Recent advances in backscatter communication have exhibited great advantages on uplink, both in power consumption and communication performance. However, their downlink tends to lag far behind due to stringent on-device power constraints. This paper presentsSisyphus, a novel communication paradigm designed to empower backscatter devices with LoRa downlink. To achieve this, we propose a novel receiver design for passive coherent demodulation of LoRa. In this design, we creatively couple LoRa’s down-conversion with de-chirping (dc2), leveraging the processing gain brought by chirp spread spectrum (CSS) modulation to boost communication range without the need for additional power supply. Moreover, we exploit the cyclical time-frequency feature intrinsic to LoRa for demodulation, and a low-power analog-digital signal processing circuit with negligible power is devised to replace the existing power-intensive sampling and costly digital computation. We prototype Sisyphus for proof-of-concept, and comprehensive experimental results demonstrate that Sisyphus can achieve significant power savings compared to legacy LoRa receiver while retaining the anti-interference ability of legacy LoRa. We envision that the design of Sisyphus can unlock the potential for broader applications of LoRa-based backscatter devices.

In this paper, a neural network-based symmetric cipher design methodology is proposed to provide high performance data encryption. The proposed approach is a novel attempt to apply the parallel processing capability of neural networks for cryptography purposes. By incorporating neural networks approach, the proposed cipher releases the constraint on the length of the secret key. The proposed cipher is robust in resisting different cryptanalysis attacks and provides efficient data integrity and authentication services. The design of the symmetric cipher is presented and its security is analyzed. Simulation results are presented to validate the effectiveness of the proposed cipher design.