Channel Modeling for FR3 Upper Mid-band via Generative Adversarial Networks
Paper i proceeding, 2024

The upper mid-band (FR3) has been recently attracting interest for new generation of mobile networks, as it provides a promising balance between spectrum availability and coverage, which are inherent limitations of the sub 6GHz and millimeter wave bands, respectively. In order to efficiently design and optimize the network, channel modeling plays a key role since FR3 systems are expected to operate at multiple frequency bands. Data-driven methods, especially generative adversarial networks (GANs), can capture the intricate relationships among data samples, and provide an appropriate tool for FR3 channel modeling. In this work, we present the architecture, link state model, and path generative network of GAN-based FR3 channel modeling. The comparison of our model greatly matches the ray-tracing simulated data.

upper mid-band

GANs

FR3

6G

Channel modeling

neural networks

Författare

Yaqi Hu

New York University

Mingsheng Yin

New York University

Marco Mezzavilla

New York University

Hao Guo

New York University

Chalmers, Elektroteknik, Kommunikation, Antenner och Optiska Nätverk

Sundeep Rangan

New York University

IEEE Workshop on Signal Processing Advances in Wireless Communications, SPAWC

23253789 (ISSN)

776-780
9798350393187 (ISBN)

25th IEEE International Workshop on Signal Processing Advances in Wireless Communications, SPAWC 2024
Lucca, Italy,

6G kommunikationsmedveten navigering för robotdirektiv

Vetenskapsrådet (VR) (2023-00272), 2023-07-01 -- 2025-06-30.

Ämneskategorier

Kommunikationssystem

DOI

10.1109/SPAWC60668.2024.10693976

Mer information

Senast uppdaterat

2024-11-06