no code implementations • 25 May 2023 • Kang Li, Pengcheng Zhu, Yan Wang, Fu-Chun Zheng, Xiaohu You
With the proposed packet delivery mechanism, we jointly optimize bandwidth allocation and power control of uplink and downlink, antenna configuration, and subchannel assignment to minimize the average total power under the constraint of URLLC transmission requirements.
no code implementations • 11 Jul 2022 • Yuhong Liu, Changyang She, Yi Zhong, Wibowo Hardjawana, Fu-Chun Zheng, Branka Vucetic
In this paper, we aim to improve the Quality-of-Service (QoS) of Ultra-Reliability and Low-Latency Communications (URLLC) in interference-limited wireless networks.
no code implementations • 23 Jun 2022 • Yunwei Tao, Yanxiang Jiang, Fu-Chun Zheng, Pengcheng Zhu, Dusit Niyato, Xiaohu You
To utilize the computing resources of other fog access points (F-APs) and to reduce the communications overhead, we propose a quantized federated learning (FL) framework combining with Bayesian learning.
no code implementations • 23 Jun 2022 • Yanxiang Jiang, Min Zhang, Fu-Chun Zheng, Yan Chen, Mehdi Bennis, Xiaohu You
In this paper, cooperative edge caching problem is studied in fog radio access networks (F-RANs).
no code implementations • 13 Jun 2022 • Zhiheng Wang, Yanxiang Jiang, Fu-Chun Zheng, Mehdi Bennis, Xiaohu You
Based on clustered federated learning, we propose a novel mobility-aware popularity prediction policy, which integrates content popularities in terms of local users and mobile users.
no code implementations • 13 Jun 2022 • Lingling Zhang, Yanxiang Jiang, Fu-Chun Zheng, Mehdi Bennis, Xiaohu You
In this paper, by considering time-varying network environment, a dynamic computation offloading and resource allocation problem in F-RANs is formulated to minimize the task execution delay and energy consumption of MDs.
no code implementations • 27 Feb 2019 • Liuyang Lu, Yanxiang Jiang, Mehdi Bennis, Zhiguo Ding, Fu-Chun Zheng, Xiaohu You
In this paper, the distributed edge caching problem in fog radio access networks (F-RANs) is investigated.