ITM Web Conf.
Volume 47, 20222022 2nd International Conference on Computer, Communication, Control, Automation and Robotics (CCCAR2022)
|Number of page(s)||9|
|Section||Computer Science and System Design, Application|
|Published online||23 June 2022|
Polynomial fitting based on least squares approximates for first-order Tracy-Widom distribution
College of Information Science and Engineering, Jishou University, Jishou, Hunan, China
* Corresponding author: firstname.lastname@example.org
Tracy-Widom distribution can primely describe the limit distribution of the largest eigenvalue of noise matrix, so it is widely used in the field of signal processing and wireless communication. The exact expression of this distribution is very complex and difficult to be applied in practice. Therefore, an approximate method of Tracy-Widom distribution based on least squares is proposed, in which the optimal fitting order and optimal fitting coefficient are determined by minimizing the average fitting uncertainty. The simulation results show that the fitting results can accurately predict the largest eigenvalue distribution of the noise matrix, which proves the effectiveness of the polynomial fitting method to approximate the first-order Tracy-Widom distribution.
Key words: First-order Tracy-Widom distribution / Largest eigenvalue / Least squares / Polynomial fit / Fitting uncertainty
© The Authors, published by EDP Sciences, 2022
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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