Channel Estimation and Pilot Design for Ambient Internet of Things With Frequency Offsets

Recently backscatter communications and Ambient Internet of Things (A-IoT) arouse extensive interest from both academia and industry. One key parameter for A-IoT is frequency offset (FO), including carrier frequency offset (CFO) and sampling frequency offset (SFO), which is often neglected by existing studies. In this paper, we investigate the channel estimation and optimal pilot design for A-IoT with frequency offsets. Specifically, we first propose a joint FOs and channel estimator and then derive the corresponding Cramer-Rao Bounds (CRBs) for the channel estimates. We then suggest the optimal pilot design for the tag with on-off keying and binary phase shift keying modulation schemes. Finally, extensive numerical results are provided to corroborate our proposed studies.

I. Introduction

Backscatter communications and Ambient Internet of Things (A-IoT) are hot topics for future wireless networks. The sensors or tags in A-IoT collect energy from ambient radio waves and backscatter them for communications. Compared to other communication technologies, the sensors or tags require neither complex RF structures such as power amplifiers, high-precision filters, and high-frequency oscillators, nor the complex baseband processing. Therefore, the design of the sensors and tags can be considerably simplified and their corresponding costs can be significantly reduced [1].