4 citations · 4 across the 13 of their papers we have counts for
13 papers
QAOA-Based Pilot Assignment for Cell-Free Massive MIMO Systems
Xiaoyu Ma, Fang Fang, Xianbin Wang
Pilot contamination is a major challenge in cell-free massive multiple-input multiple-output (MIMO) systems, where the limited number of orthogonal pilots makes pilot reuse unavoid…
EQE-QAOA: An Equivalence-Preserving Qubit Efficient Framework for Combinatorial Optimization
Xiaoyu Ma, Fang Fang, Ximing Xie +2
The limited number of qubits is a major bottleneck in Quantum Approximate Optimization Algorithm (QAOA) for large-scale combinatorial optimization in the Noisy Intermediate-Scale Q…
Secure Semantic Communications via AI Defenses: Fundamentals, Solutions, and Future Directions
Lan Zhang, Chengsi Liang, Zeming Zhuang +4
Semantic communication (SemCom) redefines wireless communication from reproducing symbols to transmitting task-relevant semantics. However, this AI-native architecture also introdu…
Straggler-Resilient Federated Learning over A Hybrid Conventional and Pinching Antenna Network
Bibo Wu, Fang Fang, Ming Zeng +1
Leveraging pinching antennas in wireless network enabled federated learning (FL) can effectively mitigate the common "straggler" issue in FL by dynamically establishing strong line…
Energy-Efficient Design for Downlink Pinching-Antenna Systems with QoS Guarantee
Ming Zeng, Ji Wang, Gui Zhou +2
Pinching antennas have recently garnered significant attention due to their ability to dynamically reconfigure wireless propagation environments. Despite notable advancements in th…
A Low-Complexity Placement Design of Pinching-Antenna Systems
Ximing Xie, Fang Fang, Zhiguo Ding +1
Pinching-antenna systems have recently been proposed as a new candidate for flexible-antenna systems, not only inheriting the reconfiguration capability but also offering a unique…
Dynamic Authentication and Granularized Authorization with a Cross-Domain Zero Trust Architecture for Federated Learning in Large-Scale IoT Networks
Xiaoyu Ma, Fang Fang, Xianbin Wang
With the increasing number of connected devices and complex networks involved, current domain-specific security techniques become inadequate for diverse large-scale Internet of Thi…
Optimizing Value of Learning in Task-Oriented Federated Meta-Learning Systems
Bibo Wu, Fang Fang, Xianbin Wang
Federated Learning (FL) has gained significant attention in recent years due to its distributed nature and privacy preserving benefits. However, a key limitation of conventional FL…
Collaborative Knowledge Sharing-empowered Effective Semantic Rate Maximization for Two-tier Semantic-Bit Communication Networks
Hong Chen, Fang Fang, Xianbin Wang
Effective task-oriented semantic communications relies on perfect knowledge alignment between transmitters and receivers for accurate recovery of task-related semantic information,…
Knowledge Sharing-enabled Semantic Rate Maximization for Multi-cell Task-oriented Hybrid Semantic-Bit Communication Networks
Hong Chen, Fang Fang, Xianbin Wang
In task-oriented semantic communications, the transmitters are designed to deliver task-related semantic information rather than every signal bit to receivers, which alleviates the…
Power-Efficient Optimization for Coexisting Semantic and Bit-Based Users in NOMA Networks
Ximing Xie, Fang Fang, Lan Zhang +1
Semantic communications, which focus on transmitting the semantic meaning of data, have been proposed as a novel paradigm for achieving efficient and relevant communication. Meanwh…
Improving Channel Resilience for Task-Oriented Semantic Communications: A Unified Information Bottleneck Approach
Shuai Lyu, Yao Sun, Linke Guo +4
Task-oriented semantic communications (TSC) enhance radio resource efficiency by transmitting task-relevant semantic information. However, current research often overlooks the inhe…
Semantic Extraction Model Selection for IoT Devices in Edge-assisted Semantic Communications
Hong Chen, Fang Fang, Xianbin Wang
Semantic communications offer the potential to alleviate communication loads by exchanging meaningful information. However, semantic extraction (SE) is computationally intensive, p…