Uppsala universitet

Adaptive Massive MIMO for fast moving connected vehicles: It will work with Predictor Antennas!

Dinh-Thuy Phan-Huy , Orange Labs, Paris,
Stefan Wesemann , Nokia Bell Labs, Stuttgart,
Joachim Björsell , Uppsala University, and
Mikael Sternad , Uppsala University.

22th International Workshop on Smart Antennas (WSA2018) , Bochum, Germany, March 2018.

Paper In Pdf

Presentation slides

Predicting the channel between a massive multiple input multiple output antenna and a car is a challenge, due to the short-term fading. It becomes essentially impossible by conventional extrapolation from past estimates if the car has moved by half a wavelength or more in space at the time when the channel estimate will be needed. This problem would prevent us from using the best fifth generation adaptive antenna downlink precoding schemes for very fast moving connected vehicles.

A potential solution is to add another vehicle antenna, a “predictor antenna”, which senses the channel in advance. In this paper, based on drive tests and channel measurements from a 64- element antenna to a car, we for the first time show that this concept works for massive MIMO downlinks.

Thanks to the use of a predictor antenna, the complex OFDM downlink channels can be predicted with an accuracy that enables maximum ratio transmit beamforming with close to ideal beamforming gain for non-line-of-sight channels.

Zero forcing transmission to two users results in a signal-to-interference ratio of 20 dB to 30 dB when predicting non-line-of-sight channels up to three wavelengths ahead in space.

These first experiment shows that the predictor antenna concept is a potential solution to make fifth generation adaptive antennas work for very fast moving connected vehicles.

Related publications:

Paper at IEEE PIMRC 2017 on the on-line algorithm and performance of prediction antennas based on measured channels.

Paper at IEEE ICC 2017 that provides the statistical estimate of the prediction accuracy.

Paper at IEEE WCNC 2012, Original proposal for using "Predictor antennas" for long-range prediction of fast fading for moving relays.

Conference paper at EUCAP 2014 presenting compensation of antenna coupling.

IEEE Intelligent Transportation Systems Magazine 2015: Making 5G adaptive antennas work for very fast moving vehicles.

Paper at Globecom 2016 5G Workshop on the gain by predictor antennas in terms of spectral efficiency and power efficiency when serving connected vehicles by 5G Massive MIMO antennas.

Channel Estimation and Prediction for 5G Applications.
PhD Thesis by Rikke Apelfröjd, Uppsala University 2018.

Channel Estimation and Prediction for MIMO OFDM Systems.
PhD Thesis by Danel Aronsson, Uppsala University 2011.

Prediction of Mobile Radio Channels.
PhD Thesis by Torbjörn Ekman, Uppsala University 2002.

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