Browsing by Author "Ehiagwina, F. O."

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    An Overview of Applications of Cognitive Wireless Communication Simulators
    (Faculty of Engineering, University of Ilorin, Ilorin, 2023-06-05) Ehiagwina, F. O.; Surajudeen-Bakinde, N. T.; Afolabi, A. S.; Afolabi, L. O.; Usman, A. M.
    Cognitive radio is proposed in the literature to address the ironical problem of spectrum scarcity owing to inefficient utilisation. This idea has recently gained popularity because it provides wireless users with the ability to detect and efficiently adapt operating parameters based on interactions with the surrounding radio environment. In the evaluation of cognitive radio networks simulators are used. The simulators differ in terms of platforms and technicalities. Thus making selection process difficult. In this review, attention is paid to cognitive radio network simulators such as Network Simulator 2 and 3 (NS-2) and (NS-3), Java Simulator (J-Sim), Operations Network (OPNET) and MATLAB. In the selection of literature covered in this review, attention was paid to publications not later than 2017 from reputable databases. This review of cognitive radio network simulators will provide useful insights to new researchers in this field. Furthermore, a case study is reported on the application of the Monte Carlo simulation method to the cognitive radio network.
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    Analysing Gene Expression Data of Patients with and without Ovarian Cancer using Dynamic Mode Decomposition
    (Faculty of Engineering and Technology, University of Ilorin, Ilorin., 2023) Usman, A. M.; Surajudeen-Bakinde, N. T.; Ehiagwina, F. O.; Afolabi, A. S.; Oloyede, A. A.; Zakariya, O. S.
    Machine learning (ML) algorithms have been deployed in recent years as models for the analysis of complex data. The ubiquity of ML algorithms stems from their ability to learn the patterns and structures inherent in data. In addition, they are adaptable to a wide range of data types, irrespective of size, which allows them to learn and predict the future pattern of data. In this work, dynamic mode decomposition (DMD), an ML algorithm, is deployed to analyse the pattern of gene expression data from patients with and without ovarian cancer. Ovarian cancer is one of the deadliest gynaecologic cancers in the world. The obscure nature of the symptoms makes early detection of ovarian cancer difficult. If the disease is diagnosed early, the chance of survival increases for patients. In this work, DMD is applied to analyse gene expression data from patients with and without ovarian cancer to understand the spatiotemporal patterns of the data. The DMD modes captured the prevalent structures and predicted the future state of the data. The results obtained show that DMD is a promising algorithm that can predict the features inherent in gene expression for patients with and without ovarian cancer. The DMD modes can further be applied as features to train detection and classification models that can assist health practitioners in the quest for early detection of ovarian cancer through gene expression data.
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    Sensitivity Degradation and Antenna Isolation Analyses for a Multi-Operator Global Systems for Mobile Communication Base Transceiver Stations
    (Faculty of Engineering, University of Nigeria, Nsukka, (UNN) Nigeria., 2019) Ehiagwina, F. O.; Afolabi, A. S.; Surajudeen-Bakinde, N. T.; Fakolujo, O. A.
    In other to mitigate challenges associated with the expansion of Global System for Mobile Communication (GSM) systems, infrastructure sharing have been proposed and adopted by some GSM operators. When infrastructure sharing is done, there is the possibility of degradation of quality of service due to Electromagnetic Compatibility issues, interference between operators, sensitivity degradation, increasing noise floor, antenna isolation requirement issue. This paper analyses the sensitivity degradation and the effects of spatial separation on antenna isolation requirement of Base Transceiver Station (BTS) receiver for a multi-operator mobile cellular systems. The data used were extracted from standards of organisation like European Telecommunications Standards Institute (ETSI) standards and others. Antenna dimension were obtained from physical observations of BTS site. By comparison with identified metrics in the standards, we verified that the number of operators that can share infrastructure is limited by the allowable sensitivity degradation. It was noted that an antenna isolation of 70dB can be achieved for GSM 900 band antennas and when GSM 1800 band antennas are used, 90dB antenna isolation is achievable greater than the minimum recommendation of 30dB.