<![CDATA[Spectrum sensing (SS) is essential for cognitive radio (CR) networks to enable secondary users to opportunistically access unused spectrum without interfering with primary users. This article proposes a novel multi-user detection (MUD) and square-law combining (SLC) framework for SS in multiple-input multiple-output (MIMO) and orthogonal frequency division multiplexing (OFDM) CR networks. Traditional SS methods, especially energy detection (ED), often underperform in low signal-to-noise ratio (SNR) conditions, resulting in high false alarm rates due to noise uncertainty and multi-user interference. The multi-user detection-square-law combining (MUD-SLC) framework addresses these limitations by using MUD to separate user signals and SLC to combine energy from multiple antennas, significantly improving probability of detection (PD) while maintaining a low false alarm probability (Pfa). Simulation results show that the proposed approach achieves a PD of 0.81 at Pfa=0.15 and SNR=15 dB, outperforming conventional and advanced SS methods. Moreover, MUD-SLC demonstrates a considerable boost in detection performance, even in the presence of severe interference and noise uncertainty, leading to more reliable spectrum utilization in systems. The framework also maintains a lower Pfa, especially in dynamic wireless environments. This research work contributes to improving the efficiency and reliability of SS in CR networks.]]>
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