Name
Abstract | ||
|---|---|---|
Orthogonal time frequency space (OTFS) modulation, collaborated with millimeter-wave (mmWave) massive multiple-input-multiple-output (MIMO), is a promising technology for next generation wireless communications in high mobility scenarios. However, one of the main challenges for mmWave massive MIMO-OTFS systems is the enormous computational complexity of channel estimation incurred by the huge OTFS symbol size and the large number of antennas. To address this issue, in this paper, a tensor-based orthogonal matching pursuit (OMP) channel estimation algorithm is proposed by exploiting the channel sparsity in the delay-Doppler-angle domain. In particular, we firstly propose a novel pilot design for the OTFS symbol structure in the frequency-time domain. Then, based on the proposed pilot structure, we formulate the channel estimation as a sparse signal recovery problem, and the tensor decomposition and parallel support detection are introduced into the tensor-based OMP algorithm to reduce the signal processing dimension significantly. Numerical simulations are performed to verify the superiority and the robustness of the proposed tensor-based OMP algorithm. |
Year | DOI | Venue |
|---|---|---|
2020 | 10.23919/JCIN.2020.9200896 | Journal of Communications and Information Networks |
Keywords | DocType | Volume |
Channel estimation,OFDM,Matching pursuit algorithms,Time-frequency analysis,Modulation,MIMO communication | Journal | 5 |
Issue | ISSN | Citations |
3 | 2096-1081 | 2 |
PageRank | References | Authors |
0.36 | 0 | 3 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Xianda Wu | 1 | 2 | 0.36 |
| Shaodan Ma | 2 | 666 | 71.25 |
| Xi Yang | 3 | 2 | 0.36 |