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5G Frequencies Standardization, Technologies, Channel Models and Network Deployment: Advances, Challenges, and Future Directions
(2023) Musa, Abdulwaheed
The rapid increase in data traffic caused by the proliferation of smart devices has spurred the demand for extremely large-capacity wireless networks. Thus, faster data transmission rates and greater spectral efficiency have become critical requirements in modern-day networks. The ubiquitous 5G is an end-to-end network capable of accommodating billions of linked devices and offering high-performance broadcast services due to its several enabling technologies. However, the existing review works on 5G wireless systems examined only a subset of these enabling technologies by providing a limited coverage of the system model, performance analysis, technology advancements, and critical design issues, thus requiring further research directions. In order to fill this gap and fully grasp the potential of 5G, this study comprehensively examines various aspects of 5G technology. Specifically, a systematic and all-encompassing evaluation of the candidate 5G enabling technologies was conducted. The evolution of 5G, the progression of wireless mobile networks, potential use cases, channel models, applications, frequency standardization, key research issues, and prospects are discussed extensively. Key findings from the elaborate review reveal that these enabling technologies are critical to developing robust, flexible, dependable, and scalable 5G and future wireless communication systems. Overall, this review is useful as a resource for wireless communication researchers and specialists.
A chi-square-SVM based pedagogical rule extraction method for microarray data analysis
(Institute of Advanced Engineering and Science (IAES), 2020) Salawu, Mukhtar Damola; Arowolo, Micheal Olaolu; Abdulsalam, Sulaiman Olaniyi; Isiaka, Rafiu Mope; Jimada-Ojuolape, Bilkisu; Olumide, Mudashiru Lateef; Gbolagade, Kazeem A.
Support Vector Machine (SVM) is currently an efficient classification technique due to its ability to capture nonlinearities in diagnostic systems, but it does not reveal the knowledge learnt during training. It is important to understand of how a decision is reached in the machine learning technology, such as bioinformatics. On the other hand, a decision tree has good comprehensibility; the process of converting such incomprehensible models into an understandable model is often regarded as rule extraction. In this paper we proposed an approach for extracting rules from SVM for microarray dataset by combining the merits of both the SVM and decision tree. The proposed approach consists of three steps; the SVM-CHI-SQUARE is employed to reduce the feature set. Dataset with reduced features is used to obtain SVM model and synthetic data is generated. Classification and Regression Tree (CART) is used to generate Rules as the Last phase. We use breast masses dataset from UCI repository where comprehensibility is a key requirement. From the result of the experiment as the reduced feature dataset is used, the proposed approach extracts smaller length rules, thereby improving the comprehensibility of the system. We obtained accuracy of 93.53%, sensitivity of 89.58%, specificity of 96.70%, and training time of 3.195 seconds. A comparative analysis is carried out done with other algorithms.
A Comparative Analysis of Complexity of C++ and Python Programming Languages Using Multi- Paradigm Complexity Metric (MCM)
(International Journal of Science and Research (IJSR), 2018-10-26) Balogun M. O.; Sotonwa K. A.
Software complexity metrics have used to quantifydifferent types of software properties such as cost, effort, time, maintainability, understanding and reliability. The existing metrics considered limited factors that affect software complexity, but do not consider the characteristics that affect complexity of multi-paradigm languages. In this work, a Multi-paradigm Complexity Metric (MCM) for measuring software complexity was developed for multi-paradigm codes. Multi-paradigm languages that were considered in thiswork are C++ and Python, these two languages combine the features of procedural and object oriented paradigms, therefore this research began with investigation of factors that affect the complexity of procedural code and object oriented code, so that the developed metric could be used not only for procedural code, but also either object oriented codes or in more general for multi-paradigm codes. The developed metric was then applied on sample programs written in most popular programming languages such as Python and C++, and the result of the developed metric was further evaluated with other existing complexity metrics like effective line of code (eLOC), cyclomatic complexity metric and Halstead complexity measures. The study showed that the developed complexity metric have significant comparison with the existing complexity metrics and can be used to rank numerous programs and difficulties of various modules.
A Complexity Metric for Multi-Paradigm Programming Languages
(International Journal of Emerging Technology and Advanced Engineering, 2014-04-22) Olabiyisi S. O.; Omidiora E. O.; Balogun M. O.
Software complexity metrics are used to measure variety of software properties such as cost, effort, time, maintenance, understanding and reliability. Most of the existing metrics considered limited factors that affect software complexity, but do not consider the characteristics of multi-paradigm languages. In this work, a Multi-paradigm Complexity Metric (MCM) for measuring software complexity was developed for multi-paradigm codes. Multi-paradigm languages that were used in this work combine the features of procedural and object oriented paradigms, therefore this research began with investigation of factors that affect the complexity of procedural code, thereafter with a more modern approach, the research was further extended by adding object oriented features, so that the developed metric could be used not only for procedural code, but also either object oriented codes or in more general meaning for multi-paradigm codes. The developed metric was then applied on sample programs written in most popular programming languages such as Python, Java and C++, and was further evaluated with other existing complexity metrics like effective line of code (eLOC), cyclomatic complexity metric and Halstead complexity measures. The study showed that the developed complexity metric have significant comparison with the existing complexity metrics and can be used to rank competitive programs and difficulties of various modules.
A Control Model of the Operating Head Dynamics of Jebba Hydropower System.
(Nigerian Journal of Technological Research (NJTR), 2019) Ogunbiyi O., Thomas C., Omeiza I. O. A. , Akanni J., Olufeagba B. J.
Electricity availability in Nigeria has been very poor over the years, underscoring the need for a better approach for managing generating resources. This paper presents the development of a dynamical model of the operating head of Jebba hydroelectric power plants for system studies and control system design. The mathematical model of the plant was developed from flow continuity conditions, some model parameters were obtained from the source while others were estimated from observations and analysis of the measured data. The developed dynamical equation was validated by comparing the response produced with values obtained by measurement. Upon integrating the model equation in the Microsoft EXCEL VBA® environment, a deviation of 2% from measured values was observed. Operators can therefore use the model as a decision support system, while control engineers can find the model directly applicable for optimal and robust control system design for the station.
A Direct Optimal Control of the Jebba Hydropower Station
(Institute of Electrical and Electronics Engineering (IEEE), 2019-09-01) Olalekan Ogunbiyi; Cornelius T. Thomas; Benjamin J. Olufeagba; Ibrahim S. Madugu; Busayo H. Adebiyi; Lambe M. Adesina
The optimal power generation from the Jebba hydroelectric power station is subject to the reservoir operating head, weather-related factors, units’ availability and system dynamics. In this paper, a computer control system is designed to ensure safe operation and maximize power generation. The controller is an optimal controller, which determines the amount of inflow required to regulate the reservoir operating head. The control law is an optimal control procedure developed around the steepest descent and conjugate gradient algorithm. The algorithms determine the control signal and state trajectories for minimization of a performance index defined for the regulation of the reservoir operating head. The results show that the two techniques are feasible in estimating an optimal inflow needed to move the reservoir operating head from any level to the nominal head. The two techniques were compared under different operating conditions of the hydropower system, the conjugate gradient algorithm performs better in terms of computational time. The control algorithm is recommended for use in the realization of a computer control system for the station.
A Direct Optimal Control of the Jebba Hydropower Station
(2nd International Conference of the IEEE Nigeria Computer Chapter, NigeriaComputConf, 2019) Ogunbiyi, O., Thomas, C. T., Olufeagba, B. J., Madugu, I. S., Adebiyi, B. H., & Adesina, L. M.
The optimal power generation from the Jebba hydroelectric power station is subject to the reservoir operating head, weather-related factors, units’ availability and system dynamics. In this paper, a computer control system is designed to ensure safe operation and maximize power generation. The controller is an optimal controller, which determines the amount of inflow required to regulate the reservoir operating head. The control law is an optimal control procedure developed around the steepest descent and conjugate gradient algorithm. The algorithms determine the control signal and state trajectories for the minimization of a performance index defined for the regulation of the reservoir operating head. The results show that the two techniques are feasible in estimating an optimal inflow needed to move the reservoir operating head from any level to the nominal head. The two techniques were compared under different operating conditions of the hydropower system, the conjugate gradient algorithm performs better in terms of computational time. The control algorithm is recommended for use in the realization of a computer control system for the station.
A Method of Colour-Histogram Matching for Nigerian Paper Currency Notes Classification
(Jordan Journal of Electrical Engineering (JJEE), 2023) Omeiza, I. O. A., Ogunbiyi, O., Ogundepo, O. Y., Otuoze, A. O., Egbune, D. O., & Osunsanya, K.
In this paper a new algorithm for the classification of three Nigerian paper currency notes, namely 200, 500, and 1000 Naira (N) denominations is presented. The work examines the effectiveness of using only colour histograms to differentiate between the classes or denominations of the three Nigerian paper currency notes. The bin-heights of the histograms of the HSI component images for the paper currencies are used as features while a rule-based classifier designed to take advantage of the changes or variations in the histogram patterns is used to classify the paper currencies into the right denomination class. The algorithm involves the utilization of a simple and effective comparison strategy as opposed to the existing, too-rigid metrics for histogram-comparison used by other authors for color indexing in content-based image retrieval systems. Over a testing data-set of 300 samples, the algorithm achieved an average classification accuracy of 98.66%, and classification accuracies of 100%, 99% and 97% for the N=200, N=500 and N=1000 denominations, respectively. The proposed algorithm does not require extensive preprocessing of the paper-currency images and as such is fast in implementation.
A Modified COST-231-Hata Path Loss Model for Typical Semi-Urban Environments in Nigeria
(KIU Journal of Science, Engineering and Technology, 2024) AKANNI, Jimoh, ISA Abdurrhaman Ademola, OGUNBIYI Olalekan, OLUFEAGBA Benjamin Jimmy
Outdoor path loss propagation modeling is critical in the planning and design of the coverage area by the Global System for Mobile Communication (GSM). For the best prediction of GSM signal at any location within its coverage region, an accurate forecast based on critical characteristics and a mathematical model is necessary. Multiple studies on path loss propagation model prediction for GSM networks conducted at various semi-urban environments in Nigeria proclaimed that propagation path loss models may provide different results when utilized in environments other than those in which they were initially designed, that car drive-test methodology was used during the data collection, and that COST-231-Hata model provides closet prediction to the practical measure values. This paper created an appropriate path loss model based on the COST-23-Hata model and outdoor measurement at 1800 MHz frequency range for the semi-urban area of Kwara State, Nigeria. The created model was used and validated with the measured data and COST-231-Hata model at other different semi-urban environments in Nigeria. The results analysis shows that the created model performed satisfactorily given the closet path loss prediction to the practical measure path loss values at all the study locations. It also gives the lowest Square Root Means Error (SRME) and Standard Deviation (SD) in all the base stations that were tested in semi-urban environments. The newly created model would therefore be more appropriate for GSM 1800 network design and installation in semi-urban environments in Kwara State, Nigeria, as well as any other semi-urban locations in Nigeria.
A Nonlinear Control Model and Operational Support System for the Kainji Hydroelectric Power System
(2019) Ogunbiyi, O., Thomas, C. T., Omeiza, I. O. A., Akanni, J., & Olufeagba, B. J.
Over the past years, the hydropower model and control were largely based on classical and linear transfer functions, this was motivated by the available control system design techniques that were available and the desire to simplify the design procedure. Such a model is inadequate for dynamic study and design of hydropower stations in the presence of uncertainties in the water head, discharge rate, elastic water effect, travelling wave effect, large variation power output and frequency. This research, therefore, focuses on developing a nonlinear model for the Kainji hydroelectric power station. The model relies on the energy conversion principles, inflows, discharge, evaporation rate and number of units on the busbar. The parameters of the model were also estimated, and the model was validated with an error within +1.4% to -3.6%. The model is expected to be used to determine the optimal control policies for the operation of the station and the release of water to downstream.
A Nonlinear Control Model and Operational Support System for the Kainji Hydroelectric Power System.
(Nigerian Journal of Technology (NIJOTECH), 2019) Ogunbiyi, O., Thomas, C. T., Omeiza, I. O. A., Akanni, J., & Olufeagba, B. J.
Over the past years, the hydropower model and control were largely based on classical and linear transfer functions, this was motivated by the available control system design techniques that were available and the desire to simplify the design procedure. Such a model is inadequate for dynamic study and design of hydropower station in the presence of uncertainties in the water head, discharge rate, elastic water effect, traveling wave effect, large variation power output and frequency. This research, therefore, focuses on developing a nonlinear model for the Kainji hydroelectric power station. The model relies on the energy conversion principles, inflows, discharge, evaporation rate and number of units on busbar. The parameters of the model were also estimated, and the model validated with an error within +1.4% to -3.6%. The model is expected to be used to determine the optimal control policies for the operation of the station and the release of water to the downstream.
A Progressive Domain Expansion Method for Solving Optimal Control Problem.
(TELKOMNIKA (Telecommunication, Computing, Electronics and Control), 2020) Ogunbiyi, O., Ogundepo, O. Y., & Sani, M. I.
Electricity generation at the hydropower stations in Nigeria has been below the expected value. While the hydro stations have a capacity to generate up to 2,380 MW, the daily average energy generated in 2017 was estimated at around 846 MW. A factor responsible for this is the lack of a proper control system to manage the transfer of resources between the cascaded Kainji-Jebba Hydropower stations operating in tandem. This paper addressed the optimal regulation of the operating head of the Jebba hydropower reservoir in the presence of system constraints, flow requirements and environmental factors that are weather-related. The resulting two-point boundary value problem was solved using the progressive expansion of domain technique as against the shooting or multiple shooting techniques. The results provide the optimal inflow required to keep the operating head of the Jebba reservoir at a nominal level, hence ensuring that the maximum number of turbo-alternator units are operated.
A Review of Microwave Cross Polarization in Sand and Dust Storms
(2019) Musa, Abdulwaheed
This paper presents a review of cross polarization in sand and dust storms (SDS). Relevant past works have been identified and their contributions to microwave cross polarization have been highlighted. Attention was given to semi-empirical models since they are used most readily for statistical predictions in design applications. The cross polarization mechanisms and parameters are also presented as well as a discussion about the advantages and the constraints of some of the models and their methodologies. Modified cross polarization discrimination (XPD) models for both terrestrial and slant links are proposed. Besides, the gaps in knowledge are established and the outlook of this topic in future is also suggested.
A Steepest Descent Algorithm for the Optimal Control of a Cascaded Hydropower System
(International Journal of Electrical and Computer Engineering (IJECE), 2020) Ogunbiyi, O., Thomas, C. T., Ogundepo, O. Y., Omeiza, I. O. A., Akanni, J., & Olufeagba, B. J.
Optimal power generation along the cascaded Kainji-Jebba hydroelectric power system had been very difficult to achieve. The reservoir's operating heads are being affected by possible variations in impoundments upstream, stochastic factors that are weather-related, availability of the turbo-alternators and power generated at any time. Proposed in this paper, is an algorithm for solving the optimal release of water on the cascaded hydropower system based on the steepest descent method. The uniqueness of this work is the conversion of the infinite-dimensional control problem to a finite one, the introduction of clever techniques for choosing the steepest descent step size in each iteration and the nonlinear penalty embedded in the procedure. The control algorithm was implemented in an Excel VBA® environment to solve the formulated Lagrange problem within an accuracy of 0.03%. It is recommended for use in system studies and control design for optimal power generation in the cascaded hydropower system.
A Study of Energy Conversion at the Jebba Hydroelectric Power Station
(IEEE 3rd International Conference on Electro-Technology for National Development (NIGERCON), 2017) Thomas C. T., Akorede M. F., Ogunbiyi O., Olufeagba B. J., & Samuel S. J.
Hydroelectric power significantly contributes to the national power grid of Nigeria. This paper examined the extent of utilization of the energy supplied into each of the turboalternators at the Jebba Hydroelectric Power Station (JHEPS), Nigeria and suggests a corrective culture to be employed for improved efficiency. The basic principle of a hydropower scheme and its conversion considerations were highlighted. The daily discharge, Q, in cumecs and the power generated, P, in MW at JHEPS over a decade period (2005 – 2014) were analyzed using codes and scripts of Microsoft EXCEL-VBA. Jebba hydroelectric power station is one of the three major hydropower stations in Nigeria and the potential is just beginning to be exploited. The stochastic distribution pattern of the station is also presented for further analysis of failure and repair of the station. The conversion behavior of each unit was found to be linear and all have a value greater than 0.5 on a scale of 0.00 to 1.00. Turbo-alternator (TA) unit 1 was found to have the highest conversion characteristic of 0.9951, while unit 4 was the least at 0.6884. However unit 6 was exempted in this analysis as it was not in use during this period. The paper also gave an insight into the effective operating head of each TA, the paper also suggests the corrective measure to employ for each turbine.
AI-driven demand forecasting for enhanced energy management in renewable microgrids: A hybrid lstm-cnn approach
(WisdomGale., 2024-12-29) Bashiru Olalekan Ariyo; Lambe Mutalub Adesina; Olalekan Ogunbiyi; Abdulwaheed Musa; Bilkisu Jimada Ojuolape; Monsurat Omolara Balogun
The increasing integration of renewable energy sources into microgrids (MGs) underscores the need for accurate demand forecasting to ensure stable and efficient MG operation. However, the inherent unpredictability of renewable energy sources presents significant challenges in energy management. This study aims to develop and validate an AI-driven demand forecasting model that improves prediction accuracy compared to traditional methods, thereby enhancing energy management in renewable MGs. A hybrid forecasting model that combines long short-term memory (LSTM) networks and convolutional neural networks (CNNs) was proposed. The model leverages historical energy consumption and meteorological data for training, ensuring robust and accurate predictions. Data preprocessing, training, and validation were performed meticulously to evaluate performance. The proposed model was compared with traditional forecasting techniques, including ARIMA and Exponential Smoothing, to assess its accuracy. The hybrid LSTM-CNN model demonstrated superior performance, achieving an R2 value of 0.87, a mean absolute error of 1.45 MWh, and a root mean squared error of 2.12 MWh. These results significantly outperform conventional forecasting methods, such as ARIMA and exponential smoothing, highlighting the model’s enhanced accuracy and ability to address key challenges in renewable energy forecasting. This study establishes the effectiveness of the hybrid LSTM-CNN approach in terms of improving the demand forecasting of renewable MGs. The model’s superior accuracy provides a reliable tool for real-time decision-making, energy distribution optimization, and cost reduction. Policymakers and energy stakeholders can use these insights to develop sustainable energy systems, with future research focusing on scaling up the model and exploring behavior and market pricing to improve forecasting precision.
AI-driven Demand Forecasting for Enhanced Energy Management in Renewable Microgrids: A Hybrid LSTM-CNN Approach
(WisdomGale, 2025) Musa
AJ-Olu-1: An Innovative Path Loss Model for Typical Nigerian Urban Environments
(KIU Journal of Science, Engineering and Technology, 2023) Akanni, J., Isa, A. A., Ogunbiyi, O., Olufeagba, B. J., & Sanni, T. A.
The modelling of outdoor path loss propagation is critical in the planning and construction of the Global System for Mobile Communication (GSM) coverage area. For GSM signal prediction at any location inside its service region, a precise forecast based on critical characteristics and a mathematical model is required. Numerous research findings on path loss propagation model forecast for GSM mobile networks conducted in various cities in Nigeria revealed that the COST-231-Hata model gives closer prediction to most of the practical measure path loss values. Based on the existing COST-23-Hata path loss model and outdoor measurements at 1800 MHz frequency range within the Ilorin metropolis, this paper proposed a suitable path loss model. The developed model was used and validated in various locations throughout Ilorin City with the measured and COST-231 Hata models. The analysis of the results revealed that the developed model performed satisfactorily in terms of the closest path loss prediction to the practical measure path loss values at all study locations. It also has the lowest Square Root Means Error and Standard Deviation (SD) of any Base Station (BTS) tested in Ilorin, Nigeria. As a result, it is concluded that the newly developed AJ-Olu-1 model is more suitable for GSM 1800 network design and installation in Ilorin City, Nigeria, as well as other cities in Nigeria and other cities outside Nigeria with similar environments.
Analysis of Cost-Effectiveness of Grid-Based and Off-Grid Electrification Designs in Nigeria
(MECS Press, 2022-10-08) Jimoh, Mojisola Adunola; Bello S. Raji
Analysis of Solar and Fossil Fuel Powered Base Transceiver Stations
(2019) Musa

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