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A Novel Intelligent Channel Estimation Strategy for the 5G Wireless Communication Systems

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Abstract

Nowadays, the Multiple Input Multiple Output (MIMO) Orthogonal Frequency Division Multiplexing (OFDM) is an important method used in wireless communications, especially in 5G cellular communications. As in a wireless network, the input signals pass through a channel, and the input signal undergoes phase shift, attenuation, and interference. So, the information from the user side and the received signals differ. Thus, an effective channel estimator is essential to make cellular communication better. Hence, a novel hybrid technique called Chimp-based CatBoost channel estimation (CbCBCE) was proposed. This technique combines the Chimp optimization algorithm and the CatBoost algorithm. The channel parameters are estimated and then reduced using the Chimp optimization algorithm. Finally, the proposed model is validated with the case study. Then, the result of the proposed model was estimated and compared with other existing techniques. It is observed that the outcome of the proposed design is high compared to the other conventional methods. The presented model is executed in the MATLAB platform, proving that the proposed model has high throughput, increased energy efficiency, less BER, and a high data transfer rate.

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Authors and Affiliations

  1. G. Narayanamma Institute of Technology and Science, Shaikpet, Hyderabad, 500104, India

    Maddala Vijayalakshmi & Ambidi Naveena

  2. G. Narayanamma Institute of Technology and Science, Shaikpet, Hyderabad, 500104, India

    Meeniga Vijayalakshmi

Authors
  1. Maddala Vijayalakshmi
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  2. Meeniga Vijayalakshmi
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  3. Ambidi Naveena
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Correspondence to Maddala Vijayalakshmi.

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Vijayalakshmi, M., Vijayalakshmi, M. & Naveena, A. A Novel Intelligent Channel Estimation Strategy for the 5G Wireless Communication Systems. Wireless Pers Commun 130, 2727–2751 (2023). https://doi.org/10.1007/s11277-023-10401-8

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