Learnable binary MIMO detection with negative penalty based on inexact ADMM
Abstract 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 ba...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
Wiley
2024-03-01
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| Series: | Electronics Letters |
| Subjects: | |
| Online Access: | https://doi.org/10.1049/ell2.13155 |
| Summary: | Abstract 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. |
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| ISSN: | 0013-5194 1350-911X |