Economic aspects of configuring cellular networks

Gavish, Bezalel; Sridhar, S.

doi:10.1007/bf01196263

Cited by 47 publications

(22 citation statements)

References 8 publications

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“…As further investigation, one can study the integration of this pricing scheme in the global design process of integrated networks [31] especially from the management point of view. For example, one can consider various thresholds on the income to recover costs and allow future extension of the network.…”

Section: Resultsmentioning

confidence: 99%

Jitter Characterization in Admission Control and Pricing Issues in Integrated Multiservice Networks

Houeto¹,

Pierre²

2007

J. of Computer Science

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This paper analyses the pricing framework of multiservice networks and proposes an improved pricing scheme based on the effective bandwidth concept for taking into account quality of service parameters. Based on the deficiencies noted in the classical effective bandwidth scheme (intolerance to user uncertainty and no guarantee on jitter), we propose an improved charging function which gives more flexibility to the user and we introduce an additional constraint to take into account an eventual guarantee on the jitter or delay variation. We also extended the effective bandwidth pricing scheme to the case with guaranteed jitter, in order to take into account and better deal with the various QoS parameters to be considered in 3G networks. Our proposed charging function improves the classical effective bandwidth scheme, while remaining simple in that it requires that the network only monitors the average rate and duration of each connection. It is also fairer than the classical effective bandwidth scheme as it is more flexible related to user uncertainty and the incentive to an efficient use of network resource is preserved. The constraint on the guaranteed jitter was also tested and proved to be viable.

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Section: Resultsmentioning

confidence: 99%

Jitter Characterization in Admission Control and Pricing Issues in Integrated Multiservice Networks

Houeto¹,

Pierre²

2007

J. of Computer Science

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“…Dropping probability is not included in the presented model, as it would require a more detailed model of the demand than is used here. Cost minimization has been used as an objective by some authors ( [6], [7]), but it has not been combined with system performance objectives. This paper describes an integrated approach, including both the engineering aspects of the problem as well as its economical aspects.…”

Section: Cellular System Planningmentioning

confidence: 99%

Optimization of Transmitting Powers and Locations of Base Stations in Cellular Radio Communication Systems

Hieta

Melachrinoudis

1999

Operations Research Proceedings 1998

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Summary: An optimization model for determining optimal or near-optimal locations and transmitting powers for a fixed number of base stations in a cellular communication system is presented. Traffic demand is assumed to have a stationary non-uniform distribution and is modeled using a demand grid. Demand is allocated to the base station receiving the strongest signal. Physical restrictions to the location of base stations, such as rivers, landmark buildings and parks are excluded as infeasible areas. Three objectives are considered: (a) maximization of covered traffic demand defined in terms of signal strength and co-channel interference, (b) minimization of blocking probability and (c) minimization of total cost. These are subsequently combined in a non-linear and non-smooth goal programming objective function which is optimized using the Neider-Mead down-hill simplex algorithm. The model is implemented using Matlab and illustrated in a fictitious microcellular system for the Boston downtown area.

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“…The overlap between cells is negligible relative to the cell size. 6. Subscriptions charges are not included in cash flow analysis 7.…”

Section: Assumptionsmentioning

confidence: 99%

“…Detailed estimates of costs of network deployment are available [5], but little work has been published that estimates the revenues generated by rural network deployment. Optimizing costs is an important budgetary element, yet estimating revenues is similarly important to assess the validity of an investment in new territory [6]. A number of papers admit that at the edges of the networks, different deployment conditions apply, potentially supporting a duopolic or even monopolistic model of investment.…”

Section: Introductionmentioning

confidence: 99%