Low-Complexity 2D LMMSE Channel Estimation for OFDM Systems

Abstract

In this paper, we propose a novel method of reducing the complexity of a pilot-based two-dimensional linear minimum mean square error (2D LMMSE) channel estimation scheme for orthogonal frequency division multiplexing (OFDM) systems. We identify that the 2D LMMSE channel estimation method aided by pilots embedded in a two-dimensional OFDM resource grid can be decoupled into three steps: (a) pilot denoising, (b) interpolation in each of OFDM symbols including pilots, and (c) interpolation across OFDM symbols. In the denoising step, we process pilots only for noise reduction. In the following interpolation steps, we utilize two-dimensional channel correlation across subcarriers (frequency) and across OFDM symbols (time) in order to get channel estimates of interest. Under the assumption that the frequency and time correlations are disjoint and the channel correlation can be represented by the product of them, we show that the channel interpolation can be performed in two steps along the frequency domain first and then along the time domain. By taking advantage of this separation, we can reduce the complexity of 2D LMMSE considerably while still achieving the optimal performance of it.