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Optimizing Telecommunications Network Performance: A Comprehensive Review and Analysis

Author(s)
Emmanuel Atebawone; Joseph Wumboranaan Nanjo; Owusu Agyeman Antwi; Ruhiya Abubakar
Article Type
Journal Articles
Issue
Issue 2 (2023)
Article Category
Journal Artcle
Department
Department of Telecommunications Engineering / Department of Electrical & Electronic Engineering
Keywords
Telecommunications Networks Network Performance Quality of Service (QoS) Traffic Management Software-Defined Networking (SDN) Network Function Virtualization (NFV) Artificial Intelligence Machine Learning Big Data Analytics 5G Internet of Things (IoT) Network Monitoring
This study presents a comprehensive review of strategies for optimizing telecommunications network performance in response to increasing user demands and evolving communication technologies. It examines optimization techniques including traffic management, resource allocation, Quality of Service (QoS), Software-Defined Networking (SDN), Network Function Virtualization (NFV), Artificial Intelligence (AI), Machine Learning (ML), and big data analytics. The paper also discusses security considerations, emerging technologies such as 5G and IoT, network performance monitoring, and practical optimization strategies. The findings emphasize that integrating advanced technologies with strategic network management improves efficiency, scalability, reliability, and quality of service while ensuring secure and sustainable telecommunications infrastructure.
Nsor-Anabiah, S., Abubakar, R., Antwi, O. A., Agyare, M., Nanjo, J. W., & Atebawone, E. Optimizing Telecommunications Network Performance: A Comprehensive Review and Analysis.
Nsor-Anabiah, S., Abubakar, R., Antwi, O. A., Agyare, M., Nanjo, J. W., and Atebawone, E. conducted a comprehensive review of techniques for optimizing telecommunications network performance. The study evaluates the impact of bandwidth, latency, packet loss, jitter, throughput, and congestion on network quality, while examining optimization technologies including AI, Machine Learning, Software-Defined Networking (SDN), Network Function Virtualization (NFV), 5G, IoT, cloud computing, and Quality of Service (QoS). The paper concludes that combining intelligent network management with modern virtualization and analytics technologies significantly enhances network reliability, scalability, efficiency, and user experience.
Related research areas include Telecommunications Engineering, Network Optimization, Network Performance Analysis, Software-Defined Networking (SDN), Network Function Virtualization (NFV), Artificial Intelligence for Networking, Machine Learning, Quality of Service (QoS), Network Monitoring, Cloud Computing, Internet of Things (IoT), 5G Networks, Edge Computing, Big Data Analytics, Cybersecurity, Wireless Communications, and Smart Network Management.
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Added 15 Jul 2026


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