论文标题
FusionNet：使用Sub-6GHz通道和一些飞行员进行MMWave通信的增强的光束预测
FusionNet: Enhanced Beam Prediction for mmWave Communications Using Sub-6GHz Channel and A Few Pilots
论文作者
论文摘要
在本文中，我们提出了一种新的下行链接仪，用于使用上行链路SUB-6GHz频道信息和极少数MMWave飞行员的MMWave通信。具体而言，我们设计了一个称为FusionNet的新型双输入神经网络，用于提取和利用Sub-6GHz通道和一些MMWave飞行员的特征，以准确预测MMWave Beam。为了进一步提高波束形成性能并避免过度拟合，我们开发了两种使用通道稀疏性和数据增强的数据预处理方法。模拟结果表明，与纯粹依赖于6GHz信息的现有策略相比，提出的策略的性能卓越和鲁棒性，尤其是在低信噪比（SNR）区域。
In this paper, we propose a new downlink beamforming strategy for mmWave communications using uplink sub-6GHz channel information and a very few mmWave pilots. Specifically, we design a novel dual-input neural network, called FusionNet, to extract and exploit the features from sub-6GHz channel and a few mmWave pilots to accurately predict mmWave beam. To further improve the beamforming performance and avoid over-fitting, we develop two data pre-processing approaches utilizing channel sparsity and data augmentation. The simulation results demonstrate superior performance and robustness of the proposed strategy compared to the existing one that purely relies on the sub-6GHz information, especially in the low signal-to-noise ratio (SNR) regions.
