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Publication

Minimizing Han-dover Performance Degradation due to LTE Self-Organized Load Balancing

Authors:
Dr.-Ing. Stephen Mwanje
Prof. Dr.-Ing. habil. Andreas Mitschele-Thiel
Typ:
Conferences
Status:
accepted
Date of publication
06/05/2013
Abstract:
Self-Organization (SO) has been proposed to reduce
capital and operational expenses as well as to improve cellular
network performance. Mobility Load Balancing (MLB) and
Mobility Robustness Optimization(MRO) are two of the major
proposed SO use cases. Typically, MRO sets the cell’s Handover
(HO) Hysteresis and Time to Trigger, to select the optimum point
at which a HO is initiated. Conversely, MLB can be achieved by
advancing HOs from overloaded to less loaded cells, commonly
by adjusting the Cell IndividualOffset (CIO). However, MLB
affects HO metrics specifically because advancing HOs
inadvertently increases Radio Link Failures (RLF) arising from
overly early HOs and/or the number of HOs and Ping-Pong HOs.
In this work we present a Q-Learning algorithm that learns the
best MLB action to take in different load states so as to achieve a
desired load transfer, but with the least effect on HO
performance. The learning agent minimizes the negative HO
effects by applying a penalty to MLB actions that cause high
RLFs, thereby reducing the effects on HO metrics by up to 30%.
Bibtex