Publications (33)
Decentralized Federated Learning via SGD over Wireless D2D Networks
Hong Xing, Osvaldo Simeone, Suzhi Bi
Federated Learning (FL), an emerging paradigm for fast intelligent acquisition at the network edge, enables joint training of a machine learning model over distributed data sets an…
Sparsity-Aware Event-Driven Impulse Radio Transceivers for Reliable Neuromorphic Inference
Zhengzhong Guan, Jiaying Li, Kanghua Li +2
The growing number of Internet-of-Things (IoT) based artificial intelligence (AI) applications deployed at resource-constrained network edge call for ultra-reliable and low-latency…
Pre-Training and Personalized Fine-Tuning via Over-the-Air Federated Meta-Learning: Convergence-Generalization Trade-Offs
Haifeng Wen, Hong Xing, Osvaldo Simeone
For modern artificial intelligence (AI) applications such as large language models (LLMs), the training paradigm has recently shifted to pre-training followed by fine-tuning. Furth…
Optimal Resource Allocation for Wireless Powered Mobile Edge Computing with Dynamic Task Arrivals
Feng Wang, Hong Xing, Jie Xu
This paper considers a wireless powered multiuser mobile edge computing (MEC) system, where a multi-antenna access point (AP) employs the radio-frequency (RF) signal based wireless…
PRF: Parallel Resonate and Fire Neuron for Long Sequence Learning in Spiking Neural Networks
Yulong Huang, Zunchang Liu, Changchun Feng +6
Recently, there is growing demand for effective and efficient long sequence modeling, with State Space Models (SSMs) proving to be effective for long sequence tasks. To further red…
Real-Time Resource Allocation for Wireless Powered Multiuser Mobile Edge Computing With Energy and Task Causality
Feng Wang, Hong Xing, Jie Xu
This paper considers a wireless powered multiuser mobile edge computing (MEC) system, in which a multi-antenna hybrid access point (AP) wirelessly charges multiple users, and each…
Generative Artificial Intelligence (GAI) for Mobile Communications: A Diffusion Model Perspective
Xiaoxia Xu, Xidong Mu, Yuanwei Liu +3
This article targets at unlocking the potentials of a class of prominent generative artificial intelligence (GAI) method, namely diffusion model (DM), for mobile communications. Fi…
Joint Task Assignment and Wireless Resource Allocation for Cooperative Mobile-Edge Computing
Hong Xing, Liang Liu, Jie Xu +1
This paper studies a multi-user cooperative mobile-edge computing (MEC) system, in which a local mobile user can offload intensive computation tasks to multiple nearby edge devices…
Differential Privacy as a Perk: Federated Learning over Multiple-Access Fading Channels with a Multi-Antenna Base Station
Hao Liang, Haifeng Wen, Kaishun Wu +1
Federated Learning (FL) is a distributed learning paradigm that preserves privacy by eliminating the need to exchange raw data during training. In its prototypical edge instantiati…
Optimal Throughput Fairness Trade-offs for Downlink Non-Orthogonal Multiple Access over Fading Channels
Hong Xing, Yuanwei Liu, Arumugam Nallanathan +2
Recently, non-orthogonal multiple access (NOMA) has attracted considerable interest as one of the 5G-enabling techniques. However, users with better channel conditions in downlink…
Energy-Efficient Mobile-Edge Computation Offloading for Applications with Shared Data
Xiangyu He, Hong Xing, Yue Chen +1
Mobile-edge computation offloading (MECO) has been recognized as a promising solution to alleviate the burden of resource-limited Internet of Thing (IoT) devices by offloading comp…
Multiple Antenna Assisted Non-Orthogonal Multiple Access
Yuanwei Liu, Hong Xing, Cunhua Pan +3
Non-orthogonal multiple access (NOMA) is potentially capable of circumventing the limitations of the classic orthogonal multiple access schemes, hence it has recently received sign…
Accelerating Mobile Edge Generation (MEG) by Constrained Learning
Xiaoxia Xu, Yuanwei Liu, Xidong Mu +2
A novel accelerated mobile edge generation (MEG) framework is proposed for generating high-resolution images on mobile devices. Exploiting a large-scale latent diffusion model (LDM…
Optimizing DF Cognitive Radio Networks with Full-Duplex-Enabled Energy Access Points
Hong Xing, Xin Kang, Kai-Kit Wong +1
With the recent advances in radio frequency (RF) energy harvesting (EH) technologies, wireless powered cooperative cognitive radio network (CCRN) has drawn an upsurge of interest f…
Federated Learning over Wireless Device-to-Device Networks: Algorithms and Convergence Analysis
Hong Xing, Osvaldo Simeone, Suzhi Bi
The proliferation of Internet-of-Things (IoT) devices and cloud-computing applications over siloed data centers is motivating renewed interest in the collaborative training of a sh…
Physical Layer Security Jamming: Theoretical Limits and Practical Designs in Wireless Networks
Kanapathippillai Cumanan, Hong Xing, Peng Xu +5
Physical layer security has been recently recognized as a promising new design paradigm to provide security in wireless networks. In addition to the existing conventional cryptogra…
Wireless Powered Cooperative Jamming for Secrecy Multi-AF Relaying Networks
Hong Xing, Kai-Kit Wong, Arumugam Nallanathan +1
This paper studies secrecy transmission with the aid of a group of wireless energy harvesting (WEH)-enabled amplify-and-forward (AF) relays performing cooperative jamming (CJ) and…
An Improved Privacy and Utility Analysis of Differentially Private SGD with Bounded Domain and Smooth Losses
Hao Liang, Wanrong Zhang, Xinlei He +2
Differentially Private Stochastic Gradient Descent (DPSGD) is widely used to protect sensitive data during the training of machine learning models, but its privacy guarantee often…
To Harvest and Jam: A Paradigm of Self-Sustaining Friendly Jammers for Secure AF Relaying
Hong Xing, Kai-Kit Wong, Zheng Chu +1
This paper studies the use of multi-antenna harvest-and-jam (HJ) helpers in a multi-antenna amplify-and-forward (AF) relay wiretap channel assuming that the direct link between the…
Joint Resource Allocation and Cache Placement for Location-Aware Multi-User Mobile Edge Computing
Jiechen Chen, Hong Xing, Xiaohui Lin +2
With the growing demand for latency-critical and computation-intensive Internet of Things (IoT) services, the IoT-oriented network architecture, mobile edge computing (MEC), has em…
Secrecy Wireless Information and Power Transfer in Fading Wiretap Channel
Hong Xing, Liang Liu, Rui Zhang
Simultaneous wireless information and power transfer (SWIPT) has recently drawn significant interests for its dual use of radio signals to provide wireless data and energy access a…
Energy-Efficient Proactive Caching for Fog Computing with Correlated Task Arrivals
Hong Xing, Jingjing Cui, Yansha Deng +1
With the proliferation of latency-critical applications, fog-radio network (FRAN) has been envisioned as a paradigm shift enabling distributed deployment of cloud-clone facilities…
Efficient Federated Conformal Prediction with Group-Conditional Guarantee
Haifeng Wen, Osvaldo Simeone, Hong Xing
Deploying trustworthy AI systems requires principled uncertainty quantification. Conformal prediction (CP) is a widely used framework for constructing prediction sets with distribu…
Task-Oriented Integrated Sensing, Computation and Communication for Wireless Edge AI
Hong Xing, Guangxu Zhu, Dongzhu Liu +3
With the advent of emerging IoT applications such as autonomous driving, digital-twin and metaverse etc. featuring massive data sensing, analyzing and inference as well critical la…
NCAirFL: CSI-Free Over-the-Air Federated Learning Based on Non-Coherent Detection
Haifeng Wen, Nicolò Michelusi, Osvaldo Simeone +1
Over-the-air federated learning (FL), i.e., AirFL, leverages computing primitively over multiple access channels. A long-standing challenge in AirFL is to achieve coherent signal a…
Joint Task Assignment and Resource Allocation for D2D-Enabled Mobile-Edge Computing
Hong Xing, Liang Liu, Jie Xu +1
With the proliferation of computation-extensive and latency-critical applications in the 5G and beyond networks, mobile-edge computing (MEC) or fog computing, which provides cloud-…
Unsupervised Learning for AoD Estimation in MISO Downlink LoS Transmissions
Jiaying Li, Yuanwei Liu, Hong Xing
With the emergence of simultaneous localization and communication (SLAC), it becomes more and more attractive to perform angle of departure (AoD) estimation at the receiving Intern…
Collaborative Computation Offloading in Wireless Powered Mobile-Edge Computing Systems
Binqi He, Suzhi Bi, Hong Xing +1
This paper studies a novel user cooperation model in a wireless powered mobile edge computing system where two wireless users harvest wireless power transferred by one energy node…
AirFL-Mem: Improving Communication-Learning Trade-Off by Long-Term Memory
Haifeng Wen, Hong Xing, Osvaldo Simeone
Addressing the communication bottleneck inherent in federated learning (FL), over-the-air FL (AirFL) has emerged as a promising solution, which is, however, hampered by deep fading…
Distributed Conformal Prediction via Message Passing
Haifeng Wen, Hong Xing, Osvaldo Simeone
Post-hoc calibration of pre-trained models is critical for ensuring reliable inference, especially in safety-critical domains such as healthcare. Conformal Prediction (CP) offers a…
Joint Task Offloading and Cache Placement for Energy-Efficient Mobile Edge Computing Systems
Jingxuan Liang, Hong Xing, Feng Wang +1
This letter investigates a cache-enabled multiuser mobile edge computing (MEC) system with dynamic task arrivals, taking into account the impact of proactive cache placement on the…
User Localization and Channel Estimation for Pinching-Antenna Systems (PASS)
Xiaoxia Xu, Xidong Mu, Yuanwei Liu +2
This letter proposes a novel user localization and channel estimation framework for pinching-antenna systems (PASS), where pinching antennas are grouped into subarrays on each wave…
Convergence Analysis of Over-the-Air FL with Compression and Power Control via Clipping
Haifeng Wen, Hong Xing, Osvaldo Simeone
One of the key challenges towards the deployment of over-the-air federated learning (AirFL) is the design of mechanisms that can comply with the power and bandwidth constraints of…