IEICE TRANSACTIONS on Fundamentals
Data Detection for OFDM Systems with Phase Noise and Channel Estimation Errors Using Variational Inference
Summary :
This paper studies a novel iterative detection algorithm for data detection in orthogonal frequency division multiplexing systems in the presence of phase noise (PHN) and channel estimation errors. By simplifying the maximum a posteriori algorithm based on the theory of variational inference, an optimization problem over variational free energy is formulated. After that, the estimation of data, PHN and channel state information is obtained jointly and iteratively. The simulations indicate the validity of this algorithm and show a better performance compared with the traditional schemes.
- Publication
- IEICE TRANSACTIONS on Fundamentals Vol.E100-A No.4 pp.1037-1044
- Publication Date
- 2017/04/01
- Publicized
- Online ISSN
- 1745-1337
- DOI
- 10.1587/transfun.E100.A.1037
- Type of Manuscript
- PAPER
- Category
- Communication Theory and Signals
Authors
Feng LI
Xi'an Jiaotong University
Shuyuan LI
Xi'an Jiaotong University
Hailin LI
Xi'an Jiaotong University
Keyword
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Feng LI, Shuyuan LI, Hailin LI, "Data Detection for OFDM Systems with Phase Noise and Channel Estimation Errors Using Variational Inference" in IEICE TRANSACTIONS on Fundamentals,
vol. E100-A, no. 4, pp. 1037-1044, April 2017, doi: 10.1587/transfun.E100.A.1037.
Abstract: This paper studies a novel iterative detection algorithm for data detection in orthogonal frequency division multiplexing systems in the presence of phase noise (PHN) and channel estimation errors. By simplifying the maximum a posteriori algorithm based on the theory of variational inference, an optimization problem over variational free energy is formulated. After that, the estimation of data, PHN and channel state information is obtained jointly and iteratively. The simulations indicate the validity of this algorithm and show a better performance compared with the traditional schemes.
URL: https://global.ieice.org/en_transactions/fundamentals/10.1587/transfun.E100.A.1037/_p
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@ARTICLE{e100-a_4_1037,
author={Feng LI, Shuyuan LI, Hailin LI, },
journal={IEICE TRANSACTIONS on Fundamentals},
title={Data Detection for OFDM Systems with Phase Noise and Channel Estimation Errors Using Variational Inference},
year={2017},
volume={E100-A},
number={4},
pages={1037-1044},
abstract={This paper studies a novel iterative detection algorithm for data detection in orthogonal frequency division multiplexing systems in the presence of phase noise (PHN) and channel estimation errors. By simplifying the maximum a posteriori algorithm based on the theory of variational inference, an optimization problem over variational free energy is formulated. After that, the estimation of data, PHN and channel state information is obtained jointly and iteratively. The simulations indicate the validity of this algorithm and show a better performance compared with the traditional schemes.},
keywords={},
doi={10.1587/transfun.E100.A.1037},
ISSN={1745-1337},
month={April},}
Copy
TY - JOUR
TI - Data Detection for OFDM Systems with Phase Noise and Channel Estimation Errors Using Variational Inference
T2 - IEICE TRANSACTIONS on Fundamentals
SP - 1037
EP - 1044
AU - Feng LI
AU - Shuyuan LI
AU - Hailin LI
PY - 2017
DO - 10.1587/transfun.E100.A.1037
JO - IEICE TRANSACTIONS on Fundamentals
SN - 1745-1337
VL - E100-A
IS - 4
JA - IEICE TRANSACTIONS on Fundamentals
Y1 - April 2017
AB - This paper studies a novel iterative detection algorithm for data detection in orthogonal frequency division multiplexing systems in the presence of phase noise (PHN) and channel estimation errors. By simplifying the maximum a posteriori algorithm based on the theory of variational inference, an optimization problem over variational free energy is formulated. After that, the estimation of data, PHN and channel state information is obtained jointly and iteratively. The simulations indicate the validity of this algorithm and show a better performance compared with the traditional schemes.
ER -
English
