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Channel-Aware Rate Adaptation for Backscatter Networks

Wei Gong,Haoxiang Liu,Jiangchuan Liu,Xiaoyi Fan,Kebin Liu,Q. Ma,Xiaoyue Ji

Published 2018 in IEEE/ACM Transactions on Networking

ABSTRACT

Backscatter communication networks receive much attention recently due to the small size and low power of backscatter nodes. As backscatter communication is often influenced by the dynamic wireless channel quality, rate adaptation becomes necessary. Most existing approaches share a common drawback: they fail to take both spatial and frequency diversity into consideration at the same time. Consequently, the transmission rate may be improperly selected, resulting in low network throughput. In this paper, we propose a channel-aware rate adaptation framework (CARA) for backscatter networks. CARA incorporates three essential modules, a lightweight channel probing scheme that differentiates collisions from packet losses, a burstiness-aware channel selection mechanism benefiting as many backscatter nodes as possible, a rate selection method choosing the optimal rate, and a mobility detection that discovers location changes. We implement CARA on commercial readers, and the experiment results show that CARA achieves up to $4 \times$ goodput gain compared with the state-of-the-art rate adaptation scheme.

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