Priori-Information Aided Iterative Hard Threshold: A Low-Complexity High-Accuracy Compressive Sensing Based Channel Estimation for TDS-OFDM
Zhen Gao, Chao Zhang, Zhaocheng Wang, Sheng Chen

TL;DR
This paper introduces a low-complexity, high-accuracy channel estimation method for TDS-OFDM using a priori information and iterative hard thresholding, improving performance in doubly selective fading channels.
Contribution
It proposes a novel priori-information aided iterative hard threshold algorithm that enhances channel estimation accuracy and reduces computational complexity for TDS-OFDM systems.
Findings
Significantly improves channel estimation accuracy in doubly selective fading channels.
Reduces computational complexity compared to classical algorithms.
Outperforms existing schemes in various severe fading scenarios.
Abstract
This paper develops a low-complexity channel estimation (CE) scheme based on compressive sensing (CS) for time-domain synchronous (TDS) orthogonal frequency-division multiplexing (OFDM) to overcome the performance loss under doubly selective fading channels. Specifically, an overlap-add method of the time-domain training sequence is first proposed to obtain the coarse estimates of the channel length, path delays and path gains of the wireless channel, by exploiting the channel's temporal correlation to improve the robustness of the coarse CE under the severe fading channel with long delay spread. We then propose the priori-information aided (PA) iterative hard threshold (IHT) algorithm, which utilizes the priori information of the acquired coarse estimate for the wireless channel and therefore is capable of obtaining an accurate channel estimate of the doubly selective fading channel.…
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