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Dancing with light: Predictive in-frame rate selection for visible light networks

机译:与光共舞:针对可见光网络的预测帧内速率选择

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Visible Light Communications (VLC) is emerging as an appealing technology to complement WiFi in indoor environments. Yet maintaining VLC performance under link dynamics remains a challenging problem. In this paper, we build a VLC software-radio testbed and examine VLC channel dynamics through comprehensive measurement. We find minor device movement or orientation change can cause the VLC link SNR to vary by tens of dB even within one packet duration, which renders existing WiFi rate adaptation protocols ineffective. We thus propose a new mechanism, DLit, that leverages two unique properties of VLC links (predictability and full-duplex) to realize fine-grained, in-frame rate adaptation. Our prototype implementation and experiments demonstrate that DLit achieves near-optimal performance for mobile VLC usage cases, and outperforms conventional packet-level adaptation schemes by multiple folds.
机译:可见光通信(VLC)逐渐成为一种有吸引力的技术,可以补充室内环境中的WiFi。然而,在链路动态下保持VLC性能仍然是一个具有挑战性的问题。在本文中,我们构建了一个VLC软件无线电测试平台,并通过综合测量来检查VLC频道动态。我们发现,即使在一个数据包持续时间内,微小的设备移动或方向变化也可能导致VLC链路SNR改变数十dB,这使现有的WiFi速率自适应协议无效。因此,我们提出了一种新的机制DLit,该机制利用VLC链路的两个独特属性(可预测性和全双工)来实现细粒度的帧内速率自适应。我们的原型实现和实验表明,对于移动VLC使用案例,DLit实现了接近最佳的性能,并且其性能比传统的数据包级自适应方案高出了很多倍。

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