Critical Factors are Affecting the Application of Information Theory in Broadband Communication Channel Capacity

Shah, Yasir; Ullah, Ameen

doi:10.2478/ijanmc-2025-0025

Abstract

This study investigates the optimization of broadband communication channel capacity through an integrative information-theoretic framework. Leveraging Shannon’s theory, it examines fundamental constraints such as bandwidth limitations, channel noise, modulation techniques, error correction mechanisms, and adaptive systems. A comprehensive literature review of 118 articles identified 18 critical enablers, which were evaluated by domain experts. The Fuzzy DEMATEL method was employed to prioritize enablers based on interdependencies and influence. Results indicate that Security Considerations, Channel Access Protocols, and Propagation Characteristics exert the most significant impact on capacity optimization. The findings offer a structured decision-making model for stakeholders, enabling efficient allocation of technological, infrastructural, and human resources. By bridging theoretical principles with practical implementation, this research provides actionable insights for academic researchers and industry practitioners in designing robust, high-capacity broadband systems. The integrative modeling approach advances the application of information theory in modern communication networks, supporting informed technology adoption and system integration.

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Critical Factors are Affecting the Application of Information Theory in Broadband Communication Channel Capacity

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