High Altitude Platform Networks (HAPNETs): Design, Deployment, and Resource Management

  • Ming-Cheng Tsai

Student thesis: Master's Thesis


In this thesis, we consider maximized power allocation of non-orthogonal multiple ac- cess (NOMA) schemes since it outperforms than orthogonal multiple access (OMA) for the high altitude platform networks (HAPNETs) both in the back- haul and access links. Secondly, we propose a cluster formation (CF) algorithm and power-bandwidth resource allocation (PB-RA) for solving the resource management of HAPNETs. We adopt the particle swarm optimization (PSO) algorithm to explore the optimal de- ployment of high altitude platforms (HAPs) and unmanned aerial vehicles (UAVs) iteratively by a given swarm size. By PSO, we provide the best deployment under a given iteration number. Besides that, numerical results show that the NOMA schemes have better performance than OMA ones concerning different network control factors like the number of BSs, HAPs, and UAVs.
Date of AwardApr 2020
Original languageEnglish (US)
Awarding Institution
  • Computer, Electrical and Mathematical Sciences and Engineering
SupervisorMohamed-Slim Alouini (Supervisor)


  • High Altitude Platform
  • NOMA
  • Backhaul
  • Access
  • PSO

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