An Investigation into Using Kalman Filtering for Phase Estimation in IEEE 802.15.4 /ZigBee Receivers Running on Adjacent Channel Interference

Abstract

Recent research states that IEEE 802.15.4 /ZigBee is prone to run on Adjacent Channel Interference (ACI) when dealing with wireless industrial networks because of the increasing number of sensors and actuators. Costas Phase Locked-Loop (PLL) is used in ZigBee receivers for phase carrier recovery. The study in this paper aims at investigating the performance of applying Linear Kalman Filter (LKF) as (PLL) to estimate the phase changes in IEEE 802.15.4/ZigBee receivers in industrial environments. LKF is used to estimate and optimize the carrier phase of Binary Phase Shift Keying (BPSK) modulated signal by reducing the phase error in the presence of Gaussian noise and Adjacent Channel Interference (ACI). A MATLAB-based simulator is developed to demonstrate ZigBee transceiver with the impact of such a filter. The results show that LKF estimates the changes of carrier phase of BPSK modulated signal correctly and the performance of estimation is measured by Mean Square Error (MSE) for different Signal to Noise Ratio (SNR). MSE measures the phase error deviation of LKF estimator and Costas PLL from the true phase. This study proposes a novel method to address the need for implementing optimal filter instead of traditional and Costas PLL to estimate the carrier of the transmitted signal in the presence of Gaussian noise along with ACI.