The original paper is in English. Non-English content has been machine-translated and may contain typographical errors or mistranslations. ex. Some numerals are expressed as "XNUMX".
Copyrights notice
The original paper is in English. Non-English content has been machine-translated and may contain typographical errors or mistranslations. Copyrights notice
이 문서에서는 대규모 MIMO(다중 입력 다중 출력) 업링크의 파일럿 오염을 다룹니다. 파일럿 오염은 인접한 셀에서 동일한 파일럿 시퀀스를 재사용하여 발생합니다. 파일럿 오염을 해결하기 위해 기지국은 공동 채널 및 데이터 추정을 통해 감지되는 서로 다른 사용자의 전송 프레임 간의 차이를 활용합니다. 결합 추정은 압축 감지에서 이중선형 추론 문제로 간주됩니다. EP(Expectation Propagation)는 반복 채널 및 데이터 추정 알고리즘을 제안하는 데 사용됩니다. 대규모 페이딩에 대한 정보를 활용하지 않고 시간 이동 파일럿을 통해 초기 채널 추정치를 얻습니다. 제안된 EP는 기존 BAd-VAMP(Bilinear Adaptive Vector Approximation Message-Passing)의 두 가지 점을 수정합니다. 하나는 EP가 채널 추정에서 연판정 후의 데이터 추정을 활용하는 반면, BAd-VAMP는 연판정 전의 데이터 추정을 사용한다는 점이다. 또 다른 요점은 EP가 채널 매트릭스의 사전 분포를 활용할 수 있는 반면 BAd-VAMP는 원칙적으로 사용할 수 없다는 것입니다. 수치 시뮬레이션은 공간적으로 상관된 MIMO에서 EP가 BAd-VAMP보다 훨씬 빠르게 수렴한다는 것을 보여줍니다. 여기서 대략적인 메시지 전달은 EP 및 BAd-VAMP와 동일한 고정 소수점으로 수렴하지 못합니다.
Wataru TATSUNO
Toyohashi University of Technology
Keigo TAKEUCHI
Toyohashi University of Technology
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Wataru TATSUNO, Keigo TAKEUCHI, "Pilot Decontamination in Spatially Correlated Massive MIMO Uplink via Expectation Propagation" in IEICE TRANSACTIONS on Fundamentals,
vol. E104-A, no. 4, pp. 723-733, April 2021, doi: 10.1587/transfun.2020EAP1073.
Abstract: This paper addresses pilot contamination in massive multiple-input multiple-output (MIMO) uplink. Pilot contamination is caused by reuse of identical pilot sequences in adjacent cells. To solve pilot contamination, the base station utilizes differences between the transmission frames of different users, which are detected via joint channel and data estimation. The joint estimation is regarded as a bilinear inference problem in compressed sensing. Expectation propagation (EP) is used to propose an iterative channel and data estimation algorithm. Initial channel estimates are attained via time-shifted pilots without exploiting information about large scale fading. The proposed EP modifies two points in conventional bilinear adaptive vector approximate message-passing (BAd-VAMP). One is that EP utilizes data estimates after soft decision in the channel estimation while BAd-VAMP uses them before soft decision. The other point is that EP can utilize the prior distribution of the channel matrix while BAd-VAMP cannot in principle. Numerical simulations show that EP converges much faster than BAd-VAMP in spatially correlated MIMO, in which approximate message-passing fails to converge toward the same fixed-point as EP and BAd-VAMP.
URL: https://global.ieice.org/en_transactions/fundamentals/10.1587/transfun.2020EAP1073/_p
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@ARTICLE{e104-a_4_723,
author={Wataru TATSUNO, Keigo TAKEUCHI, },
journal={IEICE TRANSACTIONS on Fundamentals},
title={Pilot Decontamination in Spatially Correlated Massive MIMO Uplink via Expectation Propagation},
year={2021},
volume={E104-A},
number={4},
pages={723-733},
abstract={This paper addresses pilot contamination in massive multiple-input multiple-output (MIMO) uplink. Pilot contamination is caused by reuse of identical pilot sequences in adjacent cells. To solve pilot contamination, the base station utilizes differences between the transmission frames of different users, which are detected via joint channel and data estimation. The joint estimation is regarded as a bilinear inference problem in compressed sensing. Expectation propagation (EP) is used to propose an iterative channel and data estimation algorithm. Initial channel estimates are attained via time-shifted pilots without exploiting information about large scale fading. The proposed EP modifies two points in conventional bilinear adaptive vector approximate message-passing (BAd-VAMP). One is that EP utilizes data estimates after soft decision in the channel estimation while BAd-VAMP uses them before soft decision. The other point is that EP can utilize the prior distribution of the channel matrix while BAd-VAMP cannot in principle. Numerical simulations show that EP converges much faster than BAd-VAMP in spatially correlated MIMO, in which approximate message-passing fails to converge toward the same fixed-point as EP and BAd-VAMP.},
keywords={},
doi={10.1587/transfun.2020EAP1073},
ISSN={1745-1337},
month={April},}
부
TY - JOUR
TI - Pilot Decontamination in Spatially Correlated Massive MIMO Uplink via Expectation Propagation
T2 - IEICE TRANSACTIONS on Fundamentals
SP - 723
EP - 733
AU - Wataru TATSUNO
AU - Keigo TAKEUCHI
PY - 2021
DO - 10.1587/transfun.2020EAP1073
JO - IEICE TRANSACTIONS on Fundamentals
SN - 1745-1337
VL - E104-A
IS - 4
JA - IEICE TRANSACTIONS on Fundamentals
Y1 - April 2021
AB - This paper addresses pilot contamination in massive multiple-input multiple-output (MIMO) uplink. Pilot contamination is caused by reuse of identical pilot sequences in adjacent cells. To solve pilot contamination, the base station utilizes differences between the transmission frames of different users, which are detected via joint channel and data estimation. The joint estimation is regarded as a bilinear inference problem in compressed sensing. Expectation propagation (EP) is used to propose an iterative channel and data estimation algorithm. Initial channel estimates are attained via time-shifted pilots without exploiting information about large scale fading. The proposed EP modifies two points in conventional bilinear adaptive vector approximate message-passing (BAd-VAMP). One is that EP utilizes data estimates after soft decision in the channel estimation while BAd-VAMP uses them before soft decision. The other point is that EP can utilize the prior distribution of the channel matrix while BAd-VAMP cannot in principle. Numerical simulations show that EP converges much faster than BAd-VAMP in spatially correlated MIMO, in which approximate message-passing fails to converge toward the same fixed-point as EP and BAd-VAMP.
ER -