Browsing by Author "Kponyo, Jerry John"

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    Design of pattern-reconfigurable circularly polarized unidirectional antenna based on quasi-radiator for ISM applications
    (Heliyon, 2022-11-21) Arthur, Philip; Ellis, Mubarak Sani; Ahmed, Abdul-Rahman; Kponyo, Jerry John
    A pattern-reconfigurable circularly polarized antenna for 2.45 GHz industrial, scientific, and medical (ISM) band applications is designed in this work. The proposed antenna consists of a slotted-stepped monopole connected to a rectangular ground plane via a shorting side-stub. This converts the omnidirectional radiation pattern of the antenna into stable unidirectional radiation. To dynamically steer the realized pattern, two switchable RF PIN diodes are jointly incorporated into the side-stubs to achieve symmetrical radiations in specific operating modes. In this way, the radiation patterns can be simultaneously tuned in the y directions by the simple switching of the PIN diodes ON and OFF. The fabricated prototype achieves an S11 smaller than -10dB within the 3dB axial ratio (AR) bandwidth with stable far-field patterns. The antenna maintains a low-profile and compact size of 0:055λ20 which makes it suitable for body-centric wireless communication (BWC) and personal wireless area networks.
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    Resource Provisioning and Utilization in 5G Network Slicing: A Survey of Recent Advances, Challenges, and Open Issues
    (International Journal of Computer Networks and Applications (IJCNA), 2023-03) Asakipaam, Simon Atuah; Kponyo, Jerry John; Gyasi, Kwame Oteng
    The increasing demands for higher bandwidth and lower latency in modern telecommunications networks have led to the exploration of network slicing as a means to meet these requirements more efficiently in next-generation 5G networks. Despite substantial academic interest in resource allocation and management in network slicing, existing research is dispersed and fragmented. This study presents a categorization and assessment of the latest research on resource allocation and optimization techniques in 5G network slicing. It also shows how advanced machine learning techniques can support resource management in sliced wireless networks. The present paper offers a complete overview and analysis of current solutions for resource allocation and management in 5G network slicing, outlines open research challenges, and suggests future research directions for researchers and engineers in this field.