8 papers
Inductive Latent Context Persistence: Closing the Post-Handover Cold Start in 6G Radio Access Networks
Anubhab Banerjee, Daniyal Amir Awan
In modern radio access networks (RANs), rule-based handover (HO) decisions (e.g., A3/A5) depend on user equipment (UE) measurements only, so UEs at the same location can receive in…
GPU-accelerated partially linear multiuser detection for 5G and beyond URLLC systems
Matthias Mehlhose, Guillermo Marcus, Daniel Schäufele +6
In this feasibility study, we have implemented a recently proposed partially linear multiuser detection algorithm in reproducing kernel Hilbert spaces (RKHSs) on a GPU-accelerated…
Robust Cell-Load Learning with a Small Sample Set
Daniyal Amir Awan, Renato L. G. Cavalcante, Slawomir Stanczak
Learning of the cell-load in radio access networks (RANs) has to be performed within a short time period. Therefore, we propose a learning framework that is robust against uncertai…
Set-Theoretic Learning for Detection in Cell-Less C-RAN Systems
Daniyal Amir Awan, Renato L. G. Cavalcante, Zoran Utkovski +1
Cloud-radio access network (C-RAN) can enable cell-less operation by connecting distributed remote radio heads (RRHs) via fronthaul links to a powerful central unit. In conventiona…
Machine Learning-Based Adaptive Receive Filtering: Proof-of-Concept on an SDR Platform
Matthias Mehlhose, Daniyal Amir Awan, Renato L. G. Cavalcante +2
Conventional multiuser detection techniques either require a large number of antennas at the receiver for a desired performance, or they are too complex for practical implementatio…
Detection for 5G-NOMA: An Online Adaptive Machine Learning Approach
Daniyal Amir Awan, Renato L. G. Cavalcante, Masahiro Yukawa +1
Non-orthogonal multiple access (NOMA) has emerged as a promising radio access technique for enabling the performance enhancements promised by the fifth-generation (5G) networks in…