A Low-complexity Algorithm for Designing Waveforms with Low Weighted Integrated Sidelobe Levels - Dai, Xiaoming; Huang, Zhenyue; Luo, Yuquan; Liu, Xinya; Li, Hua; Wang, Xiyuan (Wireless personal communications, 2025)
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.