Xu, Tianheng; Xu, Yinjun; Wu, Jingyi; Zhang, Haijun; Zhou, Ting; Hu, Honglin; Leung, Victor C. M.

IEEE TRANSACTIONS ON WIRELESS COMMUNICATIONS

2025, 11,

Xu, Tianheng; Xu, Yinjun; Wu, Jingyi; Zhang, Haijun; Zhou, Ting; Hu, Honglin; Leung, Victor C. M.

Next-generation Internet of Things(IoT) technology is vital for sixth-Generation(6G) communication systems, driving exponential growth in spectrum resource demand. Spectrum sensing, essential for identifying unused spectrum, and Non-Orthogonal Multiple Access(NOMA), which allows efficient frequency band sharing among users, can significantly improve spectrum efficiency. However, current sensing methods do not fully support NOMA, resulting in suboptimal performance. Motivated by such a circumstance, we propose a feature-based spectrum sensing method for uplink communication in power-domain NOMA IoT scenarios with multi-user interference, aiming to maximize both static and dynamic spectrum efficiency. Firstly, we introduce the notion of orbits to represent non-fully occupied spectral holes. Then we elaborate on the sensing criterion as well as workflow and design the two-stage spectrum sensing framework, which proposes the orbit estimation sensing algorithm in the stage 1 and accurate sensing threshold in the stage 2, to mitigate false alarm fluctuations. The closed-form solution for the estimation threshold and accurate threshold configuration are derived thereafter. Simulation results show that our proposed multi-orbit sensing method has stable performance and achieves average 30% system throughput gains compared to the latest NOMA techniques at 5 dB.