The Optimal and the Greedy: Drone Association and Positioning Schemes for Internet of UAVs

Hajar El Hammouti, Doha Hamza, Basem Shihada, Mohamed Slim Alouini, Jeff S. Shamma

Research output: Contribution to journalArticlepeer-review


This work considers the deployment of unmanned aerial vehicles (UAVs) over a predefined area to serve a number of ground users. Due to the heterogeneous nature of the network, the UAVs may cause severe interference to the transmissions of each other. Hence, a judicious design of the user-UAV association and UAV locations is desired. A potential game is defined where the players are the UAVs. The potential function is the total sum rate of the users. The agents' utility in the potential game is their marginal contribution to the global welfare or their so-called wonderful life utility. A game-theoretic learning algorithm, binary log-linear learning (BLLL), is then applied to the problem. Given the potential game structure, a consequence of our utility design, the stochastically stable states using BLLL are guaranteed to be the potential maximizers. Hence, we optimally solve the joint user-UAV association and 3-D-location problem. Next, we exploit the submodular features of the sum rate function for a given configuration of UAVs to design an efficient greedy algorithm. Despite the simplicity of the greedy algorithm, it comes with a performance guarantee of $1-1/e$ of the optimal solution. To further reduce the number of iterations, we propose another heuristic greedy algorithm that provides very good results. Our simulations show that, in practice, the proposed greedy approaches achieve significant performance in a few iterations.

Original languageEnglish (US)
Article number9392003
Pages (from-to)14066-14079
Number of pages14
JournalIEEE Internet of Things Journal
Issue number18
StatePublished - Sep 15 2021


  • Binary log-linear learning (BLLL)
  • UAV-enabled networks
  • greedy algorithm
  • potential game
  • unmanned aerial vehicle (UAV) 3-D placement
  • users-UAVs association

ASJC Scopus subject areas

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


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