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سی و چهارمین کنفرانس بین المللی مهندسی برق
A Model-Driven Deep Learning Approach to Signal Detection in Large-Scale MIMO Systems
نویسندگان :
Nima Kiaheyrati
1
Mojtaba Amiri
2
Ali Olfat
3
1- School of Electrical and Computer Engineering, University of Tehran
2- School of Electrical and Computer Engineering, University of Tehran
3- School of Electrical and Computer Engineering, University of Tehran
کلمات کلیدی :
Massive MIMO،Detection،Deep learning،Iterative algorithm
چکیده :
Massive multiple-input multiple-output (MIMO) has become a technology for next-generation wireless communication systems due to its potential to significantly increase capacity and spectral efficiency. However, efficient signal detection in massive MIMO systems remains a major challenge, particularly when aiming to balance accuracy and computational complexity. In this paper, we propose a new model-driven deep learning architecture for massive MIMO detection, inspired by an iterative framework. For the first time, we define a novel loss function that not only accelerates convergence during training but also improves the overall detection quality. Furthermore, simulation results demonstrate that our detector achieves up to $25\%$ performance improvement compared to state-of-the-art methods.
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بیشتر
ثمین همایش، سامانه مدیریت کنفرانس ها و جشنواره ها - نگارش 44.7.2
