Low-complexity Neural Network-based MIMO Detector using Permuted Diagonal Matrix
Siyu Liao, Chunhua Deng, Yi Xie, Lingjia Liu, Bo Yuan · 2020
DNN has achieved state-of-the-art performance in MIMO detection problem. However, the deep and large model is hard to deploy to resource constrained platforms. In this work, we propose to provide a sparse DNN model for MIMO detection using permuted diagonal matrices. As a result, our model is with low complexity and doesn't have indexing overhead like other sparsity method. Experiment shows that our method can achieve high sparsity while maintaining the model performance.