Low Complexity Adaptive Channel Estimation and QR Decomposition for an LTE-A Downlink
Gangarajaiah, Rakesh LU ; Nilsson, Peter LU ; Edfors, Ove LU
and Liu, Liang
LU
(2015)
IEEE 25th International Symposium on Personal, Indoor and Mobile Radio Communications (PIMRC), 2014
- Abstract
- This paper presents a link adaptive processor to
perform low-complexity channel estimation and QR decomposition
(QRD) in Long Term Evolution-Advanced (LTE-A) receivers.
The processor utilizes frequency domain correlation of the propagation
channel to adaptively avoid unnecessary computations in
the received signal processing, achieving significant complexity
reduction with negligible performance loss. More specifically, a
windowed Discrete Fourier transform (DFT) algorithm is used to
detect channel conditions and to compute a minimum number of
sparse subcarrier channel estimates required for low complexity
linear QRD interpolation. Furthermore, the... (More) - This paper presents a link adaptive processor to
perform low-complexity channel estimation and QR decomposition
(QRD) in Long Term Evolution-Advanced (LTE-A) receivers.
The processor utilizes frequency domain correlation of the propagation
channel to adaptively avoid unnecessary computations in
the received signal processing, achieving significant complexity
reduction with negligible performance loss. More specifically, a
windowed Discrete Fourier transform (DFT) algorithm is used to
detect channel conditions and to compute a minimum number of
sparse subcarrier channel estimates required for low complexity
linear QRD interpolation. Furthermore, the sparsity of subcarrier
channel estimates can be adaptively changed to handle different
channel conditions. Simulation results demonstrate a reduction
of 40%-80% in computational complexity for different channel
models specified in the LTE-A standard. (Less)
Please use this url to cite or link to this publication:
https://lup.lub.lu.se/record/4469005
- author
- Gangarajaiah, Rakesh
LU
; Nilsson, Peter
LU
; Edfors, Ove
LU
and Liu, Liang
LU
- organization
- publishing date
- 2015-06-29
- type
- Chapter in Book/Report/Conference proceeding
- publication status
- published
- subject
- host publication
- 2014 IEEE 25th Annual International Symposium on Personal, Indoor, and Mobile Radio Communication (PIMRC)
- publisher
- IEEE - Institute of Electrical and Electronics Engineers Inc.
- conference name
- IEEE 25th International Symposium on Personal, Indoor and Mobile Radio Communications (PIMRC), 2014
- conference location
- Washington DC, United States
- conference dates
- 2014-09-02 - 2014-09-05
- external identifiers
-
- scopus:84944317368
- ISBN
- 978-1-4799-4912-0
- DOI
- 10.1109/PIMRC.2014.7136209
- project
- EIT_DARE Digitally-Assisted Radio Evolution
- language
- English
- LU publication?
- yes
- id
- ac870044-57f1-4f5a-bbc0-2f839f99ea61 (old id 4469005)
- date added to LUP
- 2016-04-04 13:13:43
- date last changed
- 2024-03-07 16:32:31
@inproceedings{ac870044-57f1-4f5a-bbc0-2f839f99ea61,
abstract = {{This paper presents a link adaptive processor to<br/><br>
perform low-complexity channel estimation and QR decomposition<br/><br>
(QRD) in Long Term Evolution-Advanced (LTE-A) receivers.<br/><br>
The processor utilizes frequency domain correlation of the propagation<br/><br>
channel to adaptively avoid unnecessary computations in<br/><br>
the received signal processing, achieving significant complexity<br/><br>
reduction with negligible performance loss. More specifically, a<br/><br>
windowed Discrete Fourier transform (DFT) algorithm is used to<br/><br>
detect channel conditions and to compute a minimum number of<br/><br>
sparse subcarrier channel estimates required for low complexity<br/><br>
linear QRD interpolation. Furthermore, the sparsity of subcarrier<br/><br>
channel estimates can be adaptively changed to handle different<br/><br>
channel conditions. Simulation results demonstrate a reduction<br/><br>
of 40%-80% in computational complexity for different channel<br/><br>
models specified in the LTE-A standard.}},
author = {{Gangarajaiah, Rakesh and Nilsson, Peter and Edfors, Ove and Liu, Liang}},
booktitle = {{2014 IEEE 25th Annual International Symposium on Personal, Indoor, and Mobile Radio Communication (PIMRC)}},
isbn = {{978-1-4799-4912-0}},
language = {{eng}},
month = {{06}},
publisher = {{IEEE - Institute of Electrical and Electronics Engineers Inc.}},
title = {{Low Complexity Adaptive Channel Estimation and QR Decomposition for an LTE-A Downlink}},
url = {{https://lup.lub.lu.se/search/files/17264494/8851517.pdf}},
doi = {{10.1109/PIMRC.2014.7136209}},
year = {{2015}},
}