Novel Aninath Computation Detection Algorithm to Identify the UAV Users in 5G Networks

Cognitive Radio (CR) Network is a backbone for the 5G cellular Networks and Unmanned Aerial Vehicle (UAV) user identification at low power levels is a biggest task CR. Detection of UAV user is more difficult than the stable or fixed user. In the available literature various authors proposed their research with single detection algorithms low power levels as well as concatenation of two or three detection methods. To estimate the user presence the existing detection methods proposed with covariance based approach at static or predefined threshold power levels. In this paper, the authors proposed a novel Aninath computation detection algorithm to estimate the threshold dynamically with inverse covariance approach to improve the Probability of Detection (P-D) and mitigate the Probability of false alarm (P-fa) and Probability of miss detection (P-md) at low power levels.

Automated summary

Cognitive Radio Network serves as the backbone for 5G cellular networks and UAV user identification at low power levels is a challenging task. Existing methods rely on static or predefined threshold detection, while this paper proposes a novel approach for dynamic threshold estimation.