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
본 논문에서는 OFDM(Orthogonal Frequency Division Multiplexing) 이동통신에서 EM(expectation-maximization) 알고리즘을 기반으로 신호 검출과 채널 추정의 공동 처리를 위한 새로운 접근 방식을 제안합니다. EM 알고리즘을 기반으로 하는 기존 기법들은 칼만 필터(Kalman filter)를 이용하여 채널 임펄스 응답을 추정하고, 필터에 대한 처리 방정식을 도출하기 위해 랜덤 워크(Random Walk) 모델이나 AR(First-Order Autoregressive) 모델을 사용합니다. 이러한 모델은 자기상관 특성을 고려하지 않고 임펄스 응답의 시간 변화를 백색 잡음으로 가정하기 때문에 빠른 페이딩 조건에서 채널 추정의 정확도가 저하되어 PER(패킷 오류율)이 증가합니다. 고속 페이딩 채널 추정의 정확도를 향상시키기 위해 제안된 방식은 채널 임펄스 응답의 XNUMX차 및 고차 시간 미분을 도입하여 상관된 시간 변화를 고려할 수 있는 미분 모델을 사용합니다. 또한 본 논문에서는 계산 복잡도를 줄이기 위해 주파수 축과 시간 축 모두를 따라 순방향 재귀 형태의 채널 추정을 유도합니다. 빠른 다중 경로 페이딩 조건에서 채널의 컴퓨터 시뮬레이션은 제안된 방법이 랜덤 워크 모델을 사용하는 기존 방식보다 PER이 우수하다는 것을 보여줍니다.
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부
Kazushi MURAOKA, Kazuhiko FUKAWA, Hiroshi SUZUKI, Satoshi SUYAMA, "Joint Signal Detection and Channel Estimation Using Differential Models via EM Algorithm for OFDM Mobile Communications" in IEICE TRANSACTIONS on Communications,
vol. E94-B, no. 2, pp. 533-545, February 2011, doi: 10.1587/transcom.E94.B.533.
Abstract: This paper proposes a new approach for the joint processing of signal detection and channel estimation based on the expectation-maximization (EM) algorithm in orthogonal frequency division multiplexing (OFDM) mobile communications. Conventional schemes based on the EM algorithm estimate a channel impulse response using Kalman filter, and employ the random walk model or the first-order autoregressive (AR) model to derive the process equation for the filter. Since these models assume that the time-variation of the impulse response is white noise without considering any autocorrelation property, the accuracy of the channel estimation deteriorates under fast-fading conditions, resulting in an increased packet error rate (PER). To improve the accuracy of the estimation of fast-fading channels, the proposed scheme employs a differential model that allows the correlated time-variation to be considered by introducing the first- and higher-order time differentials of the channel impulse response. In addition, this paper derives a forward recursive form of the channel estimation along both the frequency and time axes in order to reduce the computational complexity. Computer simulations of channels under fast multipath fading conditions demonstrate that the proposed method is superior in PER to the conventional schemes that employ the random walk model.
URL: https://global.ieice.org/en_transactions/communications/10.1587/transcom.E94.B.533/_p
부
@ARTICLE{e94-b_2_533,
author={Kazushi MURAOKA, Kazuhiko FUKAWA, Hiroshi SUZUKI, Satoshi SUYAMA, },
journal={IEICE TRANSACTIONS on Communications},
title={Joint Signal Detection and Channel Estimation Using Differential Models via EM Algorithm for OFDM Mobile Communications},
year={2011},
volume={E94-B},
number={2},
pages={533-545},
abstract={This paper proposes a new approach for the joint processing of signal detection and channel estimation based on the expectation-maximization (EM) algorithm in orthogonal frequency division multiplexing (OFDM) mobile communications. Conventional schemes based on the EM algorithm estimate a channel impulse response using Kalman filter, and employ the random walk model or the first-order autoregressive (AR) model to derive the process equation for the filter. Since these models assume that the time-variation of the impulse response is white noise without considering any autocorrelation property, the accuracy of the channel estimation deteriorates under fast-fading conditions, resulting in an increased packet error rate (PER). To improve the accuracy of the estimation of fast-fading channels, the proposed scheme employs a differential model that allows the correlated time-variation to be considered by introducing the first- and higher-order time differentials of the channel impulse response. In addition, this paper derives a forward recursive form of the channel estimation along both the frequency and time axes in order to reduce the computational complexity. Computer simulations of channels under fast multipath fading conditions demonstrate that the proposed method is superior in PER to the conventional schemes that employ the random walk model.},
keywords={},
doi={10.1587/transcom.E94.B.533},
ISSN={1745-1345},
month={February},}
부
TY - JOUR
TI - Joint Signal Detection and Channel Estimation Using Differential Models via EM Algorithm for OFDM Mobile Communications
T2 - IEICE TRANSACTIONS on Communications
SP - 533
EP - 545
AU - Kazushi MURAOKA
AU - Kazuhiko FUKAWA
AU - Hiroshi SUZUKI
AU - Satoshi SUYAMA
PY - 2011
DO - 10.1587/transcom.E94.B.533
JO - IEICE TRANSACTIONS on Communications
SN - 1745-1345
VL - E94-B
IS - 2
JA - IEICE TRANSACTIONS on Communications
Y1 - February 2011
AB - This paper proposes a new approach for the joint processing of signal detection and channel estimation based on the expectation-maximization (EM) algorithm in orthogonal frequency division multiplexing (OFDM) mobile communications. Conventional schemes based on the EM algorithm estimate a channel impulse response using Kalman filter, and employ the random walk model or the first-order autoregressive (AR) model to derive the process equation for the filter. Since these models assume that the time-variation of the impulse response is white noise without considering any autocorrelation property, the accuracy of the channel estimation deteriorates under fast-fading conditions, resulting in an increased packet error rate (PER). To improve the accuracy of the estimation of fast-fading channels, the proposed scheme employs a differential model that allows the correlated time-variation to be considered by introducing the first- and higher-order time differentials of the channel impulse response. In addition, this paper derives a forward recursive form of the channel estimation along both the frequency and time axes in order to reduce the computational complexity. Computer simulations of channels under fast multipath fading conditions demonstrate that the proposed method is superior in PER to the conventional schemes that employ the random walk model.
ER -