99 citations · 664 across the 27 of their papers we have counts for
28 papers
Direct Satellite-to-Device Communications: From Cooperative Task Offloading to Non-Cooperative Access Monitoring
Sai Huang, Wanli Ni, Ke Lv +5
Direct satellite-to-device (DS2D) communication is emerging as a transformative paradigm for extending ubiquitous connectivity and edge computing capabilities to remote and underse…
Token Communication in the Era of Large Models: An Information Bottleneck-Based Approach
Hao Wei, Wanli Ni, Wen Wang +3
This letter proposes UniToCom, a unified token communication paradigm that treats tokens as the fundamental units for both processing and wireless transmission. Specifically, to en…
Improving Convergence for Semi-Federated Learning: An Energy-Efficient Approach by Manipulating Over-the-Air Distortion
Jingheng Zheng, Hui Tian, Wanli Ni +2
In this paper, we propose a hybrid learning framework that combines federated and split learning, termed semi-federated learning (SemiFL), in which over-the-air computation is util…
Federated Intelligence: When Large AI Models Meet Federated Fine-Tuning and Collaborative Reasoning at the Network Edge
Wanli Ni, Haofeng Sun, Huiqing Ao +1
Large artificial intelligence (AI) models exhibit remarkable capabilities in various application scenarios, but deploying them at the network edge poses significant challenges due…
Reconfigurable Intelligent Surface for Internet of Robotic Things
Wanli Ni, Ruyu Luo, Xinran Zhang +3
With the rapid development of artificial intelligence, robotics, and Internet of Things, multi-robot systems are progressively acquiring human-like environmental perception and und…
Energy-Efficient Robust Beamforming for Multi-Functional RIS-Aided Wireless Communication under Imperfect CSI
Ailing Zheng, Wanli Ni, Wen Wang +2
The robust beamforming design in multi-functional reconfigurable intelligent surface (MF-RIS) assisted wireless networks is investigated in this work, where the MF-RIS supports sig…
OFDM-Based Digital Semantic Communication with Importance Awareness
Chuanhong Liu, Caili Guo, Yang Yang +2
Semantic communication (SemCom) has received considerable attention for its ability to reduce data transmission size while maintaining task performance. However, existing works mai…
Multi-Functional Reconfigurable Intelligent Surface: System Modeling and Performance Optimization
Wen Wang, Wanli Ni, Hui Tian +2
In this paper, we propose and study a multi-functional reconfigurable intelligent surface (MF-RIS) architecture. In contrast to conventional single-functional RIS (SF-RIS) that onl…
Semi-Federated Learning: Convergence Analysis and Optimization of A Hybrid Learning Framework
Jingheng Zheng, Wanli Ni, Hui Tian +3
Under the organization of the base station (BS), wireless federated learning (FL) enables collaborative model training among multiple devices. However, the BS is merely responsible…
Convergence Analysis and Latency Minimization for Semi-Federated Learning in Massive IoT Networks
Jianyang Ren, Wanli Ni, Hui Tian +1
As the number of sensors becomes massive in Internet of Things (IoT) networks, the amount of data is humongous. To process data in real-time while protecting user privacy, federate…
Robust Transceiver Design for Covert Integrated Sensing and Communications With Imperfect CSI
Yuchen Zhang, Wanli Ni, Jianquan Wang +4
We propose a robust transceiver design for a covert integrated sensing and communications (ISAC) system with imperfect channel state information (CSI). Considering both bounded and…
Semi-Federated Learning for Collaborative Intelligence in Massive IoT Networks
Wanli Ni, Jingheng Zheng, Hui Tian
Implementing existing federated learning in massive Internet of Things (IoT) networks faces critical challenges such as imbalanced and statistically heterogeneous data and device d…
Enhancing NOMA Networks via Reconfigurable Multi-Functional Surface
Ailing Zheng, Wanli Ni, Wen Wang +1
By flexibly manipulating the radio propagation environment, reconfigurable intelligent surface (RIS) is a promising technique for future wireless communications. However, the singl…
Balancing Accuracy and Integrity for Reconfigurable Intelligent Surface-aided Over-the-Air Federated Learning
Jingheng Zheng, Hui Tian, Wanli Ni +2
Over-the-air federated learning (AirFL) allows devices to train a learning model in parallel and synchronize their local models using over-the-air computation. The integrity of Air…
Federated Deep Reinforcement Learning for RIS-Assisted Indoor Multi-Robot Communication Systems
Ruyu Luo, Wanli Ni, Hui Tian +1
Indoor multi-robot communications face two key challenges: one is the severe signal strength degradation caused by blockages (e.g., walls) and the other is the dynamic environment…
Safeguarding NOMA Networks via Reconfigurable Dual-Functional Surface under Imperfect CSI
Wen Wang, Wanli Ni, Hui Tian +3
This paper investigates the use of the reconfigurable dual-functional surface to guarantee the full-space secure transmission in non-orthogonal multiple access (NOMA) networks. In…
Towards Communication-Learning Trade-off for Federated Learning at the Network Edge
Jianyang Ren, Wanli Ni, Hui Tian
In this letter, we study a wireless federated learning (FL) system where network pruning is applied to local users with limited resources. Although pruning is beneficial to reduce…
Online Offloading Scheduling for NOMA-Aided MEC Under Partial Device Knowledge
Meihui Hua, Hui Tian, Xinchen Lyu +2
By exploiting the superiority of non-orthogonal multiple access (NOMA), NOMA-aided mobile edge computing (MEC) can provide scalable and low-latency computing services for the Inter…
STAR-RIS Integrated Non-Orthogonal Multiple Access and Over-the-Air Federated Learning: Framework, Analysis, and Optimization
Wanli Ni, Yuanwei Liu, Yonina C. Eldar +2
This paper integrates non-orthogonal multiple access (NOMA) and over-the-air federated learning (AirFL) into a unified framework using one simultaneous transmitting and reflecting…
Research on Resource Allocation for Efficient Federated Learning
Jianyang Ren, Wanli Ni, Gaofeng Nie +1
As a promising solution to achieve efficient learning among isolated data owners and solve data privacy issues, federated learning is receiving wide attention. Using the edge serve…
QoS-Constrained Federated Learning Empowered by Intelligent Reflecting Surface
Jingheng Zheng, Wanli Ni, Hui Tian
This paper investigates the model aggregation process in an over-the-air federated learning (AirFL) system, where an intelligent reflecting surface (IRS) is deployed to assist the…
Integrating Over-the-Air Federated Learning and Non-Orthogonal Multiple Access: What Role can RIS Play?
Wanli Ni, Yuanwei Liu, Zhaohui Yang +2
With the aim of integrating over-the-air federated learning (AirFL) and non-orthogonal multiple access (NOMA) into an on-demand universal framework, this paper proposes a novel rec…
Deep Reinforcement Learning for Energy-Efficient Beamforming Design in Cell-Free Networks
Weilai Li, Wanli Ni, Hui Tian +1
Cell-free network is considered as a promising architecture for satisfying more demands of future wireless networks, where distributed access points coordinate with an edge cloud p…
Intelligent Reflecting Surface Aided Multi-Cell NOMA Networks
Wanli Ni, Xiao Liu, Yuanwei Liu +2
This paper proposes a novel framework of resource allocation in intelligent reflecting surface (IRS) aided multi-cell non-orthogonal multiple access (NOMA) networks, where a sum-ra…