Browsing by Author "Abdulkarim, Oloyede"

Now showing 1 - 8 of 8
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    Application of Computational Intelligence Algorithms in Radio Propagation: A Systematic Review and Metadata Analysis
    (Mobile Information Systems, 2021-01-21) Quadri, Ramon; Nasir, Faruk; Kayode, Adewole; Abubakar, Abdulkarim; Lukman, Olawoyin; Abdulkarim, Oloyede; Haruna, Chiroma; Aliyu, Usman; Carlos, Calafate
    The importance of wireless path loss prediction and interference minimization studies in various environments cannot be over- emphasized. In fact, numerous researchers have done massive work on scrutinizing the effectiveness of existing path loss models for channel modeling. The difficulties experienced by the researchers determining or having the detailed information about the propagating environment prompted for the use of computational intelligence (CI) methods in the prediction of path loss. This paper presents a comprehensive and systematic literature review on the application of nature-inspired computational approaches in radio propagation analysis. In particular, we cover artificial neural networks (ANNs), fuzzy inference systems (FISs), swarm intelligence (SI), and other computational techniques. The main research trends and a general overview of the different research areas, open research issues, and future research directions are also presented in this paper. This review paper will serve as reference material for researchers in the field of channel modeling or radio propagation and in particular for research in path loss prediction.
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    Energy Consumption in Perpetual Wireless Sensor Networks
    (Zaria Journal of Electrical Engineering Technology, Department of Electrical Engineering, Ahmadu Bello University, Zaria, 2020-09-30) Abdulkarim, Oloyede; Lukman, Olawoyin; Faruk, Nasir; Abdulkarim, Abubakar; ABdulrahman, Otuoze
    Abstract: This paper investigates the amount of energy consumed in different configuration for perpetual wireless sensor networks. Wireless Sensor Networks (WSNs) represent an area of networking that become pivotal in many applications. The use of WSNs for the monitoring of environments, habitats as well as systems within industry and healthcare has made WSNs a crucial area of research within recent years. The principles behind WSNs involve the deployment of remote sensing and relay nodes, able to collect and transmit raw data for processing. Applications such as remote environmental monitoring present new challenges such as the prospect of developing networks that can operate perpetually to collect data for as long as possible. Simulation and theoretical analysis were done using the networking simulator DENSE. DENSE is presented to provide insight into what protocols and energy saving techniques can be employed to establish the possible feasibility of constructing PWSN. The results show that mesh is the most realistic due to its energy distribution and optimization over a large area for a great number of nodes; however, a small single hop based network can provide good result for energy consumption and packet success rates.
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    Hybridization of OFDM and Physical Layer Techniques for Information Security in Wireless System.
    (by Sule Lamido University Journal of Science & Technology, 2023-03-31) Lukman .A, Olawoyin; Abdul -Rahman, Musrafah; Nasir, Faruk; Abdulkarim, Oloyede; Temitayo, Adeniran; Imam-Fulani, Yusuf; Olabamji, Lasisi; Sikiru, Ismaeel; Bashir, Abdullahi Baba
    Due to quest for high data rate, reliable and secure communication, this has motivated both wired and wireless network access service providers to deploy a next-generation network with ability to meet the required need. The use orthogonal frequency division multiplexing (OFDM) enables reliable transmission of various data traffic by optimizing subcarrier, power, and allocation of bits among different users. Traditionally, securing data in wireless system is always at the upper layer of open system interconnection (OSI) Model by using data encryption techniques. However, such techniques may not be acceptable for future decentralized networks due to their high complexity in implementation and computation. In this work, an OFDM IEEE 802.11a wireless system is used and physical layer encryption (PLE) schemes are implemented in securing the information transfer between two legitimate parties. In the simulation, the source data are encrypted by obfuscation with dummy data in between the encrypted data of which 52 subcarriers were considered of which 25 subcarriers are reserved for dummy data and 27 were for data. The simulation was conducted for four different modulation techniques i.e., BPSK, QPSK, 16 QAM, and 64 QAM. The result obtained shown that for all the modulation schemes, the key rate increases with an increase in the reserved subcarrier bits. Also, the security level increased when substantial percentages of the subcarriers are reserved for dummy data.
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    Path Loss Predictions in the VHF and UHF Bands Within Urban Environments: Experimental Investigation of Empirical, Heuristics and Geospatial Models
    (Institute of Electrical and Electronics Engineers, 2019-06-01) Nasir, Faruk; Segun, Popoola; Bakinde, Surajudeen; Abdulkarim, Oloyede; Lukman A, Olawoyin; Mudathir, Akorede; Adulkader, Madugu; J.D, Morrow; Yinusa, Adediran
    Deep knowledge of how radio waves behave in a practical wireless channel is required for effective planning and deployment of radio access networks in urban environments. Empirical propagation models are popular for their simplicity, but they are prone to introduce high prediction errors. Different heuristic methods and geospatial approaches have been developed to further reduce path loss prediction error. However, the efficacy of these new techniques in built-up areas should be experimentally verified. In this paper, the efficiencies of empirical, heuristic, and geospatial methods for signal fading predictions in the very high frequency (VHF) and ultra-high frequency (UHF) bands in typical urban environments are evaluated and analyzed. Electromagnetic field strength measurements are performed at different test locations within four selected cities in Nigeria. The data collected are used to develop path loss models based on artificial neural network (ANN), adaptive neuro-fuzzy inference system (ANFIS), and Kriging techniques. The prediction results of the developed models are compared with those of selected empirical models and field measured data. Apart from Egli and ECC-33, the root mean squared error (RMSE) produced by all other models under investigation are considered acceptable. Specifically, the ANN and ANFIS models yielded the lowest prediction errors. However, the empirical models have the lowest standard deviation errors across all the bands. The findings of this study will help radio network engineers to achieve efficient radio coverage estimation; determine the optimal base station location; make a proper frequency allocation; select the most suitable antenna; and perform interference feasibility studies.
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    Reliability Study of Stand-alone Hybrid Renewable Energy Microgrids
    (Iran J Sci Technol Trans Electr Eng, 2018-10-18) Bakinde, Surajudeen; Faruk, Nasir; Segun, Popoola; Muhammad, Salman; Abdulkarim, Oloyede; Lukman A, Olawoyin; C.T, Calafate
    This paper proposed new indices for investigating the reliability of the microgrid at different levels. The microgrid used has been developed in DigSILENT software and is comprised of wind, solar, battery storage and a diesel generator. The software was used to observe the effect of system demand and the failure rate of each component at three indices levels. Different simulations had shown that an increase in the system demand affects average energy not supplied, EIC, and average customer curtailment index. Also, at load point, LPIC and load point energy not supply among others are sensitive to system demand. This work proposes a new approach to study the effect of network structure on the reliability of a microgrid. The proposed method employs the prioritization of component importance on microgrid configuration. The results obtained show that the contribution of components to the system’s reliability depends on the network structure. This could be used in identifying direction, priority, and upgrading and suggests the most efficient way to operate and maintain a microgrid.
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    Secure transmission in an unfriendly environment
    (Published by Elsevier BV, 2019-10-01) Lukman A, Olawoyin; Faruk, Nasir; Abdulkarim, Oloyede; Segun, Popoola; Temitayo, Adeniran; Bakinde, Surajudeen; Abdulkarim, Abubakar
    This work investigates and show the performance of destination assisted node in ensuring secure communication in a dual-hop broadcast system. The information transmission occurs between the transmitters which are assumed to be equipped with single antenna through a number of intermediate untrusted relays to the receiver in the presence of multiple passive eavesdroppers. This work assumes that there is no direct link between the transmitter and the receiver and hence, the relay node, receives either the information or noise signal at every transmission processes. Since the transmission occurs in a two-phase, the legitimate receiver is contributing a degrading noise to both the eavesdropper and relay node channels during the first phase while it receives information from the transmitter through the relay during the second phase. Simulation results are used to illustrate the performance of the proposed scheme.
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    State of the Art in Research on Optimum Design, Reliability and Control of Renewable Energy Microgrids
    (2018-10-01) Abdulkarim, Abubakar; Faruk, Nasir; Abdulkarim, Oloyede; LUkman A, Olawoyin; Segun, Popoola; Abdullateef, Ibrahim; Yinusa, Adeniran
    This paper has presented a comprehensive review in the area of microgrid from the design to implementation. The aim is to evaluate the current status, problems and research efforts toward realising functional microgrids in the power system. The expectations about microgrid are many; therefore the study is divided into three main sections. Recent advancements in the wind energy, solar energy and their future prediction are summarised. States of arts in optimum design of renewable energy microgrid are also investigated. In addition, critical literature review in the reliability analysis of microgrids consisting of renewable energy sources is also reported. Control of microgrids consisting renewable energy sources have been presented. Some examples of existing microgrids across the globe are critically reviewed. The work therefore recommends that energy planners and all stakeholders should consider environmental and regional difference in microgrids planning. Finally, future research areas and directions in these areas are highlighted.
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    A systematic review and Meta-data analysis on the applications of Deep Learning in Electrocardiogram.
    (Journal of Ambient Intelligence and Humanized Computing., 2022-01-15) Musa, Nehemiah; Gital, Abdulsalam Yau; Aljojo, Nahla; Haruna, Chiroma; Kayode, Adewole; Majeed, Hammed; Faruk, Nasir; Abdulkarim, Abubakar; Ifada, Emmanuel; Yusuf, Folawiyo; Abdulkarim, Oloyede; Lukman, Olawoyin; Sikiru, Ismaeel; Ibrahim, Katibi
    The success of deep learning over the traditional machine learning techniques in handling artificial intelligence application tasks such as image processing, computer vision, object detection, speech recognition, medical imaging and so on, has made deep learning the buzz word that dominates Artificial Intelligence applications. From the last decade, the applica- tions of deep learning in physiological signals such as electrocardiogram (ECG) have attracted a good number of research. However, previous surveys have not been able to provide a systematic comprehensive review including biometric ECG based systems of the applications of deep learning in ECG with respect to domain of applications. To address this gap, we conducted a systematic literature review on the applications of deep learning in ECG including biometric ECG based systems. The study analyzed systematically, 150 primary studies with evidence of the application of deep learning in ECG. The study shows that the applications of deep learning in ECG have been applied in different domains. We presented a new taxonomy of the domains of application of the deep learning in ECG. The paper also presented discussions on bio- metric ECG based systems and meta-data analysis of the studies based on the domain, area, task, deep learning models, dataset sources and preprocessing methods. Challenges and potential research opportunities were highlighted to enable novel research. We believe that this study will be useful to both new researchers and expert researchers who are seeking to add knowledge to the already existing body of knowledge in ECG signal processing using deep learning algorithm.