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Channel Estimation for Massive MIMO Systems Based on Sparse Representation and Sparse Signal Recovery
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| 자료유형 | 학위논문 |
|---|---|
| 서명/저자사항 | Channel Estimation for Massive MIMO Systems Based on Sparse Representation and Sparse Signal Recovery. |
| 개인저자 | Ding, Yacong. |
| 단체저자명 | University of California, San Diego. Electrical Engineering (Communication Theory and Systems). |
| 발행사항 | [S.l.]: University of California, San Diego., 2018. |
| 발행사항 | Ann Arbor: ProQuest Dissertations & Theses, 2018. |
| 형태사항 | 194 p. |
| 기본자료 저록 | Dissertation Abstracts International 79-12B(E). Dissertation Abstract International |
| ISBN | 9780438169005 |
| 학위논문주기 | Thesis (Ph.D.)--University of California, San Diego, 2018. |
| 일반주기 |
Source: Dissertation Abstracts International, Volume: 79-12(E), Section: B.
Adviser: Bhaskar D. Rao. |
| 요약 | Massive multiple-input multiple-output (MIMO) is a promising technology for next generation communication systems, where the base station (BS) is equipped with a large number of antenna elements to serve multiple user equipments. With the large |
| 요약 | To reduce the training and feedback overhead, compressive sensing methods and sparse recovery algorithms are proposed to robustly estimate the downlink and uplink channel by exploiting the sparse representation of the massive MIMO channel. Previ |
| 일반주제명 | Electrical engineering. |
| 언어 | 영어 |
| 바로가기 | 
: 이 자료의 원문은 한국교육학술정보원에서 제공합니다. |
