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008181129s2018 |||||||||||||||||c||eng d
020 ▼a 9780438169005
035 ▼a (MiAaPQ)AAI10824660
035 ▼a (MiAaPQ)ucsd:17493
040 ▼a MiAaPQ ▼c MiAaPQ ▼d 248032
0820 ▼a 621.3
1001 ▼a Ding, Yacong.
24510 ▼a Channel Estimation for Massive MIMO Systems Based on Sparse Representation and Sparse Signal Recovery.
260 ▼a [S.l.] : ▼b University of California, San Diego., ▼c 2018
260 1 ▼a Ann Arbor : ▼b ProQuest Dissertations & Theses, ▼c 2018
300 ▼a 194 p.
500 ▼a Source: Dissertation Abstracts International, Volume: 79-12(E), Section: B.
500 ▼a Adviser: Bhaskar D. Rao.
5021 ▼a Thesis (Ph.D.)--University of California, San Diego, 2018.
520 ▼a 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
520 ▼a 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
590 ▼a School code: 0033.
650 4 ▼a Electrical engineering.
690 ▼a 0544
71020 ▼a University of California, San Diego. ▼b Electrical Engineering (Communication Theory and Systems).
7730 ▼t Dissertation Abstracts International ▼g 79-12B(E).
773 ▼t Dissertation Abstract International
790 ▼a 0033
791 ▼a Ph.D.
792 ▼a 2018
793 ▼a English
85640 ▼u http://www.riss.kr/pdu/ddodLink.do?id=T14998690 ▼n KERIS
980 ▼a 201812 ▼f 2019
990 ▼a 관리자