Abstract
A new study on Machine Learning is now available. According to news reporting originating in Berlin, Germany, by NewsRx journalists, research stated, "In this work, we propose novel HARQ prediction schemes for Cloud RANs (C-RANs) that use feedback over a rate-limited feedback channel (2 - 6 bits) from the Remote Radio Heads (RRHs) to predict at the User Equipment (UE) the decoding outcome at the BaseBand Unit (BBU) ahead of actual decoding. In particular, we propose a Dual Autoencoding 2-Stage Gaussian Mixture Model (DA2SGMM) that is trained in an end-to-end fashion over the whole C-RAN setup." Financial support for this research came from Federal Ministry of Education and Research of Germany in the Programme of "Souvern. Digital. Vernetzt." Joint Project 6G-RIC.
NETL
NSTL
IEEE