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Analytical Analysis on LS, MMSE and Modified Entropy-Based LS Channel Estimation Techniques for 5G Massive MIMO Systems

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Micro-Electronics and Telecommunication Engineering

Part of the book series: Lecture Notes in Networks and Systems ((LNNS,volume 617))

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Abstract

Universal frequency division multiplexing (UFMC) has obtained a lot of interest in 5G wireless communication. In UFMC systems, the function of channel transfer of radio channel appears unequal in both time and frequency domains. Therefore, estimating a channel dynamically is important for the detection of UFMC signals. There are many estimation methods for UFMC systems. This paper investigates pilot-aided channel estimation techniques for UFMC systems. It is known that least square (LS) and minimum mean square error (MMSE) algorithms are effective channel estimation (CE) methods to produce accurate estimation output. We proposed a novel modified entropy-based least square (MELS) channel estimation method which is based on mean value of the transmitted vector to improve the estimation accuracy of the UFMC system. This paper also explains the analytical analysis of the LS, MMSE and MELS channel estimation techniques. The performance analysis of this channel estimation methods is done by using simulation results. The simulation results are implemented using MATLAB software. The results show that at high values of SNR, the MELS algorithm outperforms the LS and MMSE for both bit error rate (BER) and mean square error (MSE).

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Authors and Affiliations

  1. Lovely Professional University, Paghwara, Punjab, India

    Shaik Nilofer & Praveen Kumar Malik

  2. BVRIT HYDERABAD College of Engineering for Women, Hyderabad, India

    Shaik Nilofer & P. Manju

  3. Pennsylvania State University, State College, Pennsylvania, 16802, US

    Sumit Agarwal

Authors
  1. Shaik Nilofer
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  2. Praveen Kumar Malik
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  3. P. Manju
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  4. Sumit Agarwal
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Corresponding author

Correspondence to Shaik Nilofer .

Editor information

Editors and Affiliations

  1. SRM Institute of Science and Technology, Ghaziabad, India

    Devendra Kumar Sharma

  2. National Taipei University of Business, Hualien, Taiwan

    Sheng-Lung Peng

  3. SRM Institute of Science and Technology, Ghaziabad, Uttar Pradesh, India

    Rohit Sharma

  4. Department of Embedded Systems Engineering, College of Information Technology, Incheon National University, Incheon, Korea (Republic of)

    Gwanggil Jeon

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© 2023 The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

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Nilofer, S., Malik, P.K., Manju, P., Agarwal, S. (2023). Analytical Analysis on LS, MMSE and Modified Entropy-Based LS Channel Estimation Techniques for 5G Massive MIMO Systems. In: Sharma, D.K., Peng, SL., Sharma, R., Jeon, G. (eds) Micro-Electronics and Telecommunication Engineering . Lecture Notes in Networks and Systems, vol 617. Springer, Singapore. https://doi.org/10.1007/978-981-19-9512-5_40

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  • DOI: https://doi.org/10.1007/978-981-19-9512-5_40

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-19-9511-8

  • Online ISBN: 978-981-19-9512-5

  • eBook Packages: EngineeringEngineering (R0)

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