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20192026
most citedPAPR Reduction Using Iterative Clipping/Filtering and ADMM Approaches for OFDM-Based Mixed-Numerology Systems

2 citations · 5 across the 4 of their papers we have counts for

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eess.SP2026

Discovery of unobservable parameters via physical embedding

Le Cheng, Xiaoran Liu, Lingjin Kong +7

Recovering a source signal from indirect measurements often requires estimating latent parameters, such as wireless channel states or MRI coil sensitivities, that cannot be directl…

eess.SP2025

Affine Frequency Division Multiplexing for Communication and Channel Sounding: Requirements, Challenges, and Key Technologies

Yu Zhou, Chao Zou, Nanhao Zhou +8

Channel models are crucial for theoretical analysis, performance evaluation, and deployment of wireless communication systems. Traditional channel sounding systems are insufficient…

eess.SP20201 cited

Numerology Selection for OFDM Systems Based on Deep Neural Networks

Xiaoran Liu, Jiao Zhang, Jibo Wei

In order to support diverse scenarios and deployments, the numerology of orthogonal frequency division multiplexing (OFDM) is defined for the parametrization of subcarrier spacing…

eess.SP20192 cited

Peak-to-Average Power Ratio Analysis for OFDM-Based Mixed-Numerology Transmissions

Xiaoran Liu, Lei Zhang, Jun Xiong +3

In this paper, the probability distribution of the peak to average power ratio (PAPR) is analyzed for the mixed numerologies transmission based on orthogonal frequency division mul…

eess.SP20192 cited

PAPR Reduction Using Iterative Clipping/Filtering and ADMM Approaches for OFDM-Based Mixed-Numerology Systems

Xiaoran Liu, Xiaoying Zhang, Lei Zhang +4

Mixed-numerology transmission is proposed to support a variety of communication scenarios with diverse requirements. However, as the orthogonal frequency division multiplexing (OFD…