5 papers
A Deep Incremental Framework for Multi-Service Multi-Modal Devices in NextG AI-RAN Systems
Mrityunjoy Gain, Kitae Kim, Avi Deb Raha +4
In this paper, we propose a deep incremental framework for efficient RAN management, introducing the Multi-Service-Modal UE (MSMU) system, which enables a single UE to handle eMBB…
High-Frequency First: A Two-Stage Approach for Improving Image INR
Sumit Kumar Dam, Mrityunjoy Gain, Eui-Nam Huh +1
Implicit Neural Representations (INRs) have emerged as a powerful alternative to traditional pixel-based formats by modeling images as continuous functions over spatial coordinates…
DD-JSCC: Dynamic Deep Joint Source-Channel Coding for Semantic Communications
Avi Deb Raha, Apurba Adhikary, Mrityunjoy Gain +3
Deep Joint Source-Channel Coding (Deep-JSCC) has emerged as a promising semantic communication approach for wireless image transmission by jointly optimizing source and channel cod…
FedFeat+: A Robust Federated Learning Framework Through Federated Aggregation and Differentially Private Feature-Based Classifier Retraining
Mrityunjoy Gain, Kitae Kim, Avi Deb Raha +4
In this paper, we propose the FedFeat+ framework, which distinctively separates feature extraction from classification. We develop a two-tiered model training process: following lo…
Security Risks in Vision-Based Beam Prediction: From Spatial Proxy Attacks to Feature Refinement
Avi Deb Raha, Kitae Kim, Mrityunjoy Gain +4
The rapid evolution towards the sixth-generation (6G) networks demands advanced beamforming techniques to address challenges in dynamic, high-mobility scenarios, such as vehicular…