A prioritized real-time wireless call degradation framework for optimal call mix selection

  • Authors:
  • Gergely V. Záruba;Imrich Chlamtac;Sajal K. Das

  • Affiliations:
  • University of Texas at Dallas, Richardson, TX;University of Texas at Dallas, Richardson, TX;University of Texas at Arlington, Arlington, TX

  • Venue:
  • Mobile Networks and Applications - Analysis and Design of Multi-Service Wireless Networks
  • Year:
  • 2002

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Abstract

This paper describes a framework for selecting the optimal call mix to be admitted while employing a bandwidth degradation policy in a wireless cellular network. The optimal property is achieved by maximizing the revenue generated by different calls in a cell for the service provider. By degradation, we mean that: (1) some channels can be taken away from ongoing calls that are assigned multiple channels, and/or (2) newly admitted calls that require multiple channels get fewer than what they requested. To avoid removing more channels from calls than they could tolerate, we incorporate a new call attribute: the degradation tolerance, i.e., the number of channels a call can be degraded without sacrificing the acceptable level of quality. We also consider priorities over calls to influence the admission and/or degradation decision. Our analytical framework includes both static and dynamic scenarios. The dynamic case is enhanced with the ability to select the optimal call mix using incoming and departing handoffs, new calls, and call terminations in a recursive way, thus, resulting in a call admission policy. We also discuss how to accommodate non-real-time calls into our system. To evaluate the performance of the proposed scheme, a discrete event simulation tool has been developed that models our dynamic framework built on a customized simulated annealing optimization function. Simulation results demonstrate that not only does the proposed degradation framework maximize the total revenue generated by the admitted calls in the cells, but also reduce the handoff and new call blocking probabilities.