Abstract
Orthogonal frequency division multiplexing (OFDM) combined with the coordinated multi-point (CoMP) transmission technique has been proposed to improve performance of the receivers located at the cell border. However, the inevitable carrier frequency offset (CFO) will destroy the orthogonality between subcarriers and induce strong inter-carrier interference (ICI) in OFDM systems. In a CoMP-OFDM system, the impact of CFO is more severe because of the mismatch in carrier frequencies among multiple transmitters. To reduce performance degradation, CFO estimation and compensation is essential. For simultaneous estimation of multiple CFOs, the performance of conventional CFO estimation schemes is significantly degraded by the mutual interference among the signals from different transmitters. In this work, our goal is to propose an effective approach that can simultaneously estimate multiple CFOs in the downlink by using the composite signal coming from multiple base stations corresponding to CoMP transmission. Based on the Zadoff-Chu sequences, we design an optimal set of training sequences, which minimizes the mutual interference and is robust to the variations in multiple CFOs. Then, we propose a maximum likelihood (ML)-based estimator, the robust multi-CFO estimation (RMCE) scheme, for simultaneous estimation of multiple CFOs. In addition, by incorporating iterative interference cancellation into the RMCE scheme, we propose an iterative scheme to further improve the estimation performance. According to the simulations, our scheme can eliminate the mutual interference effectively, approaching the Cramer-Rao bound performance.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Disclaimer: 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.