Abstract
We propose a fixed-lag particle smoother (FLPS) for time-varying frequency-selective and nonlinear channel estimation. Compared to the standard particle filter (PF) which tracks the filtering distribution of the state variable, the FLPS tracks the fixed-lag smoothing distribution of the state variable. The choice of the proposal distribution and the computation of the importance weights are derived. Simulations are provided to illustrate the performance of the FLPS under different system settings. Performance comparison of the FLPS with the standard PF is provided. Simulation results show that the FLPS outperforms the PF with the similar computational costs.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
