NDLI: Analysis of Heuristic Graph Partitioning Methods for the Assignment of Packet Control Units in GERAN

Content Provider	Springer Nature Link
Author	Toril, Matías Molina Fernández, Iñigo Wille, Volker Walshaw, Chris
Copyright Year	2010
Abstract	Over the last few years, graph partitioning has been recognized as a suitable technique for optimizing cellular network structure. For example, in a recent paper, the authors proposed a classical graph partitioning algorithm to optimize the assignment of cells to Packet Control Units (PCUs) in GSM-EDGE Radio Access Network. Based on this approach, the quality of packet data services in a live environment was increased by reducing the number of cell re-selections between different PCUs. To learn more about the potential of graph partitioning in cellular networks, in this paper, a more sophisticated, yet computationally efficient, partitioning algorithm is proposed for the same problem. The new method combines multi-level refinement and adaptive multi-start techniques with algorithms to ensure the connectivity between cells under the same PCU. Performance assessment is based on an extensive set of graphs constructed with data taken from a live network. During the tests, the new method is compared with classical graph partitioning approaches. Results show that the proposed method outperforms classical approaches in terms of solution quality at the expense of a slight increase in computing time, while providing solutions that are easier to check by the network operator.
Starting Page	611
Ending Page	633
Page Count	23
File Format	PDF
ISSN	09296212
Journal	Wireless Personal Communications
Volume Number	60
Issue Number	4
e-ISSN	1572834X
Language	English
Publisher	Springer US
Publisher Date	2010-03-26
Publisher Place	Boston
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	Graph partitioning Mobile Network Optimization Packet control unit Signal, Image and Speech Processing Computer Communication Networks Communications Engineering, Networks
Content Type	Text
Resource Type	Article
Subject	Electrical and Electronic Engineering Computer Science Applications

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