@inproceedings{f93fad6552104677b63a61ea0b5aead3,
title = "Blind Equalization under Noisy Environment using Bias-compensated RLS method",
abstract = "In this paper, a new blind adaptive equalization algorithm under noisy environment is proposed. We consider a practical case where the noise of each transmission channel is unknown. By oversampling the channel output at twice the symbol rate, a single-input double-output channel can be obtained. We apply the recursive-least-squares (RLS) to tackle the blind equalization problem. With the noise-induced bias, RLS algorithm is biased. In order to eliminate the bias, we present a bias-compensated RLS (BCRLS) algorithm that can estimate the unknown additive noise online and the noise-induced bias can be therefore removed. The unbiased estimate of the channel characteristics obtained can be used for channel equalization. Simulations results are presented to demonstrate the performance of the proposed algorithm.",
keywords = "Bias-compensated Method, Blind Equalization, Recursive Least Squares Algorithm, Variance Estimation",
author = "Zhen Zhang and Lijuan Jia and Shunshoku Kanae and Yang, {Zi Jiang}",
note = "Publisher Copyright: {\textcopyright} 2021 Technical Committee on Control Theory, Chinese Association of Automation.; 40th Chinese Control Conference, CCC 2021 ; Conference date: 26-07-2021 Through 28-07-2021",
year = "2021",
month = jul,
day = "26",
doi = "10.23919/CCC52363.2021.9550546",
language = "English",
series = "Chinese Control Conference, CCC",
publisher = "IEEE Computer Society",
pages = "3127--3131",
editor = "Chen Peng and Jian Sun",
booktitle = "Proceedings of the 40th Chinese Control Conference, CCC 2021",
address = "United States",
}