ECC-33, Hata, COST 231 and Egli models. The NF model result is shown to improve the predictions over the estimates obtained when compared with the other models.

Performance analysis of empirical path loss models in VHF & UHF bands

In this work, signal path loss prediction from nine different empirical path loss models were statistically compared with those measured from four television transmitters along five routes that span through urban and rural environments of Osun State, Nigeria. In this respect, results obtained show that both Hata and Davidson prediction models provide best fit prediction consistently along the five measurement routes with 90% to 98% prediction accuracy, Ilorin, CCIR, Cost 231, Ericsson 9999 and ECC-33 show prediction accuracy within the range of 65% to 80% while SUI and Okumura models offer prediction accuracy within the range of 15% to 21%. Generally the results show that Davidson and Hata models have better results in all the five routes examined. SUI and Okumura models show the least performance results.

Development of an Internet based prepaid energy meter

Energy fuels the growth and development of any country, and as such effective monitoring, measurement, billing and access control is imperative. This paper presents a device that uses the evolving Internet of Things (IoT) technology in the design and implementation of an Internet based prepaid energy meter often referred to as smart meters. The energy measurement and billing system is automated. The system employs the ATMega328p and ESP8266 to operate a dual core microprocessor unit with one core dedicated to energy sensing and measurements, while the other handles the network connectivity, storage, computations and overall system performance. This work uses the HTML5 technology to develop a highly interactive mobile and web frontend Graphic User Interface (GUI) application that allows for consumers to have access to monitor and control their consumption pattern while the utility companies can monitor and control customers and their billing systems.