Abstract
In orthogonal frequency division multiplexing (OFDM) systems, two-dimensional (both time and frequency) minimum mean square error (2D-MMSE) channel estimation is optimum. However, accurate channel statistics are required to realize it, which are often unavailable in practice. In contrast, two-dimensional adaptive channel estimation based on a two-dimensional least mean square (2D-LMS) algorithm does not require any channel statistics, and at the same time can make full use of the time and frequency-domain correlations of the frequency response of time-varying dispersive fading channels. In this paper, we further study two-dimensional adaptive channel estimation in OFDM systems. We derive two-dimensional normalized least mean square (2D-NLMS) algorithm and find that the 2D-LMS algorithm with the optimum step-size parameter is just its special case. Furthermore, a parallel 2D-(N)LMS channel estimation scheme is proposed to solve the realtime realization problem due to high computational complexity encountered by two-dimensional adaptive channel estimation. Finally, we apply two-dimensional adaptive channel estimation to multiple-input multiple-output (MIMO) OFDM systems.
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.
