Cognitive Radio Networks for Dynamic Spectrum Access
DOI:
https://doi.org/10.15662/IJEETR.2023.0504002Keywords:
cognitive radio networks, dynamic spectrum access, spectrum sensing, spectrum management, cooperative sensing, wireless communication, spectrum sharingAbstract
Cognitive Radio Networks (CRNs) have emerged as a transformative solution to the increasing demand for wireless communication spectrum. Traditional fixed spectrum allocation policies have resulted in inefficient spectrum utilization, as many licensed frequency bands remain underutilized while others experience congestion. Dynamic Spectrum Access (DSA) enabled by cognitive radio technology allows secondary users to opportunistically access underutilized licensed spectrum without causing interference to primary users. This paper explores the fundamental principles, architectures, and challenges of CRNs in implementing DSA. A comprehensive review of spectrum sensing techniques, spectrum management, and spectrum sharing protocols is presented to evaluate their effectiveness in dynamic and heterogeneous wireless environments. The research methodology combines simulation-based performance analysis using NS-3 and analytical modeling to assess spectrum utilization, interference mitigation, and network throughput under various scenarios. Results indicate that advanced spectrum sensing algorithms, such as cooperative sensing and machine learning-based approaches, significantly improve detection accuracy and reduce false alarms, enabling more reliable spectrum access decisions. Furthermore, adaptive spectrum management protocols optimize resource allocation, enhancing network efficiency and user Quality of Service (QoS). Challenges including spectrum sensing overhead, hidden node problems, and security vulnerabilities are also discussed. The study concludes that CRNs with effective DSA mechanisms hold great promise for alleviating spectrum scarcity and improving wireless network capacity. Future research should focus on enhancing sensing accuracy, reducing latency in spectrum decision-making, and developing robust security frameworks to protect against malicious attacks. This work contributes valuable insights for researchers, network designers, and policymakers aiming to optimize spectrum utilization through cognitive radio technologies.
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