A Distributed MIMO Relay Scheme Inspired by Backpropagation Algorithm

• Published in: 2021 IEEE Global Communications Conference (GLOBECOM) pp. 1 - 6
• Main Authors: Wang, Rui, Jiang, Yi, Zhang, Wei
• Format: Conference Proceeding
• Language: English
• Published: IEEE 01.12.2021
• Subjects: Artificial neural networks; back-propagation algorithm; Distributed databases; Global communication; Interference; interference suppression; nonlinear amplify-and-forward; Power amplifiers; quasi-neural network; relay network; Relay networks (telecommunication); Transceivers
• DOI: 10.1109/GLOBECOM46510.2021.9685608

This paper studies a distributed scheme for a multi-input multi-output (MIMO) relay network, where the transmit nodes are subject to the nonlinear instantaneous power constraints. We introduce a novel perspective of regarding a relay network as a so-termed quasi-neural network by drawing its striking analogies with a (four-layer) artificial neural network (ANN). We propose a nonlinear amplify-and-forward (NAF) scheme inspired by the back-propagation (BP) algorithm, namely the NAF-BP, to optimize the transceivers to maximize the output signal-to-interference-plus-noise ratio (SINR) of the data streams. The NAF-BP algorithm can be implemented in a distributed manner with no channel state information (CSI) and no data exchange between the relay nodes. The NAF-BP can also coordinate the distributed relay nodes to form a virtual array to suppress interferences from unknown directions. Extensive simulations verify the effectiveness of the proposed scheme.