no code implementations • 8 Apr 2024 • Teng Ma, Yue Xiao, Xia Lei, Ming Xiao
Specifically, we expect to guarantee the communication quality while masking the real direction of the SR transmitter during the communication.
no code implementations • 31 Mar 2024 • Shudi Weng, Chengxi Li, Ming Xiao, Mikael Skoglund
We investigate federated learning (FL) in the presence of stragglers, with emphasis on wireless scenarios where the power-constrained edge devices collaboratively train a global model on their local datasets and transmit local model updates through fading channels.
no code implementations • 25 Mar 2024 • Xiaojie Li, Songyang Zhang, Hang Li, Xiaoyang Li, Lexi Xu, Haigao Xu, Hui Mei, Guangxu Zhu, Nan Qi, Ming Xiao
Multi-band radiomap reconstruction (MB-RMR) is a key component in wireless communications for tasks such as spectrum management and network planning.
no code implementations • 22 Mar 2024 • Chengxi Li, Ming Xiao, Mikael Skoglund
In ACFL, before the training, each device uploads a coded local dataset with additive noise to the central server to generate a global coded dataset under privacy preservation requirements.
no code implementations • 5 Nov 2022 • Mingming Wu, Yue Xiao, Yulan Gao, Ming Xiao
A novel reconfigurable intelligent surface (RIS)-aided hybrid reflection/transmitter design is proposed for achieving information exchange in cross-media communications.
no code implementations • 14 Sep 2022 • LiAn Yang, Ming Xiao, Xian Li, Ya-lan Wang
Mutations in STK11/LKB1 and NF1 genes have been found in ADC and SQC and are often associated with drug resistance and poor prognosis, but STK11/NF1 co-mutation has not been reported and more cases are needed to reveal the association.
no code implementations • 18 Jul 2022 • Albert Lu, Jordan Marshall, Yifan Wang, Ming Xiao, Yuhao Zhang, Hiu Yung Wong
In this paper, two methodologies are used to speed up the maximization of the breakdown volt-age (BV) of a vertical GaN diode that has a theoretical maximum BV of ~2100V.
no code implementations • 7 Feb 2022 • Hao Chen, Yu Ye, Ming Xiao, Mikael Skoglund
This paper studies the problem of training an ML model over decentralized systems, where data are distributed over many user devices and the learning algorithm run on-device, with the aim of relaxing the burden at a central entity/server.
no code implementations • 20 Nov 2021 • Hao Chen, Ming Xiao, Zhibo Pang
Driven by the ever-increasing penetration and proliferation of data-driven applications, a new generation of wireless communication, the sixth-generation (6G) mobile system enhanced by artificial intelligence (AI), has attracted substantial research interests.
no code implementations • 22 Oct 2021 • Hao Chen, Shaocheng Huang, Deyou Zhang, Ming Xiao, Mikael Skoglund, H. Vincent Poor
Hence, we investigate the problem of jointly optimized communication efficiency and resources for FL over wireless Internet of things (IoT) networks.
no code implementations • 10 Aug 2021 • Jin Huang, Ming Xiao
The recurrent neural networks (RNN) with richly distributed internal states and flexible non-linear transition functions, have overtaken the dynamic Bayesian networks such as the hidden Markov models (HMMs) in the task of modeling highly structured sequential data.
no code implementations • 30 Jun 2021 • Wanlu Lei, Yu Ye, Ming Xiao, Mikael Skoglund, Zhu Han
Alternating direction method of multipliers (ADMM) has a structure that allows for decentralized implementation, and has shown faster convergence than gradient descent based methods.
no code implementations • 2 Oct 2020 • Hao Chen, Yu Ye, Ming Xiao, Mikael Skoglund, H. Vincent Poor
A class of mini-batch stochastic alternating direction method of multipliers (ADMM) algorithms is explored to develop the distributed learning model.
no code implementations • 27 Jul 2020 • Yue Xiao, Yu Ye, Shaocheng Huang, Li Hao, Zheng Ma, Ming Xiao, Shahid Mumtaz
To handle the data explosion in the era of internet of things (IoT), it is of interest to investigate the decentralized network, with the aim at relaxing the burden to central server along with keeping data privacy.
Signal Processing
no code implementations • 22 Jun 2020 • Shaocheng Huang, Yu Ye, Ming Xiao, H. Vincent Poor, Mikael Skoglund
Cell-free networks are considered as a promising distributed network architecture to satisfy the increasing number of users and high rate expectations in beyond-5G systems.
no code implementations • 27 Apr 2020 • Shaocheng Huang, Yu Ye, Ming Xiao
Hybrid beamforming (HBF) design is a crucial stage in millimeter wave (mmWave) multi-user multi-input multi-output (MU-MIMO) systems.
no code implementations • 16 Apr 2020 • Shaocheng Huang, Yu Ye, Ming Xiao
We propose two learning schemes to design HBF for FD mmWave systems, i. e., extreme learning machine based HBF (ELM-HBF) and convolutional neural networks based HBF (CNN-HBF).
no code implementations • 22 Aug 2019 • Yu Ye, Ming Xiao, Mikael Skoglund
To determine the caching scheme for decentralized caching networks, the content preference learning problem based on mobility prediction is studied.
no code implementations • 25 Apr 2019 • Yu Ye, Ming Xiao, Mikael Skoglund
We first present the ELM based MTL problem in the centralized setting, which is solved by the proposed MTL-ELM algorithm.