research-article

Recurrent neural network based channel estimation technique for STBC coded MIMO system over Rayleigh fading channel

Authors:

Parismita Gogoi,

Kandarpa Kumar SarmaAuthors Info & Claims

CUBE '12: Proceedings of the CUBE International Information Technology Conference

Pages 294 - 298

https://doi.org/10.1145/2381716.2381771

Published: 03 September 2012 Publication History

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Abstract

Artificial Neural Networks (ANN)s, due to their high degree of adaptability, can be used to model nonlinear phenomenon of channel estimation. In this work, a channel estimation technique based on Recurrent Neural Network (RNN) has been proposed as an alternative to pilot based channel estimation technique for STBC- MIMO systems over Rayleigh fading channels. Learning property of ANN is fully exploited for decoding the degraded symbols over severely faded channel. This technique is found to be more bandwidth efficient compared to pilot-based channel estimation techniques. Simulated results in terms of bit error rates (BER) vs. signal to noise ratio (SNR) depict the effectiveness of the learning capability of ANNs for the task of channel estimation over wireless fading channel.

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Cited By

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Mai ZChen Y(2024)A CSI Entropy-Based Estimation Algorithm and Modified Recurrent Neural Networks for Time-Varying Non-Stationary ChannelsIEEE Transactions on Vehicular Technology10.1109/TVT.2023.333970673:5(6614-6625)Online publication date: May-2024
https://doi.org/10.1109/TVT.2023.3339706
Manasa BP. V(2022)Swarm intelligence‐based deep ensemble learning machine for efficient channel estimation in MIMO communication systemsInternational Journal of Communication Systems10.1002/dac.515235:10Online publication date: 6-Apr-2022
https://doi.org/10.1002/dac.5152
Wang ZPu FYang XChen NShuai YYang R(2020)Online LSTM-Based Channel Estimation for HF MIMO SC-FDE SystemIEEE Access10.1109/ACCESS.2020.30103598(131005-131020)Online publication date: 2020
https://doi.org/10.1109/ACCESS.2020.3010359
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Index Terms

Recurrent neural network based channel estimation technique for STBC coded MIMO system over Rayleigh fading channel
1. Computing methodologies
  1. Artificial intelligence
    1. Natural language processing

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Published In

CUBE '12: Proceedings of the CUBE International Information Technology Conference

September 2012

879 pages

ISBN:9781450311854

DOI:10.1145/2381716

General Chair:
Vidyasagar Potdar
Curtin University, Australia
,
Program Chair:
Debajyoti Mukhopadhyay
Maharashtra Institute of Technology, India

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 03 September 2012

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CUBE '12: CUBE International IT Conference & Exhibition

September 3 - 5, 2012

Pune, India

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Cited By

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Mai ZChen Y(2024)A CSI Entropy-Based Estimation Algorithm and Modified Recurrent Neural Networks for Time-Varying Non-Stationary ChannelsIEEE Transactions on Vehicular Technology10.1109/TVT.2023.333970673:5(6614-6625)Online publication date: May-2024
https://doi.org/10.1109/TVT.2023.3339706
Manasa BP. V(2022)Swarm intelligence‐based deep ensemble learning machine for efficient channel estimation in MIMO communication systemsInternational Journal of Communication Systems10.1002/dac.515235:10Online publication date: 6-Apr-2022
https://doi.org/10.1002/dac.5152
Wang ZPu FYang XChen NShuai YYang R(2020)Online LSTM-Based Channel Estimation for HF MIMO SC-FDE SystemIEEE Access10.1109/ACCESS.2020.30103598(131005-131020)Online publication date: 2020
https://doi.org/10.1109/ACCESS.2020.3010359
Kaya KGündüz Öğüdücü Ş(2020)Deep Flexible Sequential (DFS) Model for Air Pollution ForecastingScientific Reports10.1038/s41598-020-60102-610:1Online publication date: 25-Feb-2020
https://doi.org/10.1038/s41598-020-60102-6
Gogoi PSarma K(2018)Kalman filter and semi-blind technique-based channel estimation for coded STBC multi-antenna set-ups in faded wireless channelsInternational Journal of Information and Communication Technology10.1504/IJICT.2014.0579766:1(86-108)Online publication date: 19-Dec-2018
https://dl.acm.org/doi/10.1504/IJICT.2014.057976

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