Can Wireless Environment Information Decrease Pilot Overhead: A Channel Prediction Example

Channel state information (CSI) is crucial for massive multi-input multi-output (MIMO) system. As the antenna scale increases, acquiring CSI results in significantly higher system overhead. In this letter, we propose a novel channel prediction method which utilizes wireless environment information with pilot pattern optimization for channel prediction (WEI-CP). Specifically, the distribution of scatterers around the mobile station (MS) significantly affecting the CSI, which represents the wireless environment information, is acquired using multi-view images. Then, to dig out the mapping relationship between wireless environment information (WEI) and CSI, the image feature extraction module extracts environment feature map from multi-view images. Additionally, the pilot pattern optimization module acquires an optimal fixed pilot pattern to select partial CSI. Finally, using the environment feature map and partial CSI, the channel prediction module predicts the complete CSI. Simulation results show that the WEI-CP can reduce pilot overhead from 1/5 to 1/8 and improve prediction accuracy, with the normalized mean squared error reduced to 0.0113, an 83.2% improvement over channel prediction method without WEI.