Distributed Optimization of Multiuser MIMO Relay Network Using Backpropagation Algorithm

This paper studies a multiuser multi-input multi-output (MIMO) relay network, where the transmit nodes and the relay nodes are subject to the nonlinear instantaneous power constraints. We introduce a perspective of regarding a relay network as a so-termed quasi-neural network by drawing its striking...

Celý popis

Uloženo v:
Podrobná bibliografie
Vydáno v:Conference record - Asilomar Conference on Signals, Systems, & Computers s. 1205 - 1209
Hlavní autoři: Wang, Rui, Jiang, Yi
Médium: Konferenční příspěvek
Jazyk:angličtina
Vydáno: IEEE 31.10.2021
Témata:
Artificial neural networks
Backpropagation
backpropagation algorithm
Interference
interference suppression
nonlinear amplify-and-forward
Numerical simulation
quasi-neural network
relay network
Relay networks (telecommunication)
Training
Transceivers
ISSN:2576-2303
On-line přístup:Získat plný text
Tagy: Přidat tag
Žádné tagy, Buďte první, kdo vytvoří štítek k tomuto záznamu!
Popis
Shrnutí:This paper studies a multiuser multi-input multi-output (MIMO) relay network, where the transmit nodes and the relay nodes are subject to the nonlinear instantaneous power constraints. We introduce a perspective of regarding a relay network as a so-termed quasi-neural network by drawing its striking analogies to a (four-layer) artificial neural network (ANN) and propose a distributed scheme inspired by the backpropagation (BP) algorithm to optimize the transceivers. Using a crafty design of training sequences, the proposed scheme can be implemented with no channel state information (CSI) and no data exchange between the relay nodes. Numerical simulations verify the effectiveness of the proposed scheme. More important, it can suppress interferences from unknown directions.
ISSN:2576-2303
DOI:10.1109/IEEECONF53345.2021.9723157