Spectrum auction games for multimedia streaming over cognitive radio networks

  • Authors:

  • Yan Chen;Yongle Wu;Beibei Wang;K. J. Ray Liu

  • Affiliations:

  • Department of Electrical and Computer Engineering, University of Maryland, College Park, MD;Department of Electrical and Computer Engineering, University of Maryland, College Park, MD;Department of Electrical and Computer Engineering, University of Maryland, College Park, MD;Department of Electrical and Computer Engineering, University of Maryland, College Park, MD

  • Venue:
  • IEEE Transactions on Communications
  • Year:
  • 2010

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Abstract

Cognitive radio technologies have become a promising approach to efficiently utilize the spectrum. Although many works have been proposed recently in the area of cognitive radio for data communications, little effort has been made in content-aware multimedia applications over cognitive radio networks. In this paper, we study the multimedia streaming problem over cognitive radio networks, where there is one primary user and N secondary users. The uniquely scalable and delay-sensltive characteristics of multimedia data and the resulting impact on users' viewing experiences of multimedia content are explicitly involved in the utility functions, due to which the primary user and the secondary users can seamlessly switch among different quality levels to achieve the largest utilities. Then, we formulate the spectrum allocation problem as an auction game and propose three distributively auction-based spectrum allocation schemes, which are spectrum allocation using Single object pay-as-bid Ascending Clock Auction (ACA-S), spectrum allocation using Traditional Ascending Clock Auction (ACA-T), and spectrum allocation using Alternative Ascending Clock Auction (ACA-A). We prove that all three algorithms converge in a finite number of clocks. We also prove that ACA-S and ACA-A are cheat-proof while ACA-T is not. Moreover, we show that ACA-T and ACA-A can maximize the social welfare while ACA-S may not. Therefore, ACA-A is a good solution to multimedia cognitive radio networks since it can achieve maximal social welfare in a cheat-proof way. Finally, simulation results are presented to demonstrate the efficiency of the proposed algorithms.