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LIAO Yangzhe, LIU Lin, SONG Yuanyan, et al., “Joint Communication-Caching-Computing Resource Allocation for Bidirectional Data Computation in IRS-Assisted Hybrid UAV-Terrestrial Network,” Chinese Journal of Electronics, in press, doi: 10.23919/cje.2023.00.089, 2023.
Citation: LIAO Yangzhe, LIU Lin, SONG Yuanyan, et al., “Joint Communication-Caching-Computing Resource Allocation for Bidirectional Data Computation in IRS-Assisted Hybrid UAV-Terrestrial Network,” Chinese Journal of Electronics, in press, doi: 10.23919/cje.2023.00.089, 2023.

Joint Communication-Caching-Computing Resource Allocation for Bidirectional Data Computation in IRS-Assisted Hybrid UAV-Terrestrial Network

doi: 10.23919/cje.2023.00.089
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  • Author Bio:

    Yangzhe LIAO received his BS degree in Measurement and Control Technology from Northeastern University, China in 2013 and Ph.D. degree from the University of Warwick, UK, in 2017. Dr. Liao is an associate professor at the School of Information Engineering, Wuhan University of Technology. His research interests include mobile edge computing and mobile computing. (Email: yangzhe.liao@whut.edu.cn)

    Lin LIU is currently pursuing master’s degree in information and communication Engineering with the School of Information Engineering, Wuhan University of Technology, China. Her research interests mainly focus on wireless resource allocation and network optimization. (Email: wutliulin@whut.edu.cn)

    Yuanyan SONG is currently pursuing the master’s degree in Electronic Information with the School of Information Engineering, Wuhan University of Technology, China. His research interests include mobile edge computing and resource allocation in wireless communications. (Email: 288405@whut.edu.cn)

    Ning XU (corresponding author) received his Ph.D. degree in electronic science and technology from the University of Electronic Science and Technology of China, Chengdu, in 2003 and was a postdoctoral fellow with Tsinghua University, Beijing, from 2003 to 2005. Prof. Xu is a professor at the School of Information Engineering, Wuhan University of Technology, China. His research interests include computer-aided design of VLSI circuits and systems, big data analysis, and artificial intelligence. (Email: xuning@whut.edu.cn)

  • Received Date: 2023-03-23
  • Accepted Date: 2023-06-16
  • Available Online: 2023-07-18
  • Joint communication-caching-computing resource allocation in wireless inland waterway communications enables resource-constrained unmanned surface vehicles (USVs) to provision computation-intensive and latency-sensitive tasks forward B5G and 6G era. However, the power of such resource allocation cannot be fully studied unless bidirectional data computation is properly managed. In this paper, a novel IRS-assisted hybrid UAV-terrestrial network architecture is proposed with bidirectional tasks. The sum of uplink and downlink bandwidth minimization problem is formulated by jointly considering link quality, task execution mode selection, UAVs trajectory and task execution latency constraints. A heuristic algorithm is proposed to solve the formulated challenging problem. We divide the original challenging problem into two subproblems, i.e., the joint optimization problem of USVs offloading decision, caching decision and task execution mode selection, and the joint optimization problem of UAVs trajectory and IRS phase shift-vector design. The Karush–Kuhn–Tucker conditions are utilized to solve the first subproblem and the enhanced differential evolution algorithm is proposed to solve the latter one. The results show that the proposed solution can significantly decrease bandwidth consumption in comparison with the selected advanced algorithms. The results also prove that the sum of bandwidth can be remarkably decreased by implementing a higher number of IRS elements.
  • 1For simplification purposes, since each UAV is integrated with IRS, IRS $ l $ refers to IRS integrated by UAV $ l $.
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