Beyond Empirical Models: Pattern Formation Driven Placement of UAV Base Stations

Jiaxun Lu, Shuo Wan, Xuhong Chen, Zhengchuan Chena, Pingyi Fan, Khaled Letaief

Research output: Contribution to journalArticle

5 Citations (Scopus)

Abstract

This work considers the placement of unmanned aerial vehicle base stations (UAV-BSs) with criterion of minimum UAV-recall-frequency (UAV-RF), indicating the energy efficiency of mobile UAVs networks. Several different power consumptions, including signal transmit power, on-board circuit power and the power for UAVs mobility, and the ground user density are taken into account. Instead of conventional empirical stochastic models, this paper utilizes a pattern formation system to track the instable and non-ergodic time-varying nature of user density. We show that for a single time-slot, the optimal placement is achieved when the transmit power of UAV-BSs equals their onboard circuit power. Then, for multiple time-slot duration, we prove that the optimal placement updating problem is an integer nonlinear programming coupled with an inherent integer linear programming. Since the original problem is NP-hard and can not be solved with conventional recursive methods, we propose a sequential-Markov-greedy-decision strategy to achieve near minimal UAV-RF in polynomial time. Further, we prove that the increment of UAV-RF caused by inaccurate predicted user density is proportional to the generalization error of learned patterns. Here, in regions with large area, high-rise buildings or low user density, large sample sets are required for effective pattern formation.

Original languageEnglish
JournalIEEE Transactions on Wireless Communications
DOIs
Publication statusAccepted/In press - 10 Mar 2018
Externally publishedYes

Fingerprint

Empirical Model
Unmanned aerial vehicles (UAV)
Pattern Formation
Base stations
Placement
Nonlinear Integer Programming
Generalization Error
Recursive Method
Integer Linear Programming
Mobile Networks
Inaccurate
Energy Efficiency
Increment
Power Consumption
Updating
Stochastic Model
Time-varying
Polynomial time
NP-complete problem
Directly proportional

Keywords

  • Aerial base-station
  • air-to-ground communication
  • Pareto-optimality
  • pattern formation
  • sample size
  • time-varying user density
  • UAV deployment

ASJC Scopus subject areas

  • Computer Science Applications
  • Electrical and Electronic Engineering
  • Applied Mathematics

Cite this

Beyond Empirical Models : Pattern Formation Driven Placement of UAV Base Stations. / Lu, Jiaxun; Wan, Shuo; Chen, Xuhong; Chena, Zhengchuan; Fan, Pingyi; Letaief, Khaled.

In: IEEE Transactions on Wireless Communications, 10.03.2018.

Research output: Contribution to journalArticle

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