3 citations · 4 across the 7 of their papers we have counts for
4 papers · 1 filter
A Machine Learning based Hybrid Receiver for 5G NR PRACH
Rohit Singh, Anil Kumar Yerrapragada, Radha Krishna Ganti
Random Access is a critical procedure using which a User Equipment (UE) identifies itself to a Base Station (BS). Random Access starts with the UE transmitting a random preamble on…
On the Application of Deep Learning for Precise Indoor Positioning in 6G
Sai Prasanth Kotturi, Anil Kumar Yerrapragada, Sai Prasad +1
Accurate localization in indoor environments is a challenge due to the Non Line of Sight (NLoS) nature of the signaling. In this paper, we explore the use of AI/ML techniques for p…
UCINet0: A Machine Learning based Receiver for 5G NR PUCCH Format 0
Jeeva Keshav Sattianarayanin, Anil Kumar Yerrapragada, Radha Krishna Ganti
Accurate decoding of Uplink Control Information (UCI) on the Physical Uplink Control Channel (PUCCH) is essential for enabling 5G wireless links. This paper explores an AI/ML-based…
Enhancements for 5G NR PRACH Reception: An AI/ML Approach
Rohit Singh, Anil Kumar Yerrapragada, Jeeva Keshav S +1
Random Access is an important step in enabling the initial attachment of a User Equipment (UE) to a Base Station (gNB). The UE identifies itself by embedding a Preamble Index (RAPI…