面向高吞吐率的后向散射网络适应

Wei Gong, Si Chen, Jiangchuan Liu
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引用次数: 23

摘要

最近,反向散射网络引起了人们的极大兴趣,因为它们提供了一种无电池的通信模式,使用传播无线电波,而不是传统传感器网络中的有源无线电,同时提供了类似的传感功能,从光和温度传感器到最近的麦克风和相机。虽然后向散射节点上的传感数据在数量和种类上都有明显的增加,但后向散射通信并没有为传输这种连续的、大容量的数据做好充分的准备和优化。为了弥补这一差距,我们通过探索后向散射链路的独特特征和ISO 18000-6C (C1G2)协议的设计空间,提出了一种高吞吐量的后向散射网络适应方案。我们的主要见解是,虽然先前的工作使下行链路无人值管,但我们观察到下行链路的质量受到多径衰落的显著影响,因此可以大大降低上行链路和总体吞吐量。因此,我们引入了一种新的速率映射算法,该算法可以选择下行链路和上行链路的最佳速率。此外,我们还设计了一种完全兼容C1G2协议的高效信道估计方法和可靠的探测触发器,大大节省了探测开销。我们的方案是使用COTS RFID阅读器和标签的原型。结果表明,在各种移动性、信道和网络规模条件下,我们比最先进的方法实现了高达2.5倍的吞吐量增益。
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Towards higher throughput rate adaptation for backscatter networks
Recently backscatter networks have received booming interest because, they offer a battery-free communication paradigm using propagation radio waves as opposed to active radios in traditional sensor networks while providing comparable sensing functionalities, ranging from light and temperature sensors to recent microphones and cameras. While sensing data on backscatter nodes has been seen on a clear path to increase in both volume and variety, backscatter communication is not well prepared and optimized for transferring such continuous and high-volume data. To bridge this gap, we propose a high-throughput rate adaptation scheme for backscatter networks by exploring the unique characteristics of backscatter links and the design space of the ISO 18000-6C (C1G2) protocol. Our key insight is that while prior work has left the downlink unattended, we observe that the quality of downlink is affected significantly by multipath fading and thus can degrade the uplink and overall throughput considerably. Therefore, we introduce a novel rate mapping algorithm that chooses the best rate for both the downlink and uplink. Also, we design an efficient channel estimation method fully compatible with the C1G2 protocol and a reliable probing trigger, substantially saving probing overhead. Our scheme is prototyped using a COTS RFID reader and tags. The results show that we achieve up to 2.5x throughput gain over state-of-the-art approaches across various mobility, channel, and network-size conditions.
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