TY - GEN
T1 - DEEP OPTIMIZATION OF RELAY NETWORKS - USING RELAYS AS NEURONS
AU - Bergel, Itsik
N1 - Publisher Copyright: © 2024 IEEE.
PY - 2024
Y1 - 2024
N2 - We consider the optimization of a network with amplify- and-forward relays. Observing that the power limit at each relay presents a non-linear transfer function, we focus on the similarity between relay networks and neural networks. Thus, we treat relays as neurons, and use deep learning tools to achieve better optimization of the network. Deep learning optimization allows relays to exploit their non-linear regime (and hence increase their transmission power) while still avoiding harmful distortion. Moreover, copying the computational capabilities of neural networks, we can take advantage of the non-linearities and implement parts of the received functionalities over the relay network. By treating each relay element as a node in a deep neural network, our optimization results in huge gains over traditional relay optimization, and also allows the use of simpler receivers.
AB - We consider the optimization of a network with amplify- and-forward relays. Observing that the power limit at each relay presents a non-linear transfer function, we focus on the similarity between relay networks and neural networks. Thus, we treat relays as neurons, and use deep learning tools to achieve better optimization of the network. Deep learning optimization allows relays to exploit their non-linear regime (and hence increase their transmission power) while still avoiding harmful distortion. Moreover, copying the computational capabilities of neural networks, we can take advantage of the non-linearities and implement parts of the received functionalities over the relay network. By treating each relay element as a node in a deep neural network, our optimization results in huge gains over traditional relay optimization, and also allows the use of simpler receivers.
UR - http://www.scopus.com/inward/record.url?scp=85195388435&partnerID=8YFLogxK
U2 - https://doi.org/10.1109/ICASSP48485.2024.10447401
DO - https://doi.org/10.1109/ICASSP48485.2024.10447401
M3 - منشور من مؤتمر
T3 - ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
SP - 9056
EP - 9060
BT - 2024 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2024 - Proceedings
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 49th IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2024
Y2 - 14 April 2024 through 19 April 2024
ER -