Investigation of QR-RLS based Channel Estimation Techniques for MIMO-OFDM Systems
Krishn Kumar Gupta1 , K. K. Nayak2
Section:Research Paper, Product Type: Journal Paper
Volume-7 ,
Issue-5 , Page no. 1500-1503, May-2019
CrossRef-DOI: https://doi.org/10.26438/ijcse/v7i5.15001503
Online published on May 31, 2019
Copyright © Krishn Kumar Gupta, K. K. Nayak . This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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IEEE Style Citation: Krishn Kumar Gupta, K. K. Nayak, “Investigation of QR-RLS based Channel Estimation Techniques for MIMO-OFDM Systems,” International Journal of Computer Sciences and Engineering, Vol.7, Issue.5, pp.1500-1503, 2019.
MLA Style Citation: Krishn Kumar Gupta, K. K. Nayak "Investigation of QR-RLS based Channel Estimation Techniques for MIMO-OFDM Systems." International Journal of Computer Sciences and Engineering 7.5 (2019): 1500-1503.
APA Style Citation: Krishn Kumar Gupta, K. K. Nayak, (2019). Investigation of QR-RLS based Channel Estimation Techniques for MIMO-OFDM Systems. International Journal of Computer Sciences and Engineering, 7(5), 1500-1503.
BibTex Style Citation:
@article{Gupta_2019,
author = {Krishn Kumar Gupta, K. K. Nayak},
title = {Investigation of QR-RLS based Channel Estimation Techniques for MIMO-OFDM Systems},
journal = {International Journal of Computer Sciences and Engineering},
issue_date = {5 2019},
volume = {7},
Issue = {5},
month = {5},
year = {2019},
issn = {2347-2693},
pages = {1500-1503},
url = {https://www.ijcseonline.org/full_paper_view.php?paper_id=4438},
doi = {https://doi.org/10.26438/ijcse/v7i5.15001503}
publisher = {IJCSE, Indore, INDIA},
}
RIS Style Citation:
TY - JOUR
DO = {https://doi.org/10.26438/ijcse/v7i5.15001503}
UR - https://www.ijcseonline.org/full_paper_view.php?paper_id=4438
TI - Investigation of QR-RLS based Channel Estimation Techniques for MIMO-OFDM Systems
T2 - International Journal of Computer Sciences and Engineering
AU - Krishn Kumar Gupta, K. K. Nayak
PY - 2019
DA - 2019/05/31
PB - IJCSE, Indore, INDIA
SP - 1500-1503
IS - 5
VL - 7
SN - 2347-2693
ER -
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Abstract
Use of multiple antennas at the transmitter and receiver ends called as MIMO has become a very popular technique for improvement of data rates required by the current and future wireless networks. OFDM combined with MIMO is very attractive air interface in mobile and wireless communication scenario. Less complex and reliable channel estimation and detection techniques are required to take advantages offered by MIMO. In this thesis, channel estimation and detection techniques for MIMO and MIMO-OFDM system are studied. In MIMO-OFDM system, the received OFDM symbols can be processed in time domain or frequency domain. The numbers of channel estimation methods for OFDM and MIMO-OFDM system are studied. This research work has implemented a combined time and frequency domain approach to channel estimation for MIMO-OFDM.
Key-Words / Index Term
MIMO-OFDM System, Channel Estimation Technique, Bit Error Rate, Mean Square Error
References
[1] Akhilesh Venkatasubramanian, Krithika. V and Partibane. B, “Channel Estimation For A Multi-User MIMOOFDM- IDMA System”, International Conference on Communication and Signal Processing, April 6-8, 2017, India.
[2] R. Prasad, C. R. Murthy, B. D. Rao, "Joint channel estimation and data detection in MIMO-OFDM systems: A sparse Bayesian learning approach", IEEE Trans. Signal Process., vol. 63, no. 20, pp. 5369-5382, Oct. 2015.
[3] R. Prasad, C. R. Murthy, B. D. Rao, "Joint approximately sparse channel estimation and data detection in OFDM systems using sparse Bayesian learning", IEEE Trans. Signal Process., vol. 62, no. 14, pp. 3591-3603, Jul. 2014.
[4] Mel Li, Xiang Wang and Kun Zhang, “Comparative Study of Adaptive Filter Channel Estimation Technique in MIMO-OFDM System Based on STBC”, Proceedings of the 2014 International Conference on Machine Learning and Cybernetics, Lanzhou, 13-16 July, 2014.
[5] Biswajit Sahoo, Ravi Ranjan Prasad, and P. Samundiswary, “BER Analysis of Mobile WiMAX System using LDPC Coding and MIMO System under Rayleigh Channel”, International conference on Communication and Signal Processing, April 3-5, 2013, India.
[6] Mukesh Patidar, Rupesh Dubey, Nitinkumar Jain and Saritakul Pariya, “Performance Analysis of WiMAX 802.16e Physical Layer Model”, International Conference on wireless communication, 2012 IEEE.
[7] Chin-Liang Wang and Shun-Sheng Wang and Hsiao-Ling Chang, “A Low-Complexity SLM Based PAPR Reduction Scheme for SFBC MIMO-OFDM Systems”, International Conference on Wireless Communication, 2011 IEEE.
[8] Divyang Rawal, Park Youn Ok and C. Vijaykumar, “A Novel training based QR-RLS channel estimator for MIMO OFDM systems”, Wireless Advanced (WiAD), 6th Conference on, IEEE 2010.
[9] Ke Chen and Xiaojing Huang, “A Novel Approach for Interference Suppression in Multi-Sub band Convolutional Coded OFDM System”, School of Electrical, Computer & Telecommunications University of Wollongong, Australia (2010).
[10] Sen-Hung Wang, and Chih-Peng Li, “A Low-Complexity PAPR Reduction Scheme for SFBC MIMO-OFDM Systems”, IEEE Signal Processing Letters, Vol. 16, No. 11, November 2009.
[11] Yang Zhou and Tao Jiang, “A Novel Multi-Points Square Mapping Combined With PTS to Reduce PAPR of OFDM Signals Without Side Information”, IEEE Transactions on Broadcasting, Vol. 55, No. 4, December 2009.
[12] Wei Jiang and Daoben Li, “Convolutional Multi-code Multiplexing for OFDM Systems”, Beijing University of Posts and Telecommunications Beijing 100876, China (2007).
[13] B. Sklar, “Digital Communications Fundamentals and Applications,” Prentice Hall, Upper Saddle River, NJ, 2000.