Wideband Cooperative Spectrum Sensing in 5G via MRC-Aided Energy Detection and K-out-of-N Decision Fusion: A Scalable Noise Resilient Framework for Dynamic Spectrum Access

Volume 16, Number 3/4/5

Wideband Cooperative Spectrum Sensing in 5G via MRC-Aided Energy Detection and K-out-of-N Decision Fusion: A Scalable Noise Resilient Framework for Dynamic Spectrum Access

Authors

Blessing C. Dike, Cajetan M. Akujuobi, Justin Foreman, Suxia Cui and Lin Li, Prairie View A&M University Prairie View, USA

Abstract

The rapid expansion of 5G use cases and dense IoT deployments has intensified pressure on scarce spectrum, making reliable wideband sensing indispensable for dynamic spectrum access (DSA). This work targets energy detector-based cooperative wideband spectrum sensing (CWSS) over multiple sub-bands in complex AWGN channels, where noise uncertainty and very low SNR commonly affect performance. We propose a CWSS architecture that applies maximal-ratio combining (MRC) at the pre-detection stage and employs a k-out-of-N fusion rule at the decision center. MRC boosts the effective per-sub-band SNR before thresholding, while the fusion mechanism aggregates local binary decisions to improve global reliability with modest reporting overhead. Comparative evaluations indicate that the MRC-aided ED with k-out-of-N consistently achieves higher detection probability for a given false-alarm rate across challenging low-SNR conditions, outperforming non-cooperative sensing and conventional CSS baseline. The results demonstrate that combining MRC with k-out-of-N fusion mitigates noise-uncertainty effects, strengthens wideband hole detection, and provides a practical sensing frontend for policy-compliant DSA in 5G environments.

Keywords

Dynamic Spectrum Access, 5G Networks, Internet of Things, Wideband Cooperative Spectrum Sensing, Energy Detection, Maximal-Ratio Combining, k-out-of-N Fusion Rule, Noise Uncertainty, Low-SNR