论文标题
频谱智能广播：技术，开发和未来趋势
Spectrum Intelligent Radio: Technology, Development, and Future Trends
论文作者
论文摘要
具有大量连通性的行业4.0的出现在当前的频谱资源上占据了重大压力，并挑战了行业和监管机构以新的破坏性频谱管理策略迅速做出反应。当前具有某些智能元素的无线电开发尚未显示出对复杂无线电环境的敏捷响应。遵循情报线，我们建议将频谱智能无线电分类为三个流：经典信号处理，机器学习（ML）和上下文适应。我们专注于ML方法，并提出了一种具有三种层次形式的新智能无线电架构：感知，理解和推理。提出的感知方法实现了完全盲目的多层次谱传感。理解方法准确地预测了主要用户在大面积上的覆盖范围，而推理方法执行了近乎最佳的空闲通道选择。还讨论了机会，挑战和未来的愿景，以实现完全智能的广播。
The advent of Industry 4.0 with massive connectivity places significant strains on the current spectrum resources, and challenges the industry and regulators to respond promptly with new disruptive spectrum management strategies. The current radio development, with certain elements of intelligence, is nowhere near showing an agile response to the complex radio environments. Following the line of intelligence, we propose to classify spectrum intelligent radio into three streams: classical signal processing, machine learning (ML), and contextual adaptation. We focus on the ML approach, and propose a new intelligent radio architecture with three hierarchical forms: perception, understanding, and reasoning. The proposed perception method achieves fully blind multi-level spectrum sensing. The understanding method accurately predicts the primary users' coverage across a large area, and the reasoning method performs a near-optimal idle channel selection. Opportunities, challenges, and future visions are also discussed for the realization of a fully intelligent radio.
