Numerology-Capable UAV-MEC for Future Generation Massive IoT Networks
Mohammad Arif Hossain, Abdullah Ridwan Hossain, Nirwan Ansari
Abstract
This work proposes a dynamic numerology scheme assignment framework to provision mobile-edge computing (MEC) for massive Internet of Things (IoT) networks via unmanned aerial vehicles (UAVs). IoT devices (IoTDs) usually lack computational power; thus, they offload their computational tasks to MEC servers. To enhance their battery lives, an optimal assignment of a numerology scheme to each IoTD is imperative; it also enhances the system spectral efficiency. In this work, we bring MEC services closer to a massive IoT network by deploying a UAV-MEC and allocate communication resources of the sub-6-GHz band dependent on the numerology schemes to each IoTD. We formulate a multiobjective optimization problem (MOOP) with two countering objectives to maximize the uplink spectral efficiency while minimizing the IoTDs’ energy consumption. We solve a series of sequential subproblems, which are convex approximations of the MOOP and propose a novel algorithm to allocate computational resources, assign numerology schemes, and communication resources for each of the IoTDs. Our extensive simulation results validate the proposed aims herein.