Ecole d'ingénieur et centre de recherche en Sciences du numérique

Robust optimization framework for proactive user association in UDNs: A data-driven approach

Liakopoulos, Nikolaos; Paschos, Georgios S; Spyropoulos, Thrasyvoulos

IEEE/ACM Transactions on Networking, Vol. 27, N°4, August 2019

We study the user association problem in the context of dense networks, where standard adaptive algorithms become ineffective. This paper proposes a novel data-driven technique leveraging the theory of robust optimization. The main idea is to predict future traffic fluctuations, and use the predictions to design association maps before the actual arrival of traffic. Although, the actual playout of the map is random due to prediction error, the maps are robustly designed to handle uncertainty, preventing constraint violations, and maximizing the expectation of a convex utility function, which is used to accurately balance base station loads. We propose a generalized iterative algorithm, referred to as GRMA, which is shown to converge to the optimal robust map. The optimal maps have the intriguing property that they jointly optimize the predicted load and the variance of the prediction error. We validate our robust maps in Milano-area traces, with dense coverage and find that we can reduce violations from 25% (inflicted by a baseline adaptive algorithm) down to almost zero.

Doi Bibtex

Titre:Robust optimization framework for proactive user association in UDNs: A data-driven approach
Mots Clés:WirelessRobust optimization, user association, ultra dense networks, robust optimization, data-driven optimization
Type:Journal
Langue:English
Ville:
Date:
Département:Systèmes de Communication
Eurecom ref:5984
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Bibtex: @article{EURECOM+5984, doi = {http://dx.doi.org/10.1109/TNET.2019.2930231}, year = {2019}, month = {08}, title = {{R}obust optimization framework for proactive user association in {UDN}s: {A} data-driven approach}, author = {{L}iakopoulos, {N}ikolaos and {P}aschos, {G}eorgios {S} and {S}pyropoulos, {T}hrasyvoulos}, journal = {{IEEE}/{ACM} {T}ransactions on {N}etworking, {V}ol. 27, {N}°4, {A}ugust 2019}, url = {http://www.eurecom.fr/publication/5984} }
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