NDLI: Post-deployment tuning of UMTS cellular networks through dual-homing of RNCs

Content Provider	IEEE Xplore Digital Library
Author	Sadhukhan, S.K. Mandal, S. Biswas, S.R. Bhaumik, P. Saha, D.
Copyright Year	2009
Description	Author affiliation: Wipro Technologies, Kolkata, India (Mandal, S.) \|\| Indian Institute of Management (IIM) Calcutta, India (Sadhukhan, S.K.; Saha, D.) \|\| CSE Dept, Jadavpur Univ, Kolkata, India (Bhaumik, P.) \|\| IBM Global, Kolkata, India (Biswas, S.R.)
Abstract	In conventional UMTS cellular networks, during deployment usually a set of NodeBs is assigned to one Radio Network Controller (RNC), and a set of RNCs to one Serving GPRS Support Node (SGSN) for data services, as well as to one Mobile Switching Centre (MSC) for voice services. Operators thus far have considered single-homing of RNCs to MSCs/SGSNs (i.e., many-to-one mapping) with an objective to reduce the total cost over a fixed period of time. However, a single-homing network does not remain cost-effective any more when subscribers later on begin to show specific inter-MSC/SGSN mobility patterns (say, diurnality of office goers) over time. This necessitates post-deployment topological extension of the network in terms of dual-homing of RNCs, in which some specific RNCs are connected to two MSCs/SGSNs via direct links resulting in a more complex many-to-two mapping structure in parts of the network. The partial dual-homing attempts to increase link cost minimally and reduce handoff cost maximally, thereby significantly reducing the total cost in a post-deployment optimal extension. In this paper, we formulate the scenario as a combinatorial optimization problem and solve the NP-Complete problem using two meta-heuristic techniques, namely Simulated Annealing (SA) and Tabu search (TS). We then compare these techniques with a novel optimal heuristic search method that we propose typically to solve the problem. The comparative results reveal that, though all of them perform equally well for small networks, for larger networks, the search-based method is more efficient than meta-heuristic techniques in finding optimal solutions quickly.
Starting Page	1
Ending Page	10
File Size	6478059
Page Count	10
File Format	PDF
ISBN	9781424429127
DOI	10.1109/COMSNETS.2009.4808896
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2009-01-05
Publisher Place	India
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Ground penetrating radar Simulated Annealing 3G mobile communication Telecommunication traffic Tabu Search Heuristic search Cellular network Optimization Radio spectrum management UMTS Dual-homing Technology management Land mobile radio cellular systems Simulated annealing Cost function Radio network Network planning Radio control
Content Type	Text
Resource Type	Article

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