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  • 2005-2009  (3)
  • 1995-1999  (5)
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  • 1
    Publication Date: 2014-02-26
    Description: We present a mathematical formulation of a \emph{frequency assignment problem} encountered in cellular phone networks: frequencies have to be assigned to stationary transceivers (carriers) such that as little interference as possible is induced while obeying several technical and legal restrictions. The optimization problem is NP-hard, and no good approximation can be guaranteed---unless P = NP. We sketch some starting and improvement heuristics, and report on their successful application for solving the frequency assignment problem under consideration. Computational results on real-world instances with up to 2877 carriers and 50 frequencies are presented.
    Keywords: ddc:000
    Language: English
    Type: reportzib , doc-type:preprint
    Format: application/postscript
    Format: application/pdf
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  • 2
    Publication Date: 2020-08-05
    Language: English
    Type: conferenceobject , doc-type:conferenceObject
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  • 3
    Publication Date: 2020-08-05
    Language: English
    Type: article , doc-type:article
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  • 4
    Publication Date: 2020-08-05
    Language: English
    Type: article , doc-type:article
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  • 5
    Publication Date: 2020-08-05
    Language: English
    Type: article , doc-type:article
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  • 6
    Publication Date: 2020-03-09
    Description: We present a graph-theoretic model for the \emph{frequency assignment problem} in Cellular Phone Networks: Obeying several technical and legal restrictions, frequencies have to be assigned to transceivers so that interference is as small as possible. This optimization problem is NP-hard. Good approximation cannot be guaranteed, unless P = NP. We describe several assignment heuristics. These heuristics are simple and not too hard to implement. We give an assessment of the heuristics' efficiency and practical usefulness. For this purpose, typical instances of frequency assignment problems with up to 4240 transceivers and 75 frequencies of a German cellular phone network operator are used. The results are satisfying from a practitioner's point of view. The best performing heuristics were integrated into a network planning system used in practice.
    Keywords: ddc:000
    Language: English
    Type: reportzib , doc-type:preprint
    Format: application/postscript
    Format: application/pdf
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  • 7
    Publication Date: 2020-03-09
    Description: Mobile telecommunication systems establish a large number of communication links with a limited number of available frequencies; reuse of the same or adjacent frequencies on neighboring links causes interference. The task to find an assignment of frequencies to channels with minimal interference is the frequency assignment problem. The frequency assignment problem is usually treated as a graph coloring problem where the number of colors is minimized, but this approach does not model interference minimization correctly. We give in this paper a new integer programming formulation of the frequency assignment problem, the orientation model, and develop a heuristic two-stage method to solve it. The algorithm iteratively solves an outer and an inner optimization problem. The outer problem decides for each pair of communication links which link gets the higher frequency and leads to an acyclic subdigraph problem with additional longest path restrictions. The inner problem to find an optimal assignment respecting an orientation leads to a min-cost flow problem.
    Keywords: ddc:000
    Language: English
    Type: reportzib , doc-type:preprint
    Format: application/postscript
    Format: application/pdf
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  • 8
    Publication Date: 2014-02-26
    Description: The performance evaluation of W-CDMA networks is intricate as cells are strongly coupled through interference. Pole equations have been developed as a simple tool to analyze cell capacity. Numerous scientific contributions have been made on their basis. In the established forms, the pole equations rely on strong assumptions such as homogeneous traffic, uniform users, and constant downlink orthogonality factor. These assumptions are not met in realistic scenarios. Hence, the pole equations are typically used during initial network dimensioning only. Actual network (fine-) planning requires a more faithful analysis of each individual cell's capacity. Complex analytical analysis or Monte-Carlo simulations are used for this purposes. In this paper, we generalize the pole equations to include inhomogeneous data. We show how the equations can be parametrized in a cell-specific way provided the transmit powers are known. This allows to carry over prior results to realistic settings. This is illustrated with an example: Based on the pole equation, we investigate the accuracy of average snapshot'' approximations for downlink transmit powers used in state-of-the-art network optimization schemes. We confirm that the analytical insights apply to practice-relevant settings on the basis of results from detailed Monte-Carlo simulation on realistic datasets.
    Keywords: ddc:000
    Language: English
    Type: reportzib , doc-type:preprint
    Format: application/pdf
    Format: application/postscript
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