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Pilot-aided adaptive prediction channel estimation is proposed for coherent detection in a frequency-nonselective fading channel. It is an extension of the conventional weighted multi-slot averaging (WMSA) channel estimation and consists of 3 steps. A block of *N*_{p} pilot symbols is periodically transmitted, each pilot block being followed by *N*_{d} data symbols to form a data slot. In the first step, the instantaneous channel gain is estimated by coherent addition of *N*_{p} pilot symbols. Using the *K* past and *K* future estimated instantaneous channel gains, the second step predicts the instantaneous channel gains at the end and beginning of data slot of interest by a forward predictor and a backward predictor, respectively. The tap-weights of forward prediction and backward prediction are adaptively updated using the normalized least mean square (NLMS) algorithm. Finally, in the third step, the instantaneous channel gain at each data symbol position within the data slot of interest is estimated by simple averaging or linear interpolation using the two adaptively predicted instantaneous channel gains. The computer simulation confirms that the proposed adaptive prediction channel estimation achieves better bit error rate (BER) performance than the conventional WMSA channel estimation in a fast fading channel and/or in the presence of frequency offset between a transmitter and a receiver.

- Publication
- IEICE TRANSACTIONS on Communications Vol.E85-B No.8 pp.1552-1560

- Publication Date
- 2002/08/01

- Publicized

- Online ISSN

- DOI

- Type of Manuscript
- PAPER

- Category
- Terrestrial Radio Communications

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Shinsuke TAKAOKA, Fumiyuki ADACHI, "Pilot-Aided Adaptive Prediction Channel Estimation in a Frequency-Nonselective Fading Channel" in IEICE TRANSACTIONS on Communications,
vol. E85-B, no. 8, pp. 1552-1560, August 2002, doi: .

Abstract: Pilot-aided adaptive prediction channel estimation is proposed for coherent detection in a frequency-nonselective fading channel. It is an extension of the conventional weighted multi-slot averaging (WMSA) channel estimation and consists of 3 steps. A block of *N*_{p} pilot symbols is periodically transmitted, each pilot block being followed by *N*_{d} data symbols to form a data slot. In the first step, the instantaneous channel gain is estimated by coherent addition of *N*_{p} pilot symbols. Using the *K* past and *K* future estimated instantaneous channel gains, the second step predicts the instantaneous channel gains at the end and beginning of data slot of interest by a forward predictor and a backward predictor, respectively. The tap-weights of forward prediction and backward prediction are adaptively updated using the normalized least mean square (NLMS) algorithm. Finally, in the third step, the instantaneous channel gain at each data symbol position within the data slot of interest is estimated by simple averaging or linear interpolation using the two adaptively predicted instantaneous channel gains. The computer simulation confirms that the proposed adaptive prediction channel estimation achieves better bit error rate (BER) performance than the conventional WMSA channel estimation in a fast fading channel and/or in the presence of frequency offset between a transmitter and a receiver.

URL: https://global.ieice.org/en_transactions/communications/10.1587/e85-b_8_1552/_p

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@ARTICLE{e85-b_8_1552,

author={Shinsuke TAKAOKA, Fumiyuki ADACHI, },

journal={IEICE TRANSACTIONS on Communications},

title={Pilot-Aided Adaptive Prediction Channel Estimation in a Frequency-Nonselective Fading Channel},

year={2002},

volume={E85-B},

number={8},

pages={1552-1560},

abstract={Pilot-aided adaptive prediction channel estimation is proposed for coherent detection in a frequency-nonselective fading channel. It is an extension of the conventional weighted multi-slot averaging (WMSA) channel estimation and consists of 3 steps. A block of *N*_{p} pilot symbols is periodically transmitted, each pilot block being followed by *N*_{d} data symbols to form a data slot. In the first step, the instantaneous channel gain is estimated by coherent addition of *N*_{p} pilot symbols. Using the *K* past and *K* future estimated instantaneous channel gains, the second step predicts the instantaneous channel gains at the end and beginning of data slot of interest by a forward predictor and a backward predictor, respectively. The tap-weights of forward prediction and backward prediction are adaptively updated using the normalized least mean square (NLMS) algorithm. Finally, in the third step, the instantaneous channel gain at each data symbol position within the data slot of interest is estimated by simple averaging or linear interpolation using the two adaptively predicted instantaneous channel gains. The computer simulation confirms that the proposed adaptive prediction channel estimation achieves better bit error rate (BER) performance than the conventional WMSA channel estimation in a fast fading channel and/or in the presence of frequency offset between a transmitter and a receiver.},

keywords={},

doi={},

ISSN={},

month={August},}

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TY - JOUR

TI - Pilot-Aided Adaptive Prediction Channel Estimation in a Frequency-Nonselective Fading Channel

T2 - IEICE TRANSACTIONS on Communications

SP - 1552

EP - 1560

AU - Shinsuke TAKAOKA

AU - Fumiyuki ADACHI

PY - 2002

DO -

JO - IEICE TRANSACTIONS on Communications

SN -

VL - E85-B

IS - 8

JA - IEICE TRANSACTIONS on Communications

Y1 - August 2002

AB - Pilot-aided adaptive prediction channel estimation is proposed for coherent detection in a frequency-nonselective fading channel. It is an extension of the conventional weighted multi-slot averaging (WMSA) channel estimation and consists of 3 steps. A block of *N*_{p} pilot symbols is periodically transmitted, each pilot block being followed by *N*_{d} data symbols to form a data slot. In the first step, the instantaneous channel gain is estimated by coherent addition of *N*_{p} pilot symbols. Using the *K* past and *K* future estimated instantaneous channel gains, the second step predicts the instantaneous channel gains at the end and beginning of data slot of interest by a forward predictor and a backward predictor, respectively. The tap-weights of forward prediction and backward prediction are adaptively updated using the normalized least mean square (NLMS) algorithm. Finally, in the third step, the instantaneous channel gain at each data symbol position within the data slot of interest is estimated by simple averaging or linear interpolation using the two adaptively predicted instantaneous channel gains. The computer simulation confirms that the proposed adaptive prediction channel estimation achieves better bit error rate (BER) performance than the conventional WMSA channel estimation in a fast fading channel and/or in the presence of frequency offset between a transmitter and a receiver.

ER -