Neural Network Based MIMO-OFDM Channel Equalizer Using Comb-Type Pilot Arrangement
Abstract
MIMO (Multiple Input Multiple Output) and OFDM (Orthogonal frequency division multiplexing) bringing along a number of pros; a combination of both stands a good possibility of being the next-generation (4th generation) of mobile wireless systems. The technology however imposes a challenge that is the increased complexity of channel equalization. Wireless channels are multipath fading channels, causing deformation in the signal. To remove the effect (imposed by channel) from received signal, the receiver needs to have knowledge of CIR (Channel impulse response) that is usually provided by a separate channel estimator. This paper is aimed at exploring the use of Neural Network (NN) as a tool for MIMO-OFDM channel estimation and compensation. The research attempts to gauges the usefulness of proposed system by analyzing different algorithms to train NN. Further to ascertain the performance of the proposed technique; length of the known training sequence has been varied over a reasonable range and observations are made. Finally, the results obtained by using different algorithms for training NN have been compared with each-other and against the traditional least squares channel estimator, which along with observations/comments form part of the paper.
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For fast time-varying channels, a hybrid learning method is proposed to assist in estimation and tracking of the channels.
“For such fast timevarying channels, a hybrid learning method is proposed in [75], to assist in estimation and tracking of the channels.”
From Quantum Machine Learning for 6G Communication Networks: State-of-the-Art and Vision for the Future (2019) · cites this paper as [75]
Cites
Channel estimation techniques based on pilot arrangement in OFDM systems
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Fast adaptive digital equalization by recurrent neural networks
Parisi, R., Claudio, E. D. D., Orlandi, G., et al. (1997) · IEEE Transactions on Signal Processing · doi:10.1109/78.650099 · Cited by 88 · see citing works
Applications of neural networks to telecommunications
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Channel Estimation Strategies for Coded MIMO Systems
Trepkowski, R. E. (2004) · Cited by 14 · see citing works
Applications of Neural Networks in Telecommunications
Field, S. (1995) · University of Hertfordshire Research Archive (University of Hertfordshire) · doi:10.13140/rg.2.2.21545.11368 · Cited by 13 · see citing works
Rahman, Q. M., Ibnkahla, M. A., & Bayoumi, M. M. (2005) · Annual Communication Networks and Services Research Conference (CNSR) · doi:10.1109/cnsr.2005.44 · Cited by 9 · see citing works
Channel estimation in OFDM systems
Arshad, K. (2003) · Cited by 8 · see citing works
Performance of wireless OFDM system channel estimation with different pilot patterns
Arshad, K., & Sheikh, A. U. H. (2005) · doi:10.1109/isssta.2004.1371688 · Cited by 3 · see citing works
Suboptimum Channel Estimate for MIMO-OFDM System in Time-Varying Fast Fading Channels
Mar, J., Kuo, C.-C., & Ko, C. (2010) · IEEE Vehicular Technology Conference · doi:10.1109/vetecs.2010.5493888 · Cited by 2 · see citing works
Neural Sequence Detector For Digital Equalization
Di-Claudio, E. D., Parisi, R., & Orlandi, G. (2015) · doi:10.5281/zenodo.37202 · Cited by 1 · see citing works
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Quantum Machine Learning for 6G Communication Networks: State-of-the-Art and Vision for the Future
Nawaz, S. J., Sharma, S. K., Wyne, S., Patwary, M. N., & Asaduzzaman, M. (2019) · IEEE Access · doi:10.1109/access.2019.2909490 · Cited by 658 · see citing works
Self-citation
- Authors
- Nawaz, S. J., Mohsin, S., & Ikaram, A. A.
- Affiliations
- Federal Urdu University (PK)
- COMSATS University Islamabad (PK)
- ORCID
- Nawaz, Syed Junaid
- Venue
- 2009 International Conference on Future Computer and Communication
- Publisher
- IEEE
- Published
- 2009-04
- Volume
- 3
- Pages
- 36-41
- OpenAlex
- W2104066017
- Cited by
- 27
- References
- 10
- Citations by year
- 2022: 3 · 2021: 2 · 2020: 1 · 2019: 3 · 2018: 1 · 2017: 2 · 2016: 2 · 2015: 3 · 2014: 3 · 2013: 3 · 2012: 4
- FWCI
- 1.92
- Type
- conference paper
- Language
- en
- Open access
- closed
- Locations
- International Conference on Future Computer and Communication (publishedVersion)
- Topics
- Physical Sciences › Engineering › Electrical and Electronic Engineering › Advanced Wireless Communication Techniques
- Physical Sciences › Engineering › Electrical and Electronic Engineering › PAPR reduction in OFDM
- Physical Sciences › Computer Science › Artificial Intelligence › Wireless Signal Modulation Classification
- Keywords
- MIMO-OFDM, channel equalization, multipath fading channels, channel impulse response, training sequence length, neural network training algorithms
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