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首页> 外文会议>IEEE International symposium on Personal, Indoor, and Mobile Radio Communications >A Thompson sampling approach to channel exploration-exploitation problem in multihop cognitive radio networks
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A Thompson sampling approach to channel exploration-exploitation problem in multihop cognitive radio networks

机译：汤普森采样方法解决多跳认知无线电网络中的信道探索-开发问题

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Cognitive radio technology is a promising solution to the exponential growth in bandwidth demand sustained by increasing number of ubiquitous connected devices. The allocated spectrum is opened to the secondary users conditioned on limited interference on the primary owner of the band. A major bottleneck in cognitive radio systems is to find the best available channel quickly from a large accessible set of channels. This work formulates the channel exploration-exploitation dilemma as a multi-arm bandit problem. Existing theoretical solutions to a multi-arm bandit are adapted for cognitive radio and evaluated in an experimental test-bed. It is shown that a Thompson sampling based algorithm efficiently converges to the best channel faster than the existing algorithms and achieves higher asymptotic average throughput. We then propose a multihop extension together with an experimental proof of concept.
机译：认知无线电技术是解决因无处不在的连接设备数量增加而导致带宽需求呈指数增长的有前途的解决方案。分配的频谱向二级用户开放，条件是对频段主要所有者的干扰有限。认知无线电系统的主要瓶颈是从大量可访问的信道中快速找到最佳可用信道。这项工作将渠道勘探与开发难题表述为多臂匪徒问题。现有的针对多臂匪的理论解决方案适用于认知无线电，并在实验测试台上进行了评估。结果表明，基于汤普森采样的算法可以比现有算法更快地收敛到最佳信道，并且可以实现更高的渐近平均吞吐量。然后，我们提出多跳扩展以及概念的实验证明。

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