Name
Abstract | ||
|---|---|---|
Inspired by the remarkable learning and prediction performance of deep neural networks (DNNs), we apply one special type of DNN framework, known as model-driven deep unfolding neural network, to reconfigurable intelligent surface (RIS)-aided millimeter wave (mmWave) single-input multiple-output (SIMO) systems. We focus on uplink cascaded channel estimation, where known and fixed base station combi... |
Year | DOI | Venue |
|---|---|---|
2022 | 10.1109/LWC.2022.3147250 | IEEE Wireless Communications Letters |
Keywords | DocType | Volume |
Channel estimation,Training,Phase control,MIMO communication,Radio frequency,Optimization,Neural networks | Journal | 11 |
Issue | ISSN | Citations |
4 | 2162-2337 | 1 |
PageRank | References | Authors |
0.34 | 0 | 4 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Jiguang He | 1 | 2 | 1.70 |
| Henk Wymeersch | 2 | 1589 | 128.47 |
| Marco Di Renzo | 3 | 4721 | 269.75 |
| Markku J. Juntti | 4 | 1065 | 127.57 |