Zhou, Yajing and Zhou, Zhengchun and Liu, Zilong and Yang, Yang and Yang, PIng and Fan, Pingzhi (2023) Symmetrical Z-Complementary Code Sets for Optimal Training in Generalized Spatial Modulation. Signal Processing, 208. p. 108990. DOI https://doi.org/10.1016/j.sigpro.2023.108990
Zhou, Yajing and Zhou, Zhengchun and Liu, Zilong and Yang, Yang and Yang, PIng and Fan, Pingzhi (2023) Symmetrical Z-Complementary Code Sets for Optimal Training in Generalized Spatial Modulation. Signal Processing, 208. p. 108990. DOI https://doi.org/10.1016/j.sigpro.2023.108990
Zhou, Yajing and Zhou, Zhengchun and Liu, Zilong and Yang, Yang and Yang, PIng and Fan, Pingzhi (2023) Symmetrical Z-Complementary Code Sets for Optimal Training in Generalized Spatial Modulation. Signal Processing, 208. p. 108990. DOI https://doi.org/10.1016/j.sigpro.2023.108990
Abstract
This paper considers the optimal training design for broadband generalized spatial modulation systems over frequency-selective channels using a novel class of code sets introduced, called "symmetrical Z-complementary code sets", whose aperiodic auto- and cross- correlation sums exhibit zero-correlation zones at both the front-end and tail-end of the entire correlation window. Two constructions of (optimal) symmetrical Z-complementary code sets based on generalized Boolean functions are presented. Numerical evaluations indicate that the proposed training sequences for generalized spatial modulation can achieve optimal channel estimation performance and outperform other classes of sequences.
Item Type: | Article |
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Uncontrolled Keywords: | Complementary code set, channel estimation, training sequence design, generalized spatial modulation, frequency-selective channels |
Divisions: | Faculty of Science and Health Faculty of Science and Health > Computer Science and Electronic Engineering, School of |
SWORD Depositor: | Unnamed user with email elements@essex.ac.uk |
Depositing User: | Unnamed user with email elements@essex.ac.uk |
Date Deposited: | 02 Mar 2023 12:37 |
Last Modified: | 30 Oct 2024 20:56 |
URI: | http://repository.essex.ac.uk/id/eprint/35051 |
Available files
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Licence: Creative Commons: Attribution-Noncommercial-No Derivative Works 4.0