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Learnable MIMO Detection Networks Based on Inexact ADMM

2020-10-01Code Available1· sign in to hype

Minsik Kim, Daeyoung Park

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Abstract

In this article, we present a new iterative MIMO detection algorithm based on inexact alternating direction method of multipliers. Each iteration is considered as a neural network layer with learnable parameters, which are optimized by the stochastic gradient descent algorithm with a training data set of the received vectors and the ground truth transmitted signals. Numerical results show that the proposed algorithm outperforms the existing learnable detection network and it achieves near-optimal performance close to the sphere decoder in the case of a large number of receive antennas.

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