ERMVP: Communication-Efficient and Collaboration-Robust Multi-Vehicle Perception in Challenging Environments

J Zhang, K Yang, Y Wang, H Wang… - Proceedings of the …, 2024 - openaccess.thecvf.com
Collaborative perception enhances perception performance by enabling autonomous
vehicles to exchange complementary information. Despite its potential to revolutionize the …

6G: Technology Evolution in Future Wireless Networks

M Shafi, RK Jha, S Jain - IEEE Access, 2024 - ieeexplore.ieee.org
The Sixth Generation (6G) Wireless Communication Network (WCN) is the successive
provision to ameliorate the gain with ultra-low latency, and e xtremely high energy efficiency …

Joint Cooperative Clustering and Power Control for Energy-Efficient Cell-Free XL-MIMO with Multi-Agent Reinforcement Learning

Z Liu, J Zhang, Z Li, DWK Ng, B Ai - arXiv preprint arXiv:2406.05481, 2024 - arxiv.org
In this paper, we investigate the amalgamation of cell-free (CF) and extremely large-scale
multiple-input multiple-output (XL-MIMO) technologies, referred to as a CF XL-MIMO, as a …

Intelligible Protocol Learning for Resource Allocation in 6G O-RAN Slicing

F Rezazadeh, H Chergui, S Siddiqui… - arXiv preprint arXiv …, 2023 - arxiv.org
An adaptive standardized protocol is essential for addressing inter-slice resource contention
and conflict in network slicing. Traditional protocol standardization is a cumbersome task …

Graph Neural Network Meets Multi-Agent Reinforcement Learning: Fundamentals, Applications, and Future Directions

Z Liu, J Zhang, E Shi, Z Liu, D Niyato, B Ai - arXiv preprint arXiv …, 2024 - arxiv.org
Multi-agent reinforcement learning (MARL) has become a fundamental component of next-
generation wireless communication systems. Theoretically, although MARL has the …

[引用][C] 강화학습기반다중에이전트간시맨틱통신작업환경

김진혁, 서세진, 박지훈, 김성륜 - 한국통신학회학술대회논문집, 2024 - dbpia.co.kr
요 약본 논문은 고성능 저지연 차세대 통신을 위한 시맨틱 통신 구조의 작업 환경을 제안한다.
다양한 무선 네트워크시나리오에서 저지연, 고성능을 보장하며 공통 작업을 수행하기 위해서는 …