no code implementations • 4 Jan 2024 • Chuanhong Liu, Caili Guo, Yang Yang, Wanli Ni, Tony Q. S. Quek
Based on semantic importance, we formulate a sub-carrier and bit allocation problem to maximize communication performance.
no code implementations • 4 Oct 2023 • Jingheng Zheng, Wanli Ni, Hui Tian, Deniz Gunduz, Tony Q. S. Quek, Zhu Han
To tackle this issue, we propose a semi-federated learning (SemiFL) paradigm to leverage the computing capabilities of both the BS and devices for a hybrid implementation of centralized learning (CL) and FL.
no code implementations • 4 Oct 2023 • Wen Wang, Wanli Ni, Hui Tian, Naofal Al-Dhahir
To realize a self-sustainable communication system, we investigate the use of MF-RIS in improving the sum-rate of multi-user wireless networks.
no code implementations • 4 Oct 2023 • Wen Wang, Wanli Ni, Hui Tian, Yonina C. Eldar, Rui Zhang
In this paper, we propose and study a multi-functional reconfigurable intelligent surface (MF-RIS) architecture.
1 code implementation • 9 Mar 2023 • 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 diversity.
no code implementations • 17 Jul 2022 • Jingheng Zheng, Hui Tian, Wanli Ni, Wei Ni, Ping Zhang
Under perfect channel state information (CSI), the new framework minimizes the aggregated model's distortion and retains the local models' recoverability by optimizing the transmit beamformers of the devices, the receive beamformers of the BS, and the RIS configuration in an alternating manner.
no code implementations • 29 May 2022 • Wen Wang, Wanli Ni, Hui Tian, Zhaohui Yang, Chongwen Huang, Kai-Kit Wong
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.
no code implementations • 27 May 2022 • 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.
no code implementations • 19 Apr 2021 • Jianyang Ren, Wanli Ni, Gaofeng Nie, Hui Tian
In this framework, we minimize the weighted sum of system cost and learning cost by optimizing bandwidth, computing frequency, power allocation and subcarrier assignment.
no code implementations • 7 Dec 2020 • Wanli Ni, Xiao Liu, Yuanwei Liu, Hui Tian, Yue Chen
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-rate maximization problem is formulated.
no code implementations • 26 Oct 2020 • Wanli Ni, Yuanwei Liu, Zhaohui Yang, Hui Tian, Xuemin Shen
This paper investigates the problem of model aggregation in federated learning systems aided by multiple reconfigurable intelligent surfaces (RISs).
Information Theory Signal Processing Information Theory
no code implementations • 21 Jun 2020 • Wanli Ni, Xiao Liu, Yuanwei Liu, Hui Tian, Yue Chen
This paper proposes a novel framework of resource allocation in multi-cell intelligent reflecting surface (IRS) aided non-orthogonal multiple access (NOMA) networks, where an IRS is deployed to enhance the wireless service.