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
하이브리드 ARQ 시스템에서 누적 관측 잡음 신호 시퀀스(AONSS) 또는 차동 관찰 잡음 신호 시퀀스(DONSS)를 공식화하기 위해 여러 개의 반복 신호 복제본을 사용함으로써 새로운 데이터 지원 최대 우도(DA ML) SNR 추정 및 블라인드 ML AWGN 채널에 대한 SNR 추정 기법을 제안한다. 기존의 DA ML 추정은 새로운 DA ML 추정의 특별한 경우이며, 제안된 DA ML과 제안된 블라인드 ML SNR 추정 기법 모두 기존 하이브리드 ARQ 방식에 상당한 추가 복잡성을 도입하지 않고도 만족스러운 SNR 추정을 제공할 수 있음이 밝혀졌습니다. . AONSS를 기반으로 일반 결정론적 및 특수 사례로 전통적인 Cramer-Rao 하한(CRLB)을 포함하는 무작위 Cramer-Rao 하한(GCRLB)도 파생됩니다. 마지막으로 수치해석과 시뮬레이션 결과를 통해 제안된 AONSS와 DONSS 기반의 SNR 추정 기법의 적용성을 검증한다.
The copyright of the original papers published on this site belongs to IEICE. Unauthorized use of the original or translated papers is prohibited. See IEICE Provisions on Copyright for details.
부
Qingchun CHEN, Pingzhi FAN, "A Novel SNR Estimation Technique Associated with Hybrid ARQ" in IEICE TRANSACTIONS on Fundamentals,
vol. E92-A, no. 11, pp. 2895-2909, November 2009, doi: 10.1587/transfun.E92.A.2895.
Abstract: By using multiple repeated signal replicas to formulate the accumulative observed noisy signal sequence (AONSS) or the differential observed noisy signal sequence (DONSS) in the hybrid ARQ system, a novel data-aided maximum likelihood (DA ML) SNR estimation and a blind ML SNR estimation technique are proposed for the AWGN channel. It is revealed that the conventional DA ML estimate is a special case of the novel DA ML estimate, and both the proposed DA ML and the proposed blind ML SNR estimation techniques can offer satisfactory SNR estimation without introducing significant additional complexity to the existing hybrid ARQ scheme. Based on the AONSS, both the generalized deterministic and the random Cramer-Rao lower bounds (GCRLBs), which include the traditional Cramer-Rao lower bounds (CRLBs) as special cases, are also derived. Finally, the applicability of the proposed SNR estimation techniques based on the AONSS and the DONSS are validated through numerical analysis and simulation results.
URL: https://global.ieice.org/en_transactions/fundamentals/10.1587/transfun.E92.A.2895/_p
부
@ARTICLE{e92-a_11_2895,
author={Qingchun CHEN, Pingzhi FAN, },
journal={IEICE TRANSACTIONS on Fundamentals},
title={A Novel SNR Estimation Technique Associated with Hybrid ARQ},
year={2009},
volume={E92-A},
number={11},
pages={2895-2909},
abstract={By using multiple repeated signal replicas to formulate the accumulative observed noisy signal sequence (AONSS) or the differential observed noisy signal sequence (DONSS) in the hybrid ARQ system, a novel data-aided maximum likelihood (DA ML) SNR estimation and a blind ML SNR estimation technique are proposed for the AWGN channel. It is revealed that the conventional DA ML estimate is a special case of the novel DA ML estimate, and both the proposed DA ML and the proposed blind ML SNR estimation techniques can offer satisfactory SNR estimation without introducing significant additional complexity to the existing hybrid ARQ scheme. Based on the AONSS, both the generalized deterministic and the random Cramer-Rao lower bounds (GCRLBs), which include the traditional Cramer-Rao lower bounds (CRLBs) as special cases, are also derived. Finally, the applicability of the proposed SNR estimation techniques based on the AONSS and the DONSS are validated through numerical analysis and simulation results.},
keywords={},
doi={10.1587/transfun.E92.A.2895},
ISSN={1745-1337},
month={November},}
부
TY - JOUR
TI - A Novel SNR Estimation Technique Associated with Hybrid ARQ
T2 - IEICE TRANSACTIONS on Fundamentals
SP - 2895
EP - 2909
AU - Qingchun CHEN
AU - Pingzhi FAN
PY - 2009
DO - 10.1587/transfun.E92.A.2895
JO - IEICE TRANSACTIONS on Fundamentals
SN - 1745-1337
VL - E92-A
IS - 11
JA - IEICE TRANSACTIONS on Fundamentals
Y1 - November 2009
AB - By using multiple repeated signal replicas to formulate the accumulative observed noisy signal sequence (AONSS) or the differential observed noisy signal sequence (DONSS) in the hybrid ARQ system, a novel data-aided maximum likelihood (DA ML) SNR estimation and a blind ML SNR estimation technique are proposed for the AWGN channel. It is revealed that the conventional DA ML estimate is a special case of the novel DA ML estimate, and both the proposed DA ML and the proposed blind ML SNR estimation techniques can offer satisfactory SNR estimation without introducing significant additional complexity to the existing hybrid ARQ scheme. Based on the AONSS, both the generalized deterministic and the random Cramer-Rao lower bounds (GCRLBs), which include the traditional Cramer-Rao lower bounds (CRLBs) as special cases, are also derived. Finally, the applicability of the proposed SNR estimation techniques based on the AONSS and the DONSS are validated through numerical analysis and simulation results.
ER -