Autoencoder-based Pilot Pattern Design for CDL Channels

Abstract

In the pilot-based channel estimations, a large number of pilot signals enable an improvement in the channel estimation accuracy but force a decrease in the data transmission efficiency. Therefore, the pilot pattern design schemes on the resource grid have been researched to achieve high channel estimation accuracy with a small number of pilot signals. In the conventional scheme for pilot pattern design, the autoencoder which enables discrete feature selection is utilized to design pilot patterns for Vehicular-A channels. However, the pilot pattern for other channels is not reported, and it is not clear whether this scheme has good performance compared to uniform pilot patterns. In this paper, we derive the pilot patterns for Clustered Delay Line (CDL) channels specified in the 5th Generation Mobile Communication System (5G) standard using the autoencoder-based pilot pattern design scheme. We also derive the pilot patterns for CDL-A and CDL-D, which model respectively NLOS (Non-Line-of-Sight) and LOS (Line-of-Sight) environments, with different three speeds of User Equipment (UE). Through computer simulation, we show that the autoencoder-based pilot patterns improve the channel estimation accuracy compared to the uniform pilot pattern.