Phase Noise Impairment and Environment-Adaptable Fast (EAF) Optimization for Programming of Reconfigurable Radio Frequency (RF) Receivers

In order to support a multi-standard platform, a reconfigurable RF front-end needs an optimal configuration that adapts to a dynamic communication condition. To find an optimal configuration efficiently, we previously proposed the Environment-Adaptable Fast (EAF) optimization in terms of the RF impairments of gain, nonlinearity and noise figure. However, this preliminary study did not include the important impairment of phase noise. In this paper, we extend the EAF optimization algorithm to phase noise impairment in a reconfigurable RF front-end. In this study, we will propose a novel statistical estimation tool for obtaining phase noise spectrum information with the Interpolated FIR (IFIR) model and the least mean squares (LMS) adaptive algorithm. We formulate the calculation of the Signal-to-Interference-and-Noise Ratio (SINR) which hastens the optimization process. Phase noise is included in the SINR calculation. We demonstrate the efficient performance of the EAF optimization method even with phase noise impairment. This study shows that while finding an optimal configuration, the EAF optimization significantly reduces simulation time compared to the other four conventional optimization methods.