| 引用本文： |
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周妍彤,胡春静,彭涛,等.毫米波系统中的定向波束干扰识别与SINR预测[J].电讯技术，2026，（4）：672 - 680. [点击复制]
- ZHOU Yantong,HU Chunjing,PENG Tao,et al.Identifying Interference and Predicting SINR Using Directional Beams in Millimeter-wave Systems[J].，2026，（4）：672 - 680. [点击复制]
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| 摘要: |
| 为应对传统低频无线通信系统频谱短缺的挑战，毫米波已成为下一代通信的关键技术。为了实现资源合理分配，需准确识别不同干扰源，而精确的干扰识别依赖于精准的干扰建模。目前，毫米波系统常采用的统计干扰模型适用于分析长期系统性能，即系统在稳定信道条件下的稳态表现，然而，短期系统性能分析需要考虑信道状态动态变化的特性。因此，提出了一种定向波束干扰识别模型，采用更合理的天线波束和信道模型，并充分考虑了多径效应的影响，能有效评估短期系统性能。基于该模型，进一步采用智能算法实现了对每个干扰源的精细识别及信干噪比的精准预测，为资源分配提供支持。仿真结果表明，所提算法相比基准方案在预测精度上提高了4.720%~35.077%。 |
| 关键词: 毫米波系统 定向波束干扰识别 信干噪比预测 资源分配 |
| DOI：10.20079/j.issn.1001-893x.241222003 |
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| 基金项目:国家重点研发计划（2022YFB3303700） |
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| Identifying Interference and Predicting SINR Using Directional Beams in Millimeter-wave Systems |
| ZHOU Yantong,HU Chunjing,PENG Tao,GUO Yichen,WANG Wenbo |
| (Key Laboratory of Universal Wireless Communication，Ministry of Education，Beijing University of Posts and Telecommunications，Beijing 100876，China) |
| Abstract: |
| To address spectrum scarcity in traditional low-frequency wireless communication systems，millimetre wave(mmWave) has emerged as a critical technology for the next-generation communications.Accurate interference identification is key to efficient resource allocation，achievable through a precise interference model.In mmWave systems，the prevailing statistical interference models are typically designed for long-term performance analysis，focusing on stable channel state information(CSI) and consistent interference and noise，but are inadequate for short-term scenarios where CSI may fluctuate.The authors propose a directional beam interference identification model that not only uses more realistic antenna beam and channel models but also crucially incorporates the multipath effect，enabling the assessment of short-term system performance.Based on the above model，they adopt intelligent algorithms to accurately identify interference from each source and predict signal-to-interference-plus-noise ratio(SINR) to support resource allocation.Numerical results show that the proposed algorithm improves the prediction accuracy by 4.720% to 35.077% versus the benchmark scheme. |
| Key words: mmWave systems directional beam interference identification SINR prediction resource allocation |
《电讯技术》编辑部 