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UID:305@lincs.fr
DTSTART;TZID=Europe/Paris:20170419T140000
DTEND;TZID=Europe/Paris:20170419T150000
DTSTAMP:20170420T062446Z
URL:https://www.lincs.fr/events/load-balancing-in-heterogeneous-networks-b
 ased-ondistributed-learning-in-near-potential-games-2/
SUMMARY:Load Balancing in Heterogeneous Networks Based onDistributed
 Learning in Near-Potential Games
DESCRIPTION:We present a novel approach for distributed load balancing
 in\nheterogeneous networks that use cell range expansion (CRE) for
 user\nassociation and almost blank subframe (ABS) for
 interference\nmanagement. First\, we formulate the problem as a
 minimisation of an\nalphaÃ¢fairness objective function with load and
 outage constraints.\nDepending on alpha\, different objectives in terms of
 network\nperformance or fairness can be achieved. Next\, we model
 the\ninteractions among the base stations for load balancing as
 a\nnear-potential game\, in which the potential function is
 the\nalphaÃ¢fairness function. The optimal pure Nash equilibrium (PNE) of
 the\ngame is found by using distributed learning algorithms. We
 propose\nlog-linear and binary log-linear learning algorithms for complete
 and\npartial information settings\, respectively. We give a detailed proof
 of\nconvergence of learning algorithms for a near-potential game.
 We\nprovide sufficient conditions under which the learning
 algorithms\nconverge to the optimal PNE. By running extensive simulations\,
 we show\nthat the proposed algorithms converge within few hundreds
 of\niterations. The convergence speed in the case of partial
 information\nsetting is comparable to that of the complete information
 setting.\nFinally\, we show that outage can be controlled and a better
 load\nbalancing can be achieved by introducing ABS.Joint work with
 Pierre\nCoucheney\, and Marceau Coupechoux\, in IEEE Transactions on
 Wireless\nCommunications (Vol. 15\, No. 7\, 2016).
CATEGORIES:Seminars,Youtube
LOCATION:LINCS Seminars room\, 23\, avenue d'Italie\, Paris\, 75013\,
 France
GEO:48.828400;2.356897
X-APPLE-STRUCTURED-LOCATION;VALUE=URI;X-ADDRESS=23\, avenue d'Italie\,
 Paris\, 75013\, France;X-APPLE-RADIUS=100;X-TITLE=LINCS Seminars
 room:geo:48.828400,2.356897
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TZID:Europe/Paris
X-LIC-LOCATION:Europe/Paris
BEGIN:DAYLIGHT
DTSTART:20170326T030000
TZOFFSETFROM:+0100
TZOFFSETTO:+0200
TZNAME:CEST
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