1 code implementation • 18 May 2023 • Zhijie Xie, S. H. Song
This paper investigates the federated version of Approximate PI (API) and derives its error bound, taking into account the approximation error introduced by environment heterogeneity.
no code implementations • 3 Sep 2022 • Yifan Ma, Xianghao Yu, Jun Zhang, S. H. Song, Khaled B. Letaief
In limited feedback multi-user multiple-input multiple-output (MU-MIMO) cellular networks, users send quantized information about the channel conditions to the associated base station (BS) for downlink beamforming.
no code implementations • 30 Jul 2022 • Lei Xie, Xianghao Yu, S. H. Song
Maneuvering target sensing will be an important service of future vehicular networks, where precise velocity estimation is one of the core tasks.
1 code implementation • 18 Apr 2022 • Zhijie Xie, S. H. Song
A necessary condition for the global policy to be learn-able from the local policy is also derived, which is directly related to the heterogeneity level.
1 code implementation • 21 Mar 2022 • Yifei Shen, Jun Zhang, S. H. Song, Khaled B. Letaief
For design guidelines, we propose a unified framework that is applicable to general design problems in wireless networks, which includes graph modeling, neural architecture design, and theory-guided performance enhancement.
no code implementations • 14 Mar 2022 • Lumin Liu, Jun Zhang, S. H. Song, Khaled B. Letaief
Federated Distillation (FD) is a recently proposed alternative to enable communication-efficient and robust FL, which achieves orders of magnitude reduction of the communication overhead compared with FedAvg and is flexible to handle heterogeneous models at the clients.
no code implementations • 1 Oct 2021 • Yifan Ma, Yifei Shen, Xianghao Yu, Jun Zhang, S. H. Song, Khaled B. Letaief
Furthermore, such networks will vary dynamically in a significant way, which makes it intractable to develop comprehensive analytical models.
no code implementations • 3 Aug 2021 • Yifan Ma, Yifei Shen, Xianghao Yu, Jun Zhang, S. H. Song, Khaled B. Letaief
Channel estimation and beamforming play critical roles in frequency-division duplexing (FDD) massive multiple-input multiple-output (MIMO) systems.
1 code implementation • 16 May 2019 • Lumin Liu, Jun Zhang, S. H. Song, Khaled B. Letaief
To combine their advantages, we propose a client-edge-cloud hierarchical Federated Learning system, supported with a HierFAVG algorithm that allows multiple edge servers to perform partial model aggregation.