Making 5G adaptive antennas work for very fast moving vehicles

Abstract

Wireless systems increasingly rely on the accurate knowledge at the transmitter side of the transmitter-to-receiver propagation channel, to optimize the transmission adaptively. Some candidate techniques for 5th generation networks need the channel knowledge for tens of antennas to perform adaptive beamforming from the base station towards the mobile terminal. These techniques reduce the radiated power and the energy consumption of the base station. Unfortunately, they fail to deliver the targeted quality of service to fast moving terminals such as connected vehicles. Indeed, due to the movement of the vehicle during the delay between channel estimation and data transmission, the channel estimate is outdated. In this paper, we propose three new schemes that exploit the "Predictor Antenna" concept. This recent concept is based on the observation that the position occupied by one antenna at the front of the vehicle, will later on be occupied by another antenna at the back. Estimating the channel of the "front" antenna can therefore later help beamforming towards the "back" antenna. Simulations show that our proposed schemes make adaptive beamforming work for vehicles moving at speeds up to 300 km/h