Bayesian‐MLE signal detection for multi‐antenna ambient backscatter communication. Issue 6 (9th March 2022) - Jing, Feng; Zhang, Hailin; Gao, Mei; Xue, Bin
Abstract: Multi‐antenna signal detection is one of the most critical and challenging issues for ambient backscatter communication (AmBC) systems. This paper proposes an efficient multi‐antenna AmBC signal detection method, called Bayesian‐MLE (maximum likelihood estimation). It shows good performance on high transmission rate, detection accuracy and low energy consumption. Particularly, a practical multi‐antenna AmBC system model is developed to offer transmit‐receive diversity, and then an efficient multi‐antenna AmBC signal detection method is presented using Bayesian optimization and MLE theory. Furthermore, to maximize the detection performance, an optimal detection threshold selection scheme is developed. Particularly, a non‐central chi‐square distribution conditional probability density function (PDF) is considered instead of the conventional Gaussian PDF. Extensive qualitative and quantitative experiments are performed, showing that the proposed Bayesian‐MLE detector achieves the state‐of‐the‐art signal detection performance.