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Veröffentlichung

Distributed Cooperative Q-Learning for mobility sensitive Handover Optimization in LTE SON

Autoren:
Dr.-Ing. Stephen Mwanje
Prof. Dr.-Ing. habil. Andreas Mitschele-Thiel
Typ:
Konferenz
Status:
akzeptiert
Veröffentlichungsdatum
26.06.2014
Abstract:
Optimal settings for Handover parameters (Hys-teresis and Time-to-Trigger) depend on user velocities in the
network. The Self-Organization Networks (SON) standard defines
the Mobility Robustness Optimization (MRO) use case for the
autonomous methods of configuring the parameters in congruence
to the mobility pattern. State of the art MRO solutions have
relied on expert knowledge, rule based algorithms to search the
parameter space; yet it is unwieldy to design rules for all possible
mobility patterns in any network. In this work, we present a
Q-learning MRO solution, QMRO, which learns the required
parameter values appropriate for specific velocity conditions in
the individual cells. We compare QMRO against the best static
reference configuration (Ref) that is obtained by sweeping the
parameter space. Our results show that QMRO is able to learn
parameter settings that achieve similar performance to Ref in
a realistic network environment where users have dynamically
varying velocities
Bibtex