Power-domain non-orthogonal multiple access (NOMA) is one of the key technologies in 5G communica-tions, enabling efficient multi-user transmission over the same time-frequency resources through power multiplexing. In this study, an improved max-min relay selection strategy was proposed for NOMA cooperative communication systems to address the issue of insufficient channel fairness in conventional strategies. The proposed strategy optimizes the relay selection process with the objective of ensuring channel fairness. Theoretical derivations and simulation analyses were conducted to comprehensively evaluate the proposed strategy from the perspectives of user throughput and system outage probability. The results demonstrate that, compared to the conventional max-min strategy and other commonly used relay selection methods, the proposed strategy significantly reduces the system outage probability while enhancing user throughput, thereby verifying its superiority in improving system reliability and stability.
A wide range of safety hazards exist in underground coal mines, characterized by unpredictability, randomness, and coupling effects. The increasing structural complexity and diversity of underground equipment present new challenges for fault state monitoring and diagnosis. To address the unique characteristics of underground equipment fault diagnosis, a characterization model of vibration hazards was proposed, integrating a time-frequency mask-based non-stationary filtering technique and sparse representation. Experimental analysis demonstrates that the time-frequency mask algorithm effectively filters out sharp non-stationary noise, restoring the original stationary healthy signal. Compared to Support Vector Machine (SVM), Convolutional Neural Network (CNN), and Principal Component Analysis (PCA), the sparse representation algorithm exhibits superior performance in characterizing vibration hazards, achieving the highest accuracy.
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