Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/166633
Title: A novel design of flag sequences for low-complexity delay-doppler estimation
Authors: Meng, Lingsheng
Guan, Yong Liang
Ge, Yao
Liu, Zilong
Keywords: Engineering::Electrical and electronic engineering
Issue Date: 2022
Source: Meng, L., Guan, Y. L., Ge, Y. & Liu, Z. (2022). A novel design of flag sequences for low-complexity delay-doppler estimation. 2022 10th International Workshop on Signal Design and Its Applications in Communications (IWSDA). https://dx.doi.org/10.1109/IWSDA50346.2022.9870605
Project: A19D6a0053 
Conference: 2022 10th International Workshop on Signal Design and Its Applications in Communications (IWSDA)
Abstract: This paper presents a novel design of Flag sequences whose ambiguity functions (AFs) are featured by the peak-curtain property. Such a property can be exploited for efficient identification of the AF peak by first searching the curtain, thus leading to low-complexity delay-Doppler estimation. Motivated by the high AF sidelobes of the existing Flag sequences, we propose to minimize the customized weighted integrated sidelobe level (CWISL) with the aid of an Accelerated Partially Majorization-Minimization Algorithm (APMMA). Numerical results demon-strate that our optimized Flag sequences have lower CWISL and peak sidelobe level (PSL) in the delay-Doppler zone of interest.
URI: https://hdl.handle.net/10356/166633
ISBN: 9781665452984
ISSN: 2150-3699
DOI: 10.1109/IWSDA50346.2022.9870605
Schools: School of Electrical and Electronic Engineering 
Research Centres: Continental-NTU Corporate Lab
Rights: © 2022 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. The published version is available at: https://doi.org/10.1109/IWSDA50346.2022.9870605.
Fulltext Permission: open
Fulltext Availability: With Fulltext
Appears in Collections:EEE Conference Papers

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