Smart Antenna-Based Wideband Spectrum Detection in Cognitive Radio Networks

Abstract

Wideband spectrum sensing is a critical requirement in cognitive radio networks to reliably identify spectrum holes while ensuring minimal interference to licensed users. Conventional energy- and eigenvalue-based detection techniques often suffer from degraded performance under low signal-to-noise ratio (SNR) conditions and in dynamic spectral environments. In this paper, a smart antenna–based wideband detection framework for cognitive radio networks is proposed using the Hannan–Quinn (HQ) information criterion. The proposed system exploits the spatial diversity of smart antenna arrays to enhance signal reception and interference suppression, while the HQ criterion is employed for robust model order selection to accurately determine the presence of primary user signals across multiple frequency subbands. By jointly integrating spatial processing with information-theoretic detection, the proposed approach achieves improved detection reliability, particularly in low SNR and multi-signal scenarios. Extensive simulation results demonstrate that the proposed method outperforms conventional spectrum sensing techniques in terms of probability of detection, false alarm rate, and wideband detection accuracy. The results confirm the effectiveness of the HQ criterion–based smart antenna design as a viable solution for efficient wideband spectrum sensing in cognitive radio networks.