Cognitive Radio Networks for Wireless Communications using Spectrum Sensing Technique: A Review - Shweta Kumari,Dr. Ram Milan Chadhar (International Journal of Advanced Research and Multidisciplinary Trends (IJARMT), 2025)
The exponential growth of wireless communication technologies has led to an increasing demand for radio spectrum, resulting in inefficient utilization and severe spectrum scarcity issues. Cognitive Radio Networks (CRNs) have emerged as a promising solution to address this challenge by enabling dynamic spectrum access. CRNs allow unlicensed users, known as secondary users (SUs), to opportunistically utilize the underutilized spectrum allocated to licensed or primary users (PUs) without causing harmful interference. Among the core functions of CRNs, spectrum sensing plays a pivotal role in detecting vacant spectrum bands (spectrum holes) and ensuring seamless and interference-free communication. This review provides a comprehensive analysis of various spectrum sensing techniques used in CRNs, including energy detection, matched filtering, cyclostationary feature detection, and cooperative sensing. Each technique is examined in terms of its operational principles, advantages, limitations, and applicability under different signal and channel conditions. The paper also discusses key performance metrics such as probability of detection, false alarm rate, and sensing time, which are critical for evaluating sensing accuracy. Furthermore, the review highlights recent advances such as machine learning-based sensing, compressive sensing, and their potential integration with emerging technologies like 5G, 6G, and IoT. The paper concludes by identifying key challenges and proposing future research directions aimed at improving the efficiency, reliability, and adaptability of spectrum sensing in cognitive radio networks.