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20232026
most citedGenerative AI Agents with Large Language Model for Satellite Networks via a Mixture of Experts Transmission

219 citations · 546 across the 100 of their papers we have counts for

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12 papers · 1 filter

eess.SP2026

Evolving Intelligent Complex Systems via Intellicise Networks: Architecture, Technologies, and Pathways

Ping Zhang, Rui Meng, Xiaodong Xu +23

Future engineering infrastructures are evolving into large-scale, open, heterogeneous, and wirelessly interconnected complex systems. These systems present significant challenges i…

eess.SP2026

Rotatable Antenna Enabled Multi-Cell Mixed Near-Field and Far-Field Communications

Yunpu Zhang, Changsheng You, Ruichen Zhang +4

Prior studies on mixed near-field and far-field communications have focused exclusively on single-cell scenarios, where both near-field and far-field users are served by the same b…

eess.SP2026

Towards Semantic-based Agent Communication Networks: Vision, Technologies, and Challenges

Ping Zhang, Rui Meng, Xiaodong Xu +24

The International Telecommunication Union (ITU) identifies "Artificial Intelligence (AI) and Communication" as one of six key usage scenarios for 6G. Agentic AI, characterized by i…

eess.SP2026

Rethinking Secure Semantic Communications in the Age of Generative and Agentic AI: Threats and Opportunities

Shunpu Tang, Yuanyuan Jia, Zijiu Yang +6

Semantic communication (SemCom) improves communication efficiency by transmitting task-relevant information instead of raw bits and is expected to be a key technology for 6G networ…

eess.SP2025

Agentic Graph Neural Networks for Wireless Communications and Networking Towards Edge General Intelligence: A Survey

Yang Lu, Shengli Zhang, Chang Liu +6

The rapid advancement of communication technologies has driven the evolution of communication networks towards both high-dimensional resource utilization and multifunctional integr…

eess.SP2025

Temporal Spectrum Cartography in Low-Altitude Economy Networks: A Generative AI Framework with Multi-Agent Learning

Changyuan Zhao, Ruichen Zhang, Jiacheng Wang +6

This paper introduces a two-stage generative AI (GenAI) framework tailored for temporal spectrum cartography in low-altitude economy networks (LAENets). LAENets, characterized by d…

eess.SP2025

Image Steganography For Securing Intellicise Wireless Networks: "Invisible Encryption" Against Eavesdroppers

Rui Meng, Song Gao, Haixiao Gao +6

As one of the most promising technologies for intellicise (intelligent and consice) wireless networks, Semantic Communication (SemCom) significantly improves communication efficien…

eess.SP2025

Movable Cell-Free Massive MIMO For High-Speed Train Communications: A PPO-Based Antenna Position Optimization

Jie Dai, Yuchen Liu, Jiakang Zheng +3

In recent years, high-speed trains (HSTs) communications have developed rapidly to enhance the stability of train operations and improve passenger connectivity experiences. However…

eess.SP2025

SWIPTNet: A Unified Deep Learning Framework for SWIPT based on GNN and Transfer Learning

Hong Han, Yang Lu, Zihan Song +5

This paper investigates the deep learning based approaches for simultaneous wireless information and power transfer (SWIPT). The quality-of-service (QoS) constrained sum-rate maxim…

eess.SP2025

Generative AI-enabled Wireless Communications for Robust Low-Altitude Economy Networking

Changyuan Zhao, Jiacheng Wang, Ruichen Zhang +5

Low-Altitude Economy Networks (LAENets) have emerged as significant enablers of social activities, offering low-altitude services such as the transportation of packages, groceries,…

eess.SP2024

Maximum-Likelihood Estimation Based on Diffusion Model For Wireless Communications

Changyuan Zhao, Jiacheng Wang, Ruichen Zhang +3

Generative Artificial Intelligence (GenAI) models, with their powerful feature learning capabilities, have been applied in many fields. In mobile wireless communications, GenAI can…

eess.SP2024

Graph Neural Networks for Wireless Networks: Graph Representation, Architecture and Evaluation

Yang Lu, Yuhang Li, Ruichen Zhang +3

Graph neural networks (GNNs) have been regarded as the basic model to facilitate deep learning (DL) to revolutionize resource allocation in wireless networks. GNN-based models are…