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For large-scale Internet of Things (IoT), backscatter communication is apromising technology to reduce power consumption and simplify deployment.However, backscatter communication lacks stability, along with limitedcommunication range within a few meters. Due to the limited computation abilityof backscatter tags, it is burdensome to effectively adapt the bitrate for thetime-varying channel. Thus, backscatter tags are failed to fully utilize theoptimal transmission rate. In this paper, we design a system named COOK withself-reliant bitrate adaptation in backscatter communication. Channel symmetryallows backscatter tags to adjust bitrate depending on the received signalstrength of the excitation source (ES) without feedback. In addition, the chirpspreading signal is exploited as the ES signal to enable backscatter tags towork under noise floor. Our modulation approach is denoted as Chirp-OOK sincethe tags reflect the chirp signal by employing the on-off keying modulation. Itallows that receiver can decode under the noise floor and the bitrate variesflexibly as the communication range changes. We have implemented the prototypesystem based on the universal software radio peripheral (USRP) platform.Extensive experiment results demonstrate the effectiveness of the proposedsystem. Our system provides valid communication distance up to $27m$, which is7 times as compared with normal backscatter system. The system significantlyincreases the backscatter communication stability, by supporting bitrateadaptation ranges from 0.33kbps to 1.2Mbps, and guaranteeing the bit error rate(BER) is below 1%.

COOK: Chirp-OOK Communication with Self-reliant Bitrate Adaptation in Backscatter Networks