Decentralized utility maximization in heterogeneous multicell scenarios with interference limited and orthogonal air interfaces

  • Authors:
  • Ingmar Blau;Gerhard Wunder;Ingo Karla;Rolf Sigle

  • Affiliations:
  • Fraunhofer German-Sino Lab for Mobile Communications, Fraunhofer-Institute for Telecommunications, Heinrich-Hertz-Institut, Berlin, Germany;Fraunhofer German-Sino Lab for Mobile Communications, Fraunhofer-Institute for Telecommunications, Heinrich-Hertz-Institut, Berlin, Germany;Bell Labs, Alcatel-Lucent Deutschland AG, Stuttgart, Germany;Bell Labs, Alcatel-Lucent Deutschland AG, Stuttgart, Germany

  • Venue:
  • EURASIP Journal on Wireless Communications and Networking - Special issue on fairness in radio resource management for wireless networks
  • Year:
  • 2009

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Abstract

Overlapping coverage of multiple radio access technologies provides new multiple degrees of freedom for tuning the fairness-throughput tradeoff in heterogeneous communication systems through proper resource allocation. This paper treats the problem of resource allocation in terms of optimum air interface and cell selection in cellular multi-air interface scenarios. We find a close to optimum allocation for a given set of voice users with minimum QoS requirements and a set of best-effort users which guarantees service for the voice users and maximizes the sum utility of the best-effort users. Our model applies to arbitrary heterogeneous scenarios where the air interfaces belong to the class of interference limited systems like UMTS or to a class with orthogonal resource assignment such as TDMA-based GSM or WLAN. We present a convex formulation of the problem and by using structural properties thereof deduce two algorithms for static and dynamic scenarios, respectively. Both procedures rely on simple information exchange protocols and can be operated in a completely decentralized way. The performance of the dynamic algorithm is then evaluated for a heterogeneous UMTS/GSM scenario showing high-performance gains in comparison to standard load-balancing solutions.