Denoising Higher-Order Moments for Blind Digital Modulation Identification in Multiple-Antenna Systems
Sofiane Kharbech, Eric Pierre Simon, Akram Belazi, Wei Xiang
Abstract
This letter proposes a new technique that substantially improves blind digital modulation identification (DMI) algorithms that are based on higher-order statistics (HOS). The proposed technique takes advantage of noise power estimation to make an offset on higher-order moments (HOM), thus getting an estimate of noise-free HOM. When tested for multiple-antenna systems, the proposed method outperforms other DMI algorithms, in terms of identification accuracy, that are based only on cumulants or do not consider HOM denoising, even for a receiver with impairments. The improvement is achieved with the same order of complexity of the common HOS-based DMI algorithms in the same context.
Topics & Concepts
Higher-order statisticsCumulantComputer scienceNoise reductionAlgorithmModulation (music)Context (archaeology)Noise powerNoise (video)Offset (computer science)Identification (biology)MathematicsArtificial intelligencePower (physics)Signal processingTelecommunicationsStatisticsPhilosophyAestheticsImage (mathematics)Quantum mechanicsPhysicsBiologyProgramming languageRadarPaleontologyBotanyWireless Signal Modulation ClassificationBlind Source Separation TechniquesFractal and DNA sequence analysis