Performance analysis of mobile communication networks with clustering and neural modelling

  • Authors:
  • Dimitar Radev;Izabella Lokshina

  • Affiliations:
  • Department of Communication Technique and Technologies, University of Rousse, Rousse, Bulgaria.;Division of Economics and Business, SUNY at Oneonta, Oneonta, NY, USA

  • Venue:
  • International Journal of Mobile Network Design and Innovation
  • Year:
  • 2006

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Abstract

In this paper, we present the Universal Mobile Telecommunication System (UMTS) core network model with calls that belong to one of four service classes and arrive randomly. Arriving calls are granted service based on specific service class, required maximum and minimum bandwidth and available network resources. Performance of priority-based dynamic capacity allocation, suitable for the Wireless ATM (WATM) system is analysed. Scheduling of the ATM cell transmission in each uplink Time-Division Multiple-Access (TDMA) frame is based on a priority scheme. GoS (blocking probability) and QoS (throughput) parameters for Bandwidth Sharing Policy (BSP) are considered and Partial Overlap Link (POL) is implemented. The clustering procedure for the performance analysis of the mobile communication networks and the blocking probability and throughput measurements are introduced as Markov reward models enhanced with Vector Quantification (VQ) and neural modelling. The optimal link occupancy probability distribution is determined using neural network that was trained on the base of Kohonen rules. Simulation and numerical results are shown.