Channel estimation for ambient Internet of things

Abstract

Passive backscatter based ambient Internet of things (AIoT) was an important development direction for the future of IoT and currently attracted extensive attentions. In practical applications of AIoT, there existed strong self-interference caused by phase noise and spurs, which brought about new challenges for channel estimation. Therefore, an iterative channel estimator considering phase noise and spurs were designed for the AIoT system with two nodes. Specifically, the estimator was based on the least squares method and complex exponential basis expansion model (CE-BEM), and used iteration to improve estimation accuracy. The Cramér-Rao lower bound (CRLB) of channel estimation parameters was also derived to evaluate the theoretical limit of the estimation accuracy. Finally, simulation results were provided to corroborate the proposed studies.

Keywords

• backscatter communication
• channel estimation
• complex exponential basis expansion model
• Cramér-Rao lower bound
• internet of things
• phase noise
• spurs