most citedAccurate Closed-Form Approximations to Channel Distributions of RIS-Aided Wireless Systems

10 citations · 31 across the 5 of their papers we have counts for

collaborators

8 papers

cs.CV20219 cited

RMNet: Equivalently Removing Residual Connection from Networks

Fanxu Meng, Hao Cheng, Jiaxin Zhuang +2

Although residual connection enables training very deep neural networks, it is not friendly for online inference due to its multi-branch topology. This encourages many researchers…

cs.IT20212 cited

Quantum Algorithm for DOA Estimation in Hybrid Massive MIMO

Fanxu Meng

The direction of arrival (DOA) estimation in array signal processing is an important research area. The effectiveness of the direction of arrival greatly determines the performance…

cs.CV2021

An Empirical Study and Analysis on Open-Set Semi-Supervised Learning

Huixiang Luo, Hao Cheng, Fanxu Meng +4

Pseudo-labeling (PL) and Data Augmentation-based Consistency Training (DACT) are two approaches widely used in Semi-Supervised Learning (SSL) methods. These methods exhibit great p…

cs.IT20201 cited

A Novel RIS-Assisted Modulation Scheme

Liang Yang, Fanxu Meng, Mazen O. Hasna +1

In this work, in order to achieve higher spectrum efficiency, we propose a reconfigurable intelligent surface (RIS)-assisted multi-user communication uplink system. Different from…

cs.CV2020

Pruning Filter in Filter

Fanxu Meng, Hao Cheng, Ke Li +4

Pruning has become a very powerful and effective technique to compress and accelerate modern neural networks. Existing pruning methods can be grouped into two categories: filter pr…

cs.IT202010 cited

Accurate Closed-Form Approximations to Channel Distributions of RIS-Aided Wireless Systems

Liang Yang, Fanxu Meng, Qingqing Wu +2

This paper proposes highly accurate closed-form approximations to channel distributions of two different reconfigurable intelligent surface (RIS)-based wireless system setups, name…