| 摘要: |
| 海量机器类通信（Massive Machine-type Communications，mMTC）是物联网的核心应用场景，其大规模设备高效接入依赖于精准快速的活跃用户检测（Active User Detection，AUD）。针对当前大规模AUD技术中导频序列矩阵硬件实现复杂度高、检测算法开销大的瓶颈问题，提出了系统性解决方案。首先，引入免于授予（Grant-free）传输机制以简化信令流程；其次，构建检测系统模型，并提出基于稀疏图码的导频序列矩阵构造方法，同步设计适配该矩阵结构的高效活跃设备检测算法。仿真结果表明，在无噪声场景下，当导频序列长度大于300时，所提算法的检测成功率超过95%，且能以更短的导频序列达到与传统方法相当的检测成功率；在有噪声环境下，所提算法在低信噪比条件下展现出更优的鲁棒性，其检测成功率较经典的算法有明显提升。 |
| 关键词: 物联网 海量机器类通信 活跃用户设备检测 导频序列矩阵 免于授予 稀疏图码 |
| DOI：10.20079/j.issn.1001-893x.251012002 |
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| 基金项目:国家自然科学基金资助项目（62471486，62501637）；江苏省自然科学基金项目（BK20231485）；淮安市自然科学研究项目（HABZ202223，HABL202215） |
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| Sparse Graph Code-driven Grant-free Active Device Detection Method for Internet of Things |
| ZHOU Huaqiao,ZHU Lei,XU Kui,SUN Yifan,ZHANG Beihua,ZENG Mingcong |
| (1.College of Communication Engineering，Army Engineering University of PLA，Nanjing 210007，China;2.Jiangsu Industrial Cloud Edge Collaborative Technology Engineering Research Center，Huai′an 223001，China) |
| Abstract: |
| Massive machine-type communications (mMTC) is a core application scenario of the Internet of Things，where the efficient access of massive devices relies on accurate and rapid active user detection (AUD).To address the bottleneck problems of high hardware implementation complexity of the pilot sequence matrix and large overhead of the detection algorithm in current large-scale AUD technology，a systematic solution is proposed.First，a grant-free transmission mechanism is introduced to simplify the signaling process.Second，a detection system model is constructed，and a pilot sequence matrix construction method based on sparse graph codes is proposed，together with an efficient active device detection algorithm adapted to this matrix structure.Simulation results show that in a noise-free scenario，when the pilot sequence length exceeds 300，the proposed algorithm achieves a detection success rate of over 95%，and it can reach a detection success rate comparable to that of traditional methods with a shorter pilot sequence.In a noisy environment，the proposed algorithm exhibits better robustness under low signal-to-noise ratio conditions，and its detection success rate is significantly improved compared with classical algorithms. |
| Key words: Internet of Things massive machine-type communication active user device detection pilot sequence matrix grant-free sparse graph code |
《电讯技术》编辑部 