Enhanced Deep Learning for Massive MIMO Detection Using Approximate Matrix Inversion
Author:
Affiliation:
1. University of Sharjah,Department of Electrical Engineering,Sharjah,United Arab Emirates
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/10018924/10018967/10019100.pdf?arnumber=10019100
Reference17 articles.
1. Lattice-reduction-aided detectors for MIMO communication systems;yao;Global Telecommunications Conference 2002 GLOBECOM'02 IEEE,2002
2. A Review to Massive MIMO Detection Algorithms: Theory and Implementation
3. Efficient architecture for soft-output massive MIMO detection with Gauss-Seidel method
4. On Improving Gauss-Seidel Iteration for Signal Detection in Uplink Multiuser Massive MIMO Systems
5. QuaDRiGa: A 3-D Multi-Cell Channel Model With Time Evolution for Enabling Virtual Field Trials
Cited by 1 articles. 订阅此论文施引文献 订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献
1. Massive MIMO Detectors Based on Deep Learning, Stair Matrix, and Approximate Matrix Inversion Methods;IEEE Access;2023
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