Adaptive MIMO Detector Based on Hypernetwork: Design, Simulation, and Experimental Test
Adaptive MIMO Detector Based on Hypernetwork: Design, Simulation, and Experimental Test
复制标题
基于超网络的自适应MIMO检测器：设计、仿真和实验测试
DOI：
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发表时间：
2022
影响因子：
16.4
通讯作者：
Shi Jin
中科院分区：
文献类型：
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作者：
Jing Zhang;Chao;Shi Jin
算法展开在传统的基于模型的算法和现代的基于数据的深度学习之间提供了系统的联系，在有效平衡多输入多输出（MIMO）检测器的性能和复杂性方面取得了巨大的经验成功。然而，现有的基于展开的MIMO检测器难以适应信道和噪声条件的高度差异。在这项研究中，我们提出了一种新的基于展开的MIMO检测器框架，它可以自动确定基于展开的MIMO检测器的内部参数，以适应不断变化的条件。我们的方法的一个关键部分是开发一个超网络，可以有效地学习生成复杂的期望传播为基础的MIMO检测器的内部参数。特别地，我们设计了基于长短期记忆的超网络来保证展开算法各层的灵活性。所提出的框架还扩展到编码MIMO Turbo接收机，以适应不同的反馈信念从解码器。数值结果表明，所提出的MIMO检测器具有良好的适应能力，不同的信道环境和噪声水平。与现有的展开算法相比，该框架避免了频繁的重新训练，在未编码和编码的MIMO系统中具有接近最优的性能。一个在空中平台，以及展示所提出的接收机在实际部署的显着鲁棒性。
Algorithm unfolding, which provides a systematic connection between conventional model-based algorithms and modern data-based deep learning, has exhibited great empirical success for efficiently balancing the performance and complexity of multiple-input and multiple-output (MIMO) detectors. However, existing unfolding-based MIMO detectors have difficulties adapting to the high discrepancy in channel and noise conditions. In this study, we present a novel unfolding-based framework for MIMO detectors, which can automatically determine internal parameters of an unfolding-based MIMO detector to adapt to the varying conditions. A key part of our approach is to develop a hypernetwork that can effectively learn to generate the internal parameters in the sophisticated expectation propagation-based MIMO detector. In particular, we design long short-term memory-based hypernetwork to ensure the flexibility of the layers of the unfolded algorithm. The proposed framework is also extended to a coded MIMO turbo receiver to adapt to the different feedback beliefs from the decoder. Numerical results demonstrate that the proposed MIMO detectors have excellent adaptation capability to different channel environments and noise levels. Compared with the existing unfolded algorithm that is an optimal reference, the proposed framework avoids frequent retraining and presents the nearly optimal performance in uncoded and coded MIMO systems. An over-the-air platform is presented as well to demonstrate the significant robustness of the proposed receivers in practical deployment.