Effective assessment of mobile communication networks performance with clustering and neural modeling

Izabella Lokshina, Michael R. Bartolacci

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Citation (Scopus)

Abstract

In this paper, we present the core network model of universal mobile telecommunication system 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 system is analyzed. Scheduling of the ATM cell transmission in each time division multiple access frame for the uplink is based on a priority scheme. Blocking probability and throughput parameters for bandwidth sharing policy are considered, and partial overlap link is implemented. The clustering procedure for the mobile communication networks performance assessment is developed where the blocking probability and throughput measurements are introduced with two-dimensional Markov reward model enhanced with vector quantification and neural modeling. The link occupancy probability distribution is optimized using neural network that was trained on the base of Kohonen rules. Simulation and numerical results are shown.

Original languageEnglish (US)
Title of host publication7th Annual Wireless Telecommunications Symposium, WTS 2008
Pages9-16
Number of pages8
DOIs
StatePublished - Sep 12 2008
Event7th Annual Wireless Telecommunications Symposium, WTS 2008 - Ponoma, CA, United States
Duration: Apr 24 2008Apr 26 2008

Other

Other7th Annual Wireless Telecommunications Symposium, WTS 2008
CountryUnited States
CityPonoma, CA
Period4/24/084/26/08

Fingerprint

Blocking probability
Automatic teller machines
Network performance
Telecommunication networks
Throughput
Bandwidth
communication
Mobile telecommunication systems
Time division multiple access
Probability distributions
Telecommunication links
performance
Computer systems
performance assessment
Scheduling
Neural networks
quantification
neural network
telecommunication
scheduling

All Science Journal Classification (ASJC) codes

  • Computer Networks and Communications
  • Electrical and Electronic Engineering
  • Communication

Cite this

Lokshina, Izabella ; Bartolacci, Michael R. / Effective assessment of mobile communication networks performance with clustering and neural modeling. 7th Annual Wireless Telecommunications Symposium, WTS 2008. 2008. pp. 9-16
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Lokshina, I & Bartolacci, MR 2008, Effective assessment of mobile communication networks performance with clustering and neural modeling. in 7th Annual Wireless Telecommunications Symposium, WTS 2008., 4547537, pp. 9-16, 7th Annual Wireless Telecommunications Symposium, WTS 2008, Ponoma, CA, United States, 4/24/08. https://doi.org/10.1109/WTS.2008.4547537

Effective assessment of mobile communication networks performance with clustering and neural modeling. / Lokshina, Izabella; Bartolacci, Michael R.

7th Annual Wireless Telecommunications Symposium, WTS 2008. 2008. p. 9-16 4547537.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

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