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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Veröffentlicht in:Wireless personal communications Jg. 140; H. 1-2; S. 453 - 466
Hauptverfasser: Dai, Xiaoming, Huang, Zhenyue, Luo, Yuquan, Liu, Xinya, Li, Hua, Wang, Xiyuan
Format: Journal Article
Sprache:Englisch
Veröffentlicht: Dordrecht Springer Nature B.V 01.01.2025
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ISSN:0929-6212, 1572-834X
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Zusammenfassung: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.
Bibliographie:ObjectType-Article-1
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ISSN:0929-6212
1572-834X
DOI:10.1007/s11277-024-11730-y