43 citations · 90 across the 9 of their papers we have counts for
6 papers · 1 filter
Federated Split Learning with Model Pruning and Gradient Quantization in Wireless Networks
Junhe Zhang, Wanli Ni, Dongyu Wang
As a paradigm of distributed machine learning, federated learning typically requires all edge devices to train a complete model locally. However, with the increasing scale of artif…
Federated Contrastive Learning for Personalized Semantic Communication
Yining Wang, Wanli Ni, Wenqiang Yi +3
In this letter, we design a federated contrastive learning (FedCL) framework aimed at supporting personalized semantic communication. Our FedCL enables collaborative training of lo…
From Single to Multi-Functional RIS: Architecture, Key Technologies, Challenges, and Applications
Wanli Ni, Ailing Zheng, Wen Wang +3
Although reconfigurable intelligent surfaces (RISs) have demonstrated the potential to boost network capacity and expand coverage by adjusting their electromagnetic properties, exi…
Multi-Objective Optimization-based Transmit Beamforming for Multi-Target and Multi-User MIMO-ISAC Systems
Chunwei Meng, Zhiqing Wei, Dingyou Ma +3
Integrated sensing and communication (ISAC) is an enabling technology for the sixth-generation mobile communications, which equips the wireless communication networks with sensing…
Multi-Objective Optimization-Based Waveform Design for Multi-User and Multi-Target MIMO-ISAC Systems
Peng Wang, Dongsheng Han, Yashuai Cao +2
Integrated sensing and communication (ISAC) opens up new service possibilities for sixth-generation (6G) systems, where both communication and sensing (C&S) functionalities co-exis…
Secrecy Performance Analysis of Multi-Functional RIS-Assisted NOMA Networks
Yingjie Pei, Wanli Ni, Jin Xu +3
Although reconfigurable intelligent surface (RIS) can improve the secrecy communication performance of wireless users, it still faces challenges such as limited coverage and double…