Search Results for author:
Found 6 papers, 0 papers with code
Study on Downlink CSI compression: Are Neural Networks the Only Solution?
The higher DL data rates are achieved by effective implementation of spatial multiplexing and beamforming which is subject to availability of DL channel state information (CSI) at the base station.
Physical Layer Design for Ambient IoT
One way to serve such applications is through backscatter devices, which communicate using energy harvested from ambient sources such as radio waves transmitted by a reader.
A Machine Learning based Hybrid Receiver for 5G NR PRACH
Random Access is a critical procedure using which a User Equipment (UE) identifies itself to a Base Station (BS).
On the Application of Deep Learning for Precise Indoor Positioning in 6G
Accurate localization in indoor environments is a challenge due to the Non Line of Sight (NLoS) nature of the signaling.
Enhancements for 5G NR PRACH Reception: An AI/ML Approach
The UE identifies itself by embedding a Preamble Index (RAPID) in the phase rotation of a known base sequence, which it transmits on the Physical Random Access Channel (PRACH).
Machine Learning Decoder for 5G NR PUCCH Format 0
5G cellular systems depend on the timely exchange of feedback control information between the user equipment and the base station.
