Diffraction and Scattering Aware Radio Map and Environment Reconstruction using Geometry Model-Assisted Deep Learning

arXiv:2403.00229v1 Announce Type: cross
Abstract: Machine learning (ML) facilitates rapid channel modeling for 5G and beyond wireless communication systems. Many existing ML techniques utilize a city map to construct the radio map; however, an updated city map may not always be available. This paper proposes to employ the received signal strength (RSS) data to jointly construct the radio map and the virtual environment by exploiting the geometry structure of the environment. In contrast to many existing ML approaches that lack …

abstract arxiv beyond city communication construct cs.lg deep learning eess.sp environment geometry machine machine learning map modeling paper radio systems type wireless