D. Niyato

Age-Energy Tradeoff in UAV-Aided ISAC Networks With MEC: An SA-PPO-Based Approach

Secure Low-Altitude Maritime Communications via Intelligent Jamming

Low-altitude wireless networks (LAWNs) have emerged as a viable solution for maritime communications. In these maritime LAWNs, uncrewed aerial vehicles (UAVs) serve as practical low-altitude platforms for wireless communications due to their flexibility and ease of deployment. However, the open and clear UAV communicat...

Self-Evolving AI for Humanoids: Mechanisms, Safety, and Evaluation of Post-Deployment Self-Improvement

Humanoid robots are becoming an important part of embodied artificial intelligence, driven by advances in reinforcement learning for locomotion, world models for prediction, and vision-language-action models for general control. However, most of these systems remain static after deployment. A policy is trained offline...

HFedAR: Resource Allocation for Adaptive Retransmission-Based Hierarchical Federated Learning in Open RAN

The flexible architecture of the open radio access network (O-RAN) provides effective support for the deployment of federated learning (FL). However, existing FL schemes in wireless networks often suffer from packet errors, which lead to reduced model test accuracy and increased training delay. In this paper, we propos...

Diffusion Language Models for Mobile Edge Agentic AI: Foundations, Applications, and Challenges

Diffusion language models (DLMs) offer a non-autoregressive alternative for mobile edge agentic artificial intelligence (AI) by refining tokens through iterative denoising rather than left-to-right decoding. Compared with autoregressive Transformer-based large language models (LLMs), DLMs can update multiple uncertain...

Tutorial on Large Language Model-Enhanced Reinforcement Learning for Wireless Networks

A taxonomy to categorize the roles of LLMs into four critical functions: state perceiver, reward designer, decision-maker, and generator is proposed and reviewed to offer insights into its future development in wireless networks.

Efficient Cross-View Localization in 6G Space-Air-Ground Integrated Network

This work proposes a split-inference framework for implementing CVL, which fully leverages the distributed communication and computing resources of the 6G SAGIN architecture and discusses potential research directions for 6G SAGIN-enabled CVL.

Graph Neural Networks for Diffusion and Aggregation in Wireless Federated Learning

User devices (UDs) with non-independent and identically distributed (non-IID) data will worsen accuracy performance of the global model in federated learning (FL). Therefore, the implementation of diffusion strategies in machine learning (ML) models can enhance the effectiveness of federated learning with non-IID data....