UMTS Capacity and Throughput Maximization for Different Spreading Factors

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This article discusses UMTS capacity and throughput maximization for different spreading factors.

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10 p.

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Akl, Robert G. & Nguyen, Son July 2006.

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This article is part of the collection entitled: UNT Scholarly Works and was provided by UNT College of Engineering to Digital Library, a digital repository hosted by the UNT Libraries. It has been viewed 504 times . More information about this article can be viewed below.

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This article discusses UMTS capacity and throughput maximization for different spreading factors.

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10 p.

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Abstract: An analytical model for calculating capacity in multi-cell UMTS networks is presented. Capacity is maximized for different spreading factors and for perfect and imperfect power control. The authors also design and implement a local call admission control (CAC) algorithm which allows for the simulation of network throughput for different spreading factors and various mobility scenarios. The design of the CAC algorithm uses global information ; it incorporates the call arrival rates and the user mobilities across the network and guarantees the users' quality of service as well as pre-specified blocking probabilities. On the other hand, its implementation in each cell uses local information; it only requires the number of calls currently active in that cell. The capacity and network throughput were determined for signal-to-interference threshold from 5 dB to 10 dB and spreading factor values of 256, 64, 16, and 4.

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  • Journal of Networks, 2006. Oulu: Academy Publisher, pp. 40-49

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  • Publication Title: Journal of Networks
  • Volume: 1
  • Issue: 3
  • Page Start: 40
  • Page End: 49
  • Peer Reviewed: Yes

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UNT Scholarly Works

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  • July 2006

Added to The UNT Digital Library

  • Jan. 24, 2011, 2:10 p.m.

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  • March 27, 2014, 1:33 p.m.

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Akl, Robert G. & Nguyen, Son. UMTS Capacity and Throughput Maximization for Different Spreading Factors, article, July 2006; [Oulu, Finland]. (digital.library.unt.edu/ark:/67531/metadc30833/: accessed January 20, 2018), University of North Texas Libraries, Digital Library, digital.library.unt.edu; crediting UNT College of Engineering.