According to my knowledge, the channel estimation is to analyze the channel realization based on the pilot signal, and the channel prediction is to obtain it based on past channel realizations.
Therefore, the channel prediction can be utilized when the pilot signal is contaminated. In other words, the channel prediction is only deserved in the situation when the pilot signals are crashed so that the channel estimation doesn’t work.
Did I understand right? Thank you for your valuable responses in advance.
I would describe it somewhat differently. In my vocabulary, channel estimation refers to the general concept of utilizing received signals to estimate the channel response. The estimation could be based on pilots, pilots+data or only data (the latter two are known as semi-blind and blind estimation).
Since the channel is changing over time, we need to estimate the channel repeatedly in a wireless system. Normally, we are only trying to estimate the current channel response, but one could also try to estimate future channel responses. This is what we call channel prediction. To succeed, you need an accurate model of the time variations. A Kalman filter is one method that can be used to predict future channels.
Emil has explained the difference very well. In short, channel estimation is about estimating the channel using channel state information reference-symbols (CSI-RS), whereas channel predicting is predicting the estimated channel for T future time instance. As you are focusing on channel prediction, some of the articles can be of great help. In the literature, channel prediction is mainly handled by Kalman Filter and ML/DL. Please see a few papers below.
1. ML: https://ieeexplore.ieee.org/document/9691478
2. KF: https://ieeexplore.ieee.org/document/4224424
3. DL: Conference Paper Real-Time Massive MIMO Channel Prediction: A Combination of ...
It is a very pertinent question in wireless communication scenario particularly when we have to consider communication in fading environment. The equation for the received multipath signal consists of a number of impulse of trains at random time offsets.
Under such condition, the prediction is rather difficult since the number of the scatterers, their positions etc. change randomly. One will find it impossible to predict the resultant signal at the receiver based on some previous model.
In such testing condition, estimation based on current state of the channel is more scientific. Proper estimation will help to filter out the additional noise from the resultant signal.
- Badges
- Science topic