Unscented Kalman Filtering Over Full-Duplex Relay Networks Under Binary Encoding Schemes
Licheng Wang, Zidong Wang, Shuai Liu, Daogang Peng
Abstract
In this article, a modified unscented Kalman filter design algorithm is proposed for discrete-time stochastic nonlinear systems over full-duplex relay networks with binary encoding schemes. In order to enhance the transmission reliability, a full-duplex relay is deployed between sensors and the filter, and a self-interference cancellation scheme is introduced to eliminate the interference caused by the relay itself. To accommodate the digital communication manner, a binary encoding scheme is adopted, and a sequence of random variables obeying Bernoulli distribution is introduced to characterize statistical behaviors of the random bit flips. The objective of the addressed problem is to design an unscented Kalman filter over full-duplex relay networks with binary encoding schemes that reflects the impacts of the decoding error, the bit flips, and the full-duplex relay on the filtering performance. A sufficient condition is developed using the matrix inverse lemma to guarantee the exponential mean-square boundedness of the filtering error. Finally, a simulation study is carried out to demonstrate the effectiveness of the developed binary-encoding-based unscented Kalman filter over a full duplex network.