Authors:
Sven Tomforde
1
;
Alexander Ostrovsky
2
and
Jörg Hähner
1
Affiliations:
1
University of Augsburg, Germany
;
2
Technische Universität München, Germany
Keyword(s):
Organic Computing, Adaptivity, Intelligent System Control, Learning, Antennas, LTE.
Related
Ontology
Subjects/Areas/Topics:
Hybrid Learning Systems
;
Informatics in Control, Automation and Robotics
;
Intelligent Control Systems and Optimization
;
Machine Learning in Control Applications
;
Optimization Algorithms
Abstract:
The utilisation of cell phone networks increases continuously, especially driven by the introduction of new mobile services and smart phones. Network operators can follow two directions to deal with the problem: either install new hardware or increase the efficiency of the existing infrastructure. This paper presents a novel algorithm to improve the efficiency of current networks by allowing for a self-organised load-dependent reconfiguration of antennas. The algorithm is capable of identifying hotspot traffic, assigning this to a neighbouring cell, and learning the best strategy at runtime. This leads to a self-improving intelligent control mechanism. The simulation-based evaluation results demonstrate the potential benefit, while simultaneously keeping the hardware’s deterioration at a comparable level.