Symbol Detection of Ambient Backscatter Systems with Manchester Coding

TL;DR

This paper introduces Manchester coding-based detection methods for ambient backscatter systems, improving reliability and reducing delay in IoT networks by leveraging novel encoding and detection techniques.

Contribution

It proposes new Manchester coding and detection schemes for ambient backscatter, with analytical BER analysis and superior performance over prior detectors.

Findings

SeCoMC detector outperforms NoCoMC in BER

Unknown deterministic ambient signals yield better BER

Proposed detectors achieve lower delay and better BER

Abstract

Ambient backscatter communication is a newly emerged paradigm, which utilizes the ambient radio frequency (RF) signal as the carrier to reduce the system battery requirement, and is regarded as a promising solution for enabling large scale deployment of future Internet of Things (IoT) networks. The key issue of ambient backscatter communication systems is how to perform reliable detection. In this paper, we propose novel encoding methods at the information tag, and devise the corresponding symbol detection methods at the reader. In particular, Manchester coding and differential Manchester coding are adopted at the information tag, and the corresponding semi-coherent Manchester (SeCoMC) and non-coherent Manchester (NoCoMC) detectors are developed. In addition, analytical bit error rate (BER) expressions are characterized for both detectors assuming either complex Gaussian or unknown deterministic ambient signal. Simulation results show that the BER performance of unknown deterministic ambient signal is better, and the SeCoMC detector outperforms the NoCoMC detector. Finally, compared with the prior detectors for ambient backscatter communications, the proposed detectors have the advantages of achieving superior BER performance with lower communication delay.