Outdated channel state information (CSI) has a severe impact on a wide variety of wireless techniques. Making use of artificial intelligence, a multi-antenna channel predictor is proposed in this paper. It can accurately forecast the future CSIs up to tens of symbols ahead in a fast fading channel. By tuning the number of neurons in the input and output layers of neural network (NN) in terms of the number of antennas, it congenitally suits a multi-antenna system. Relying on a NN with real-valued weights, this predictor is simpler but substantially outperforms existing complex-valued NN predictors.
Multi-Antenna Fading Channel Prediction Empowered by Artificial Intelligence
2018-08-01
639361 byte
Aufsatz (Konferenz)
Elektronische Ressource
Englisch
Artificial Intelligence Empowered Models for UAV Communications
Springer Verlag | 2022
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