Exploiting Self-Similarity for Under-Determined MIMO Modulation Recognition
Exploiting Self-Similarity for Under-Determined MIMO Modulation Recognition
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DOI：
10.1109/infocom41043.2020.9155247
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发表时间：
2020-07
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影响因子：
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通讯作者：
Wei Xiong;Lin Zhang;M. McNeil;Petko Bogdanov;M. Zheleva
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作者：
Wei Xiong;Lin Zhang;M. McNeil;Petko Bogdanov;M. Zheleva
调制识别(MODEC)是未来无线网络的重要功能组件，在动态频谱接入中具有关键应用。虽然主要研究的是单输入单输出(SISO)系统，但用于多输入多输出(MIMO)通信的实用模型需要更多的研究。现有的MIMO模型对完全或超定感知前端提出了严格的要求，即传感器天线的数量应该超过发射机的数量。即使对于简单的2x2 MIMO系统，这也带来了高昂的传感器成本，并将严重阻碍高级高阶MIMO在灵活频谱接入方面的进展。我们设计了一种MIMO MODREC框架，该框架能够对传感器天线数量少于传输天线的欠确定环境进行高效和低成本的调制分类。我们的主要思想是利用MIMO调制智商星座固有的多尺度自相似性，这种自相似性在欠确定的环境中持续存在。该框架通过总结MIMO星座中符号共定位的规律，设计了具有高分辨能力的域感知分类特征。为此，我们总结了观测样本的分形几何，以提取用于有监督MIMO模型的可区分特征。我们在真实的模拟和小规模的MIMO试验台上评估了对称性。我们证明了它在不同的噪声状态、信道衰落条件下以及随着MIMO发射机复杂度的增加而保持了高和一致的性能。我们的努力突出了对称性的高潜力，以实现高效和实用的MIMO模式。
Modulation recognition (modrec) is an essential functional component of future wireless networks with critical applications in dynamic spectrum access. While predominantly studied in single-input single-output (SISO) systems, practical modrec for multiple-input multiple-output (MIMO) communications requires more research attention. Existing MIMO modrec impose stringent requirements of fully- or over-determined sensing front-end, i.e. the number of sensor antennas should exceed that at the transmitter. This poses a prohibitive sensor cost even for simple 2x2 MIMO systems and will severely hamper progress in flexible spectrum access with advanced higher-order MIMO.We design a MIMO modrec framework that enables efficient and cost-effective modulation classification for under-determined settings characterized by fewer sensor antennas than those used for transmission. Our key idea is to exploit the inherent multi-scale self-similarity of MIMO modulation IQ constellations, which persists in under-determined settings. Our framework called SYMMeTRy (Self-similarit Y for MIMO ModulaTion Recognition) designs domain-aware classification features with high discriminative potential by summarizing regularities of symbol co-location in the MIMO constellation. To this end, we summarize the fractal geometry of observed samples to extract discriminative features for supervised MIMO modrec. We evaluate SYMMeTRy in a realistic simulation and in a small-scale MIMO testbed. We demonstrate that it maintains high and consistent performance across various noise regimes, channel fading conditions and with increasing MIMO transmitter complexity. Our efforts highlight SYMMeTRy’s high potential to enable efficient and practical MIMO modrec.