A cost model for radio access data networks. Issue 1 (12th January 2015)

• Record Type: Journal Article
• Authors: Katsigiannis, Michail; Smura, Timo
• Is Part Of: Info. Volume 17:Issue 1(2015)
• Page Start: 39
• Page End: 53
• Publication Date: 2015-01-12
• Subjects: Telecommunication -- Periodicals; Mass media -- Periodicals; Information policy -- Periodicals; Information technology -- Periodicals; 384.04105
• DOI: 10.1108/info-09-2014-0036
• Languages: English
• ISSNs: 1463-6697

Abstract

<abstract> <title> <x content-type="archive" xml:space="preserve">Abstract</x> </title> <sec> <title content-type="abstract-heading">Purpose</title> <p> – The purpose of this paper is to use basic economic theory to examine the relation between the demanded data traffic and the network costs for several network deployment scenarios and find the most preferable deployment strategy subject to specific constraints in near future (2015-2020). </p> </sec> <sec> <title content-type="abstract-heading">Design/methodology/approach</title> <p> – The paper identifies the cost structure of radio access networks and explicitly models the network costs as a function of data traffic, both in the short-run (current network) and in the long-run (future capacity expansion scenarios). In the short-run model, the operating cost of the current network is calculated, highlighting the energy cost and its dynamics. In the long-run model, assuming unchanged site infrastructure, the cost analysis provides information for decision-making on network evolution. </p> </sec> <sec> <title content-type="abstract-heading">Findings</title> <p> – The results show that the operating cost does not differ significantly from short- to long-run, and the energy cost constitutes a small but remarkable share (around 7 per cent) of total network operating cost. In addition, the paper concludes that the best strategy is not the most cost-efficient strategy but the one which meet the coverage requirements imposed by the regulator when the spectrum is allocated to operators. Finally, the speed of investments in urban regions is driven by the traffic growth, whereas in suburban and rural regions, it is driven by the regulator's intervention. </p> </sec> <sec> <title content-type="abstract-heading">Originality/value</title> <p> – The paper contributes to the improvement of cost modeling for techno-economics by using economic theory and analyzing the energy consumption. In addition, the paper investigates real cases for mobile operators, and provides useful information for decision-making in network evolution.</p> </sec> </abstract>