6 papers
Cross-Domain Federated Semantic Communication with Global Representation Alignment and Domain-Aware Aggregation
Loc X. Nguyen, Ji Su Yoon, Huy Q. Le +7
Semantic communication can significantly improve bandwidth utilization in wireless systems by exploiting the meaning behind raw data. However, the advancements achieved through sem…
Vision and Causal Learning Based Channel Estimation for THz Communications
Kitae Kim, Yan Kyaw Tun, Md. Shirajum Munir +3
The use of terahertz (THz) communications with massive multiple input multiple output (MIMO) systems in 6G can potentially provide high data rates and low latency communications. H…
Resource-Efficient Beam Prediction in mmWave Communications with Multimodal Realistic Simulation Framework
Yu Min Park, Yan Kyaw Tun, Eui-Nam Huh +2
Beamforming is a key technology in millimeter-wave (mmWave) communications that improves signal transmission by optimizing directionality and intensity. However, conventional chann…
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…
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…
SpaFL: Communication-Efficient Federated Learning with Sparse Models and Low computational Overhead
Minsu Kim, Walid Saad, Merouane Debbah +1
The large communication and computation overhead of federated learning (FL) is one of the main challenges facing its practical deployment over resource-constrained clients and syst…