FreeBack: Blind and Distributed Rate Adaptation in LoRa-based Backscatter Networks

For large-scale Internet of Things (IoT), backscatter communication is a promising technology to reduce power consumption and simplify deployment. However, due to the variable excitation source (ES) signal strength and time-varying channel condition, backscatter communication lacks stability, along with limited communication range as a few meters. Adaptive date rate (ADR) is beneficial to solve such issues, but is burdensome when implement on the capability limited tags. In this paper, we design a system named FreeBack with rate adaptation in backscatter communication. Our modulation approach is denoted as Adaptive Chirp-OOK where the ES recursively generates chirp signal, and the tags reflect the chirp signal with the On-Off Key modulation. According to channel symmetry, the tags perform rate adaption only based on the received ES signal strength instead of feedback from receiver. Such adaptation method enables the receiver to successfully decode signal through the time-varying channel, even for signal under the noise floor. We have implemented the prototype system based on the USRP platform. Extensive experiment results demonstrate the effectiveness of the proposed system. Our system provides valid ES-tag distance up to 27m, which is $ 7\times$ as compared with normal backscatter system. FreeBack significantly increases the backscatter communication stability, by supporting data rate adaptation ranges from 0. 33kbps to 1. 2Mbps, and guaranteeing the bit error rate (BER) below 1%.