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Deep Federated Learning Based Convergence Analysis in Relaying-Aided MEC-IoT Networks

Year: 2022
Type: article
Abstract: Recently, deep federated learning has attracted much attention from researchers in the fields of wireless communications, where the relaying technique has been shown as a powerful technology to assist the wireless signals and enhance the transmission quality, which is very important to the development of mobile edge computing (MEC) based Internet of Things (IoT) networks. In a relaying-aided MEC-IoT system, it is of vital importance to deeply investigate the system signal-to-noise ratio (SNR) at the receiver side, as it mainly determines the system performance metrics, such as capacity (or achievable data rate), outage probability, and bit-error-rate (BER). To this end, we first investigate the instantaneous convergence error, by deeply studying the relationship between the instantaneous two-hop relaying channels. We then investigate the statistical convergence error, by performing the statistical expectation with respect to the two-hop relaying channels. We finally present some results to show that the analysis of the convergence error is effective. The work in this paper can provide some theoretical foundation for deep federated learning and computing networks.
DOI: 10.1155/2022/8425975
Authors: Jun Liu, Tao Cui, Lin Zhang, Yuwei Zhang, Jing Wang, Chao Li, Kai Chen, Huang Huang, Xuan Zhou, Wei Zhou, Sun Li, Suili Feng, Dongqing Xie, Yun Li, Haige Xiang, Kaimeno Dube, Abbarbas Muazu, Nakilavai Rono, Wen Zhou, Fusheng Zhu, Liming Chen, Dan Deng, Zhao Wang, Yajuan Tang
Institutions: Tsinghua University, Hamdard University, Huawei Technologies (Sweden), Huawei Technologies (Germany), Huawei Technologies (France), Nanjing Forestry University, Huawei Technologies (Canada), Xi'an Jiaotong University, King Abdullah University of Science and Technology, South China University of Technology, Peking University, Anhui University of Technology, University of Illinois Urbana-Champaign, Ahmedabad University, Vaal University of Technology, Baze University, Rongo University, China Southern Power Grid (China), University of Science and Technology of China, Ericsson (Sweden), Shantou University
Language: English
Open Access status: gold
Estimated APC paid: $1,400
OpenAlex ID: W4297464455
FWCI: 0.793
Cites: 15
Cited by: 8
Related to: 10