Joint channel estimation and data detection in MIMO-OFDM using distributed compressive sensing
- 作者: Jomon K.1, Prasanth S.2
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隶属关系:
- IES College of Engineering
- Royal College of Engineering and Technology
- 期: 卷 60, 编号 2 (2017)
- 页面: 80-87
- 栏目: Article
- URL: https://journals.rcsi.science/0735-2727/article/view/177031
- DOI: https://doi.org/10.3103/S0735272717020029
- ID: 177031
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详细
Channel impulse response of a multiple input multiple output-orthogonal frequency division multiplexing (MIMO-OFDM) channel contains a smaller number of nonzero components. In addition, locations of nonzero taps coincide in delay domain. So channel impulse responses can be modeled into an approximately group sparse signals. In this work we use extended sparse Bayesian learning (ESBL), a new method for multichannel compressive sensing for channel estimation in MIMO-OFDM. In joint extended sparse Bayesian learning (JESBL), both pilot and data subcarriers are utilized for channel estimation. These methods can reduce the number of pilot subcarriers in OFDM and improve the spectral efficiency of the MIMO-OFDM system.
作者简介
K. Jomon
IES College of Engineering
编辑信件的主要联系方式.
Email: jomonkcharly@gmail.com
印度, Kerala
S. Prasanth
Royal College of Engineering and Technology
Email: jomonkcharly@gmail.com
印度, Akkikavu