Search Results for author: Xuelin Cao

Found 8 papers, 1 papers with code

A Multi-Head Ensemble Multi-Task Learning Approach for Dynamical Computation Offloading

1 code implementation2 Sep 2023 Ruihuai Liang, Bo Yang, Zhiwen Yu, Xuelin Cao, Derrick Wing Kwan Ng, Chau Yuen

To improve the MEC performance, it is required to design an optimal offloading strategy that includes offloading decision (i. e., whether offloading or not) and computational resource allocation of MEC.

Edge-computing Multi-Task Learning

Reconfigurable Intelligent Computational Surfaces: When Wave Propagation Control Meets Computing

no code implementations9 Aug 2022 Bo Yang, Xuelin Cao, Jindan Xu, Chongwen Huang, George C. Alexandropoulos, Linglong Dai, M'erouane Debbah, H. Vincent Poor, Chau Yuen

The envisioned sixth-generation (6G) of wireless networks will involve an intelligent integration of communications and computing, thereby meeting the urgent demands of diverse applications.

Spectrum Learning-Aided Reconfigurable Intelligent Surfaces for 'Green' 6G Networks

no code implementations3 Sep 2021 Bo Yang, Xuelin Cao, Chongwen Huang, Yong Liang Guan, Chau Yuen, Marco Di Renzo, Dusit Niyato, Merouane Debbah, Lajos Hanzo

In the sixth-generation (6G) era, emerging large-scale computing based applications (for example processing enormous amounts of images in real-time in autonomous driving) tend to lead to excessive energy consumption for the end users, whose devices are usually energy-constrained.

Autonomous Driving

A Joint Energy and Latency Framework for Transfer Learning over 5G Industrial Edge Networks

no code implementations19 Apr 2021 Bo Yang, Omobayode Fagbohungbe, Xuelin Cao, Chau Yuen, Lijun Qian, Dusit Niyato, Yan Zhang

In this paper, we propose a transfer learning (TL)-enabled edge-CNN framework for 5G industrial edge networks with privacy-preserving characteristic.

Privacy Preserving Transfer Learning

Intelligent Spectrum Learning for Wireless Networks with Reconfigurable Intelligent Surfaces

no code implementations2 Mar 2021 Bo Yang, Xuelin Cao, Chongwen Huang, Chau Yuen, Lijun Qian, Marco Di Renzo

Reconfigurable intelligent surface (RIS) has become a promising technology for enhancing the reliability of wireless communications, which is capable of reflecting the desired signals through appropriate phase shifts.

Offloading Optimization in Edge Computing for Deep Learning Enabled Target Tracking by Internet-of-UAVs

no code implementations18 Aug 2020 Bo Yang, Xuelin Cao, Chau Yuen, Lijun Qian

This motivates us to consider offloading this type of deep learning (DL) tasks to a mobile edge computing (MEC) server due to limited computational resource and energy budget of the UAV, and further improve the inference accuracy.

Edge-computing

Computation Offloading in Multi-Access Edge Computing Networks: A Multi-Task Learning Approach

no code implementations29 Jun 2020 Bo Yang, Xuelin Cao, Joshua Bassey, Xiangfang Li, Timothy Kroecker, Lijun Qian

Multi-access edge computing (MEC) has already shown the potential in enabling mobile devices to bear the computation-intensive applications by offloading some tasks to a nearby access point (AP) integrated with a MEC server (MES).

Edge-computing Multi-Task Learning

Lessons Learned from Accident of Autonomous Vehicle Testing: An Edge Learning-aided Offloading Framework

no code implementations27 Jun 2020 Bo Yang, Xuelin Cao, Xiangfang Li, Chau Yuen, Lijun Qian

This letter proposes an edge learning-based offloading framework for autonomous driving, where the deep learning tasks can be offloaded to the edge server to improve the inference accuracy while meeting the latency constraint.

Autonomous Driving

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