Spectrum Auction Games for Multimedia Streaming Over Cognitive Radio Networks
Spectrum Auction Games for Multimedia Streaming Over Cognitive Radio Networks
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DOI：
10.1109/tcomm.2010.08.090528
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发表时间：
2010-08
影响因子：
8.3
通讯作者：
Yan Chen;Yongle Wu;Beibei Wang;K. Liu
中科院分区：
文献类型：
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作者：
Yan Chen;Yongle Wu;Beibei Wang;K. Liu
认知无线电技术已经成为有效利用频谱的一种很有前途的方法。虽然最近在认知无线电数据通信领域已经提出了许多工作，但在认知无线电网络上的内容感知多媒体应用方面的工作还很少。在本文中，我们研究了认知无线电网络中的多媒体流问题，其中有一个主用户和N个辅助用户。多媒体数据独特的可扩展性和延迟敏感特性以及由此产生的对用户观看多媒体内容体验的影响被明确地包含在效用函数中，由于该效用函数，主用户和次用户可以在不同质量级别之间无缝切换以实现最大效用。然后，我们制定了频谱分配问题作为一个拍卖游戏，并提出了三个分布式拍卖的频谱分配方案，这是频谱分配使用单对象按出价支付上升时钟拍卖（ACA-S），频谱分配使用传统的上升时钟拍卖（ACA-T），频谱分配使用交替上升时钟拍卖（ACA-A）。我们证明了这三个算法收敛在有限数量的时钟。我们还证明了ACA-S和ACA-A是防作弊的，而ACA-T不是。此外，我们还证明了ACA-T和ACA-A能够最大化社会福利，而ACA-S则不一定。因此，ACA-A是一个很好的解决方案，多媒体认知无线电网络，因为它可以实现最大的社会福利，在一个欺骗的方式。最后，仿真结果表明所提出的算法的有效性。
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-sensitive 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.