$l_{p}$-norm. The first algorithm resorts to the alternating direction method of multipliers (ADMM) framework, and each subproblem is obtained with a closed-form solution. The second algorithm merges the penalty distance (PD) method and manifold optimization. The crux of this approach is to obtain the closed-form Euclidean PD term via the Karush-Kuhn-Tucker conditions and leverage the Riemannian conjugate gradient (RCG) framework, and we name this algorithm PD-RCG. Numerical examples demonstrate the effectiveness of our proposed algorithms. Comparatively speaking, the ADMM-based algorithm has better performance in protecting the friendly devices, while the PD-RCG algorithm performs better on the computational efficiency and the worst-case CPS of the target equipment.">

Maximin Design of Wideband Constant Modulus Waveform for Distributed Precision Jamming (original) (raw)

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