Python codes for all the figures in the manuscript titled “Massive MIMO Channel Prediction Using Neural Networks” Massive MIMO Channel Prediction Using Recurrent Neural Networks · Issue 1 (pubpub.org)
========= WORK SUMMARY ========
Massive MIMO has been classified as one of the high potential wireless communication
technologies due to its unique abilities such as high user capacity, increased spectral density, and diversity among others. These properties are of great importance for the current 5G-IoT era and future telecommunication networks. Outdated channel state information (CSI) caused by multipath fading is a major problem facing massive MIMO systems. Outdated CSI occurs when the information obtained about the channel, i.e. the constellation size, coding rate, transmit power, precoding codeword, time
and frequency resource block, transmit antennas, and relays changes before it can be used. In this work, we employ neural network models to predict instantaneous CSI. We start by defining prediction parameters from signal transmission equations, then we design a network model for prediction, and finally, we compare the performance results.