Sparse channel estimation based on compressive sensing kalman filter with limited feedback = 칼만 필터 압축센싱 기반의 피드백을 통한 희소 채널 추정

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In this paper, the adaptive pilot signal sequence design for a large millimeter-wave (mmWave) multiple-input single-output (MISO) downlink channel estimation to minimize normalized mean square error (NMSE) is considered. By developing the sparsity in a large mmWave MISO downlink channel and the time dependency of a virtual channel vector (VCV) sequence, we reformulate designing the training beam sequence and channel estimation problem as the compressive sensing on kalman filter (KF-CS) that finds non-zero entries in a one-dimensional VCV. Under the KF-CS framework, feedback is used for designing optimal adaptive pilot signal sequence in an aspect of minimum mean square error (MMSE) with low computational complexity for a practical issue. To evaluate the performance of the proposed pilot signal design method, simulation results are provided and these shows the proposed method yields the better performance than the KF-CS in channel estimation.
Advisors
Sung, Youngchulresearcher성영철researcher
Description
한국과학기술원 :전기및전자공학과,
Publisher
한국과학기술원
Issue Date
2015
Identifier
325007
Language
eng
Description

학위논문(석사) - 한국과학기술원 : 전기및전자공학과, 2015.2,[iii, 29 p. :]

Keywords

KF-CS▼afeedback▼apilot▼achannel estimation; 칼만 필터 압축센싱▼a피드백▼a파일럿▼a채널 추정

URI
http://hdl.handle.net/10203/266690
Link
http://library.kaist.ac.kr/search/detail/view.do?bibCtrlNo=849300&flag=dissertation
Appears in Collection
EE-Theses_Master(석사논문)
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