Deep learning based image-assisted millimeter wave beam prediction scheme in mobile scenarios
An image-assisted beam prediction scheme based on deep learning is proposed for the fast beam prediction problem in the downlink of millimeter-wave large-scale MIMO communication system in a high-speed mobile environment.Based on the RGB images collected from the base stations and uploaded to the MEC server,the Faster RCNN target detection model is combined with a DNN neural network to predict the high-dimensional nonlinear relationship between the user images and the millimeter-wave downlink beam vectors in the communication environment.The simulation results show that the scheme predicts the achievable rate of downlink beam vectors close to the theoretical optimum and outperforms the baseline algorithm in terms of model complexity and performance in the case of high antenna number and low signal-to-noise ratio.
万方数据
维普
