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

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 beyond fifth-generation (B5G) and sixth-generation (6G) era. The power of such resource allocation cannot be fully studied unless bidirectional data computation is properly managed. A novel intelligent reflecting surface (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.