A Multi - Task Learning Model for Super Resolution of Wireless Channel Characteristics-Reference-Cited by-同舟云学术

A Multi - Task Learning Model for Super Resolution of Wireless Channel Characteristics

Author:

Wang Xiping¹,Zhang Zhao¹,He Danping¹,Guan Ke¹,Liu Dongliang²,Dou Jianwu²,Mumtaz Shahid³,Al-Rubaye Saba⁴

Affiliation:

1. Beijing Jiaotong University,State Key Laboratory of Rail Traffic Control and Safety,Beijing,China,100044

2. State Key Laboratory of Mobile Network and Mobile Multimedia Technology,Shenzhen,China,518055

3. Instituto de Telecomunicações,Aveiro,Portugal,1049-001

4. School of Aerospace, Transport and Manufacturing, Cranfield University, Central Bedfordshire,Cranfield,UK,2717

Funder

Fundamental Research Funds for the Central Universities

National Science Foundation of China

Beijing Natural Science Foundation

State Key Laboratory of Rail Traffic Control and Safety

Publisher

IEEE

Link

Reference19 articles.

2. Radionet: Transformer based radio map prediction model for dense urban environments;tian;ar Xiv preprint,2021

4. Multi-task learning with dynamic splitting for open-set wireless signal recognition;xu;ZTE Communications,2022

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