Name
Abstract | ||
|---|---|---|
Massive multiple input multiple output (M-MIMO) is an enabling technology of 5G wireless communication. The performance of an M-MIMO system is highly dependent on the speed and accuracy of obtaining the channel-state information. The computational complexity of channel estimation for an M-MIMO system can be reduced by making use of the sparsity of the M-MIMO channel. In this paper, we propose the ... |
Year | DOI | Venue |
|---|---|---|
2018 | 10.1109/TCSI.2018.2869783 | IEEE Transactions on Circuits and Systems I: Regular Papers |
Keywords | Field | DocType |
Channel estimation,Antenna arrays,Hardware,Estimation,5G mobile communication,Training,Approximation algorithms | Preamble,Wireless,Communication channel,Electronic engineering,Gate array,Quantization (signal processing),Mathematics,Computational complexity theory,Estimator,Telecommunications link | Journal |
Volume | Issue | ISSN |
66 | 2 | 1549-8328 |
Citations | PageRank | References |
0 | 0.34 | 1 |
Authors | ||
8 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Xiaozhen Liu | 1 | 0 | 0.34 |
| Jin Sha | 2 | 189 | 21.12 |
| Hongxiang Xie | 3 | 151 | 6.27 |
| Feifei Gao | 4 | 3093 | 212.03 |
| Shi Jin | 5 | 3744 | 274.70 |
| Zaichen Zhang | 6 | 134 | 20.67 |
| xiaohu you | 7 | 2529 | 272.49 |
| Chuan Zhang | 8 | 100 | 13.67 |