An Improved DFT-based Channel Estimation for Mobile Communication Systems

TL;DR

This paper introduces an enhanced DFT-based channel estimation method for mobile systems that cleans reference signals in the time domain to improve accuracy without requiring prior channel information.

Contribution

It proposes a novel DFT-based channel estimation scheme that preprocesses reference signals to reduce noise, enhancing performance in practical mobile communication scenarios.

Findings

Improved estimation accuracy demonstrated in simulations.

No prior channel information needed for the proposed method.

Outperforms conventional schemes in various channel models.

Abstract

Channel estimation is one of the most important parts in current mobile communication systems. Among the huge contributions in channel estimation studies, the discrete Fourier transform (DFT)-based channel estimation has attracted lots of interests since it can not only be easily implemented but also have acceptable performance in practical systems. In this paper, we propose an improved DFT-based channel estimation scheme that tries to clean the reference signals in the time domain before being used for interpolation using the estimated noise variance from reference signals on multiple orthogonal frequency division multiplexing (OFDM) symbols via the property of DFT. The proposed channel estimation scheme does not need any priori channel information. We validate the proposed channel estimation scheme in various channel models via simulations and comparison with conventional channel estimation schemes.