TY - GEN
T1 - Channel Modeling for FR3 Upper Mid-band via Generative Adversarial Networks
AU - Hu, Yaqi
AU - Yin, Mingsheng
AU - Mezzavilla, Marco
AU - Guo, Hao
AU - Rangan, Sundeep
N1 - Publisher Copyright:
© 2024 IEEE.
PY - 2024
Y1 - 2024
N2 - 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.
AB - 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.
KW - 6G
KW - Channel modeling
KW - FR3
KW - GANs
KW - neural networks
KW - upper mid-band
UR - http://www.scopus.com/inward/record.url?scp=85207049337&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85207049337&partnerID=8YFLogxK
U2 - 10.1109/SPAWC60668.2024.10693976
DO - 10.1109/SPAWC60668.2024.10693976
M3 - Conference contribution
AN - SCOPUS:85207049337
T3 - IEEE Workshop on Signal Processing Advances in Wireless Communications, SPAWC
SP - 776
EP - 780
BT - 2024 IEEE 25th International Workshop on Signal Processing Advances in Wireless Communications, SPAWC 2024
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 25th IEEE International Workshop on Signal Processing Advances in Wireless Communications, SPAWC 2024
Y2 - 10 September 2024 through 13 September 2024
ER -