Towards Deep Learning-Guided Multiuser SNR and Doppler Shift Detection for Next-Generation Wireless Systems
Towards Deep Learning-Guided Multiuser SNR and Doppler Shift Detection for Next-Generation Wireless Systems
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DOI：
10.1109/vtc2022-spring54318.2022.9860990
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发表时间：
2022-06
期刊：
影响因子：
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通讯作者：
S. Kojima;Yi Feng;K. Maruta;K. Ootsu;T. Yokota;C. Ahn;V. Tarokh
中科院分区：
文献类型：
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作者：
S. Kojima;Yi Feng;K. Maruta;K. Ootsu;T. Yokota;C. Ahn;V. Tarokh
为了满足对数据流量不断增长的需求，高效的多个访问方案（例如Ofdma）被广泛用于现代通信标准中。在此类多个访问方案中，自适应调制和编码（AMC）用于优化每个用户的传输速率。但是，表征每个用户的通信环境的反馈信息，例如SNR和多普勒偏移，对于AMC来说是必不可少的。过去，通常使用参考信号估算这些信息和参数。但是，参考信号变成开销，从而导致吞吐量和处理延迟。此外，计算负担可能很大，因为有必要为每个用户单独执行通道参数估计。以前，在单用户通道上，我们通过基于频谱图的数据驱动方法提出了一种关节SNR和多普勒移位检测方法，而没有参考信号。本文将此框架扩展到多源OFDM多个访问渠道。在新提出的方法中，可以通过每个频谱图映像的深度学习引导的对象检测算法同时检测所有用户的SNR和多普勒移位。提供仿真结果以验证所提出的方法的有效性。
In order to meet the ever-growing demand for data traffic, highly efficient multiple access schemes, such as OFDMA, are widely used in modern communication standards. In such multiple access schemes, adaptive modulation and coding (AMC) are used to optimize the transmission rate of each user. However, feedback information, such as SNR and Doppler shift, characterizing the communication environment of each user is indispensable of key importance for AMC. In the past, these information and parameters were often estimated using reference signals. However, the reference signal becomes overhead, resulting in throughput degradation and processing delay. Furthermore, the computation burden can be large as it is necessary to perform channel parameter estimation individually for each user. Previously, over the single-user channel, we have proposed a joint SNR and Doppler shift detection method via a spectrogram-based data-driven method, without the reference signal. This paper extends this framework to multiuser OFDM multiple access channels. In the newly proposed method, SNR and Doppler shift for all users can be detected simultaneously via deep learning-guided object detection algorithms from each spectrogram image. Simulation results are provided to validate the effectiveness of the proposed method.