9 citations · 24 across the 5 of their papers we have counts for
9 papers · 1 filter
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…
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.…
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…
Universal Approximation of Linear Time-Invariant (LTI) Systems through RNNs: Power of Randomness in Reservoir Computing
Shashank Jere, Lizhong Zheng, Karim Said +1
Recurrent neural networks (RNNs) are known to be universal approximators of dynamic systems under fairly mild and general assumptions. However, RNNs usually suffer from the issues…
Bayesian Inference-assisted Machine Learning for Near Real-Time Jamming Detection and Classification in 5G New Radio (NR)
Shashank Jere, Ying Wang, Ishan Aryendu +2
The increased flexibility and density of spectrum access in 5G New Radio (NR) has made jamming detection and classification a critical research area. To detect coexisting jamming a…
Federated Dynamic Spectrum Access
Yifei Song, Hao-Hsuan Chang, Zhou Zhou +2
Due to the growing volume of data traffic produced by the surge of Internet of Things (IoT) devices, the demand for radio spectrum resources is approaching their limitation defined…