3 citations · 3 across the 8 of their papers we have counts for
8 papers
ESN-DAGMM: A Lightweight Framework for Unsupervised Time-Series Data Monitoring in 5G O-RAN Networks
Andrew J Chen, Raymond Zhao, Lingjia Liu
Open Radio Access Network (O-RAN) is an important 5G network architecture enabling flexible communication with adaptive strategies for different verticals. However, testing for O-R…
Learning Low-Dimensional Representation for O-RAN Testing via Transformer-ESN
Jiongyu Dai, Raymond Zhao, Farhad Rezazadeh +3
Open Radio Access Network (O-RAN) architectures enhance flexibility for 6G and NextG networks. However, it also brings significant challenges in O-RAN testing with evaluating abund…
Towards xAI: Configuring RNN Weights using Domain Knowledge for MIMO Receive Processing
Shashank Jere, Lizhong Zheng, Karim Said +1
Deep learning is making a profound impact in the physical layer of wireless communications. Despite exhibiting outstanding empirical performance in tasks such as MIMO receive proce…
Wireless Mobile Distributed-MIMO for 6G
Kumar Sai Bondada, Daniel J. Jakubisin, Karim Said +2
The paper proposes a new architecture for Distributed MIMO (D-MIMO) in which the base station (BS) jointly transmits with wireless mobile nodes to serve users (UEs) within a cell f…
Neural Network-based Two-Dimensional Filtering for OTFS Symbol Detection
Jiarui Xu, Karim Said, Lizhong Zheng +1
Orthogonal time frequency space (OTFS) is a promising modulation scheme for wireless communication in high-mobility scenarios. Recently, a reservoir computing (RC) based approach h…
Learning at the Speed of Wireless: Online Real-Time Learning for AI-Enabled MIMO in NextG
Jiarui Xu, Shashank Jere, Yifei Song +3
Integration of artificial intelligence (AI) and machine learning (ML) into the air interface has been envisioned as a key technology for next-generation (NextG) cellular networks.…
2D-RC: Two-Dimensional Neural Network Approach for OTFS Symbol Detection
Jiarui Xu, Karim Said, Lizhong Zheng +1
Orthogonal time frequency space (OTFS) is a promising modulation scheme for wireless communication in high-mobility scenarios. Recently, a reservoir computing (RC) based approach h…
Towards Explainable Machine Learning: The Effectiveness of Reservoir Computing in Wireless Receive Processing
Shashank Jere, Karim Said, Lizhong Zheng +1
Deep learning has seen a rapid adoption in a variety of wireless communications applications, including at the physical layer. While it has delivered impressive performance in task…