1 research outputs found
Massive MIMO Adaptive Modulation and Coding Using Online Deep Learning Algorithm
The paper describes an online deep learning algorithm for the adaptive
modulation and coding in massive MIMO. The algorithm is based on a fully
connected neural network, which is initially trained on the output of the
traditional algorithm and then is incrementally retrained by the service
feedback of its output. We show the advantage of our solution over the
state-of-the-art Q-Learning approach. We provide system-level simulation
results to support this conclusion in various scenarios with different channel
characteristics and different user speeds. Compared with traditional OLLA our
algorithm shows 10\% to 20\% improvement of user throughput in the full buffer
case of continuous traffic. This is a very valuable result that allows us to
significantly improve the quality of wireless MIMO communications.Comment: The paper has been submitted to the IEEE WCL journal and has 6 pages,
8 figures, and 1 tabl