Constellation Learning-Based Signal Detection for Ambient Backscatter Communication Systems

TLDR

Ambient backscatter communication offers energy‑ and spectrum‑efficient IoT solutions, yet recovering tag data is difficult because channel‑state information is hard to obtain. To avoid CSI estimation, this work introduces a label‑assisted transmission scheme where the tag sends two known labels before data. By exploiting constellation information, a modulation‑constrained expectation‑maximization algorithm is devised, yielding two detection methods—one that clusters only labeled signals and another that clusters all received signals—with efficient initialization. Simulations demonstrate that these constellation‑learning methods match the performance of an optimal detector that assumes perfect CSI.

Abstract

Ambient backscatter communication (AmBC) is a promising solution to energy-efficient and spectrum-efficient Internet of Things with stringent power and cost constraints. In an AmBC system, recovering the tag information at the reader, however, is a challenging task due to the difficulty in acquiring the relevant channel-state information (CSI). To eliminate the need to estimate the CSI, in this paper, we propose a label-assisted transmission framework, in which two known labels are transmitted from the tag before data transmission. By exploring the received signal constellation information, we propose modulation-constrained expectation maximization algorithm, based on which two detection methods are developed. One method, referred to as constellation learning with labeled signals, learns the parameters by clustering the labeled signals and recovers the unlabeled signals by the learnt parameters. The other method, referred to as constellation learning with labeled and unlabeled signals, uses all received signals in clustering. Efficient initialization techniques are provided for the two clustering algorithms. Finally, extensive simulation results show that the proposed constellation learning methods achieve comparable performance as the optimal detector with perfect CSI.