IEEE AP-S/URSI 2023 || Portland, Oregon, USA || 23-28 July 2023

TU-A4.2A.3

Prediction of indoor radio propagation using deep neural network

Takayuki Nakanishi, Kenya Shimizu, Mitsubishi Electric Corporation, Japan; Kenzaburo Hitomi, Mitsubishi Electric Engineering Company Limited, Japan; Yasuhiro Nishioka, Yoshio Inasawa, Mitsubishi Electric Corporation, Japan

Session:

Propagation Modeling and Field Prediction

Track:

AP-S: Propagation & Scattering

Location:

C 124 (OCC)

Session Time:

Tue, 25 Jul, 08:00 - 11:40 PDT (UTC -8)

Presentation Time:

Tue, 25 Jul, 08:40 - 09:00 PDT (UTC -8)

Session Chair:

Costas Sarris, University of Toronto

Session TU-A4.2A

TU-A4.2A.1: Ray Tracing Prediction for 5G Propagation Characteristics in a Modern Office Environment

Chang Liu, Durham University, United Kingdom; Mohamed Ghaddar, Princeton University, United States; mourad Nedil, University of Quebec, Canada; ISMAIL BEN MABROUK, Durham University, United Kingdom

TU-A4.2A.2: Hybrid PO Method in Beam Tracing for Wireless Channel Simulation

Yuxuan Li, Yifan Wu, Xirun Yin, Lizhen Yang, Hai Lin, Zhejiang University, China

TU-A4.2A.3: Prediction of indoor radio propagation using deep neural network

TU-A4.2A.4: A Graph Neural Network-Based Electric-Field Prediction Model for Exposure Assessments

Sen Liu, Teruo Onishi, Masao Taki, Soichi Watanabe, NICT, Japan

TU-A4.2A.5: Path Loss Analysis for Array Antenna systems in underground mine at 3.5GHz

SAIF EDDINE HADJI, Mourad Nedil, Mohamed Lamine Seddiki, UQAT, Canada; Ismail Ben Mabrouk, Durham university, United Kingdom

TU-A4.2A.6: Deep Learning-Based Path Loss Prediction with Satellite Maps

Chenlong Wang, Bo Ai, Ruisi He, Mi Yang, Zhengyu Zhang, Yuxin Zhang, Zhangdui Zhong, Beijing Jiaotong University, China

TU-A4.2A.7: Simplifying Building Structures for Efficient Radio Propagation Modeling

Zhengqing Yun, Magdy Iskander, University of Hawaii, United States

TU-A4.2A.8: Numerical Modeling and Experimental Validation of Path Loss in Realistic RIS-Enabled Links

Yuanzhi Liu, Ziqi Liu, Sean Hum, Costas Sarris, University of Toronto, Canada

TU-A4.2A.9: Propagation Modeling for Indoor Wireless Channels in High-Speed Train

Ruiqi Yang, Siyu Lin, Beijing Jiaotong University, China

TU-A4.2A.10: Modeling of Electromagnetic Wave Phase Front Aberration in Rain

Behzad Yektakhah, Kamal Sarabandi, University of Michigan, United States

IEEE International Symposium on Antennas and Propagation and USNC-URSI Radio Science Meeting

July 23–28, 2023 • Portland, Oregon, USA

Prediction of indoor radio propagation using deep neural network