activity
20182022
most cited6G White Paper on Machine Learning in Wireless Communication Networks

94 citations · 162 across the 3 of their papers we have counts for

collaborators

5 papers

cs.CR202219 cited

Rethinking the Reverse-engineering of Trojan Triggers

Zhenting Wang, Kai Mei, Hailun Ding +2

Deep Neural Networks are vulnerable to Trojan (or backdoor) attacks. Reverse-engineering methods can reconstruct the trigger and thus identify affected models. Existing reverse-eng…

eess.SP202149 cited

A Low Complexity Learning-based Channel Estimation for OFDM Systems with Online Training

Kai Mei, Jun Liu, Xiaoying Zhang +3

In this paper, we devise a highly efficient machine learning-based channel estimation for orthogonal frequency division multiplexing (OFDM) systems, in which the training of the es…

cs.IT202094 cited

6G White Paper on Machine Learning in Wireless Communication Networks

Samad Ali, Walid Saad, Nandana Rajatheva +24

The focus of this white paper is on machine learning (ML) in wireless communications. 6G wireless communication networks will be the backbone of the digital transformation of socie…

eess.SP2018

Deep Neural Network Aided Scenario Identification in Wireless Multi-path Fading Channels

Jun Liu, Kai Mei, Dongtang Ma +1

This letter illustrates our preliminary works in deep nerual network (DNN) for wireless communication scenario identification in wireless multi-path fading channels. In this letter…

eess.SP2018

High-precision timing and frequency synchronization method for MIMO-OFDM systems in double-selective channels

Jun Liu, Kai Mei, Xiaochen Zhang +3

In this letter, a novel synchronization method for MIMO-OFDM systems is proposed. The new approach has an accurate estimate of both symbol timing and large frequency offest. Simula…