Learnable binary MIMO detection with negative penalty based on inexact ADMM

초록

In this letter, a new learnable binary MIMO detection algorithm in massive MIMO systems with one-bit analog-to-digital converters is proposed. A negative penalty is introduced to transform a non-convex constraint to a convex box constraint and a learnable iterative algorithm is presented based on inexact alternating direction methods of multipliers. The proposed MIMO detection method performs better than the existing binary MIMO detection methods even with lower computational complexity. The letter introduces a novel binary MIMO detection algorithm for massive MIMO systems using one-bit analog-to-digital converters. It employs a negative penalty to make a non-convex constraint convex and presents a learnable iterative algorithm based on inexact alternating direction methods of multipliers. This new method outperforms existing binary MIMO detection techniques while maintaining significantly lower computational complexity. image

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