Imperial College London
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ProfessorEricKerrigan

Faculty of Engineering, Department of Electrical and Electronic Engineering

Professor of Control and Optimization
 
 
 
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Contact

 

+44 (0)20 7594 6343e.kerrigan Website

 
 
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Assistant

 

Mrs Raluca Reynolds +44 (0)20 7594 6281

 
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Location

 

1114Electrical EngineeringSouth Kensington Campus

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Summary

 

Publications

Citation

BibTex format

@inproceedings{Faqir:2018:10.1016/j.ifacol.2018.11.013,
author = {Faqir, O and Nie, Y and Kerrigan, E and Gunduz, D},
doi = {10.1016/j.ifacol.2018.11.013},
pages = {197--202},
publisher = {Elsevier},
title = {Energy-efficient communication in mobile aerial relay-assisted networks using predictive control},
url = {http://dx.doi.org/10.1016/j.ifacol.2018.11.013},
year = {2018}
}
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RIS format (EndNote, RefMan)

TY  - CPAPER
AB  - Energy-efficient communication in wireless networks of mobile autonomous agents mandates joint optimization of both transmission and propulsion energy. In Faqir et al. (2017) we developed communication-theoretic data transmission and Newtonian flight mechanics models to formulate a nonlinear optimal control problem. Here we extend the previous work by generalizing the communication model to include UAV-appropriate slow fading channels and specifically investigate the potential from joint optimization of mobility and communication over a multiple access channel. Numerical results exemplify the potential energy savings available to all nodes through this joint optimization. Finally, using the slow fading channel problem formulation, we generate a chance-constrained nonlinear model predictive control scheme for control of a terrestrial network served by a single UAV relay. Closed-loop simulations are performed subject to uncertainties in both transmission and mobility models.
AU  - Faqir,O
AU  - Nie,Y
AU  - Kerrigan,E
AU  - Gunduz,D
DO  - 10.1016/j.ifacol.2018.11.013
EP  - 202
PB  - Elsevier
PY  - 2018///
SN  - 2405-8963
SP  - 197
TI  - Energy-efficient communication in mobile aerial relay-assisted networks using predictive control
UR  - http://dx.doi.org/10.1016/j.ifacol.2018.11.013
UR  - http://hdl.handle.net/10044/1/62109
ER  -
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