A Low-complexity Algorithm for Designing Waveforms with Low Weighted Integrated Sidelobe Levels

Waveforms with desirable ambiguity function properties are essential in active sensing and communication systems. This work presents a low-complexity iterative sequential algorithm for designing waveforms with reduced weighted merit factor (WMF) over Doppler frequency ranges of practical interest. T...

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Bibliographic Details
Published in:Wireless personal communications Vol. 140; no. 1-2; pp. 453 - 466
Main Authors: Dai, Xiaoming, Huang, Zhenyue, Luo, Yuquan, Liu, Xinya, Li, Hua, Wang, Xiyuan
Format: Journal Article
Language:English
Published: Dordrecht Springer Nature B.V 01.01.2025
Subjects:
Algorithms
Approximation
Closed form solutions
Communications systems
Complexity
Computational efficiency
Convexity
Decomposition
Design
Doppler effect
Fast Fourier transformations
Fourier transforms
Frequency ranges
Optimization
Performance evaluation
Sidelobes
Taylor series
Waveforms
ISSN:0929-6212, 1572-834X
Online Access:Get full text
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Summary:Waveforms with desirable ambiguity function properties are essential in active sensing and communication systems. This work presents a low-complexity iterative sequential algorithm for designing waveforms with reduced weighted merit factor (WMF) over Doppler frequency ranges of practical interest. To address the inherent non-convexity of the original problem, the proposed approach decomposes it into two simpler quadratic subproblems, which are efficiently solved using approximated closed-form solutions derived from a Taylor expansion-based approximation. This ensures both computational efficiency and practical feasibility. The algorithm leverages the computational efficiency of the fast Fourier transform (FFT) and seamlessly incorporates peak-to-average power ratio (PAPR) constraints, making it well-suited for scenarios requiring strict PAPR limitations. Numerical simulations illustrate that the proposed algorithm achieves a significantly faster convergence rate compared to conventional methods across diverse scenarios, underscoring its robustness, adaptability, and practical applicability.
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ISSN:0929-6212
1572-834X
DOI:10.1007/s11277-024-11730-y