A Review of Performance Enhancement Techniques in Cognitive ‎Wireless Sensor Networks (CWSNs)‎

Abstract

Cognitive Wireless Sensor Networks (CWSNs) integrate Cognitive Radio (CR) capabilities with Wireless Sensor Networks (WSNs) to enable dynamic spectrum access and improve communication efficiency in intelligent environments. These networks address the limitations of traditional WSNs, such as fixed spectrum allocation, interference, and high energy consumption, making them suitable for modern Internet of Things (IoT) applications.

This paper presents a systematic and analytical review of recent research (2021–2025) on performance enhancement techniques in CWSNs. The study analyzes key approaches, including energy-efficient routing, intelligent spectrum sensing, security mechanisms, and hybrid optimization models. The findings indicate that integrating machine learning with cross-layer optimization significantly improves network lifetime, throughput, and adaptability. However, challenges remain in terms of scalability, computational complexity, and real-world implementation.