Numerology-Capable UAV-MEC for Future Generation Massive IoT Networks

Mohammad Arif Hossain, Abdullah Ridwan Hossain, Nirwan Ansari

Research output: Contribution to journalArticlepeer-review

11 Scopus citations


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.

Original languageEnglish (US)
Pages (from-to)23860-23868
Number of pages9
JournalIEEE Internet of Things Journal
Issue number23
StatePublished - Dec 1 2022

All Science Journal Classification (ASJC) codes

  • Signal Processing
  • Information Systems
  • Hardware and Architecture
  • Computer Science Applications
  • Computer Networks and Communications


  • Energy consumption
  • Internet of Things
  • mobile-edge computing (MEC)
  • numerology
  • spectral efficiency
  • unmanned aerial vehicle (UAV)


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