Hybrid Method for Wireless Channel Estimation
Hybrid Method for Wireless Channel Estimation |
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| © 2025 by IJETT Journal | ||
| Volume-73 Issue-3 |
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| Year of Publication : 2025 | ||
| Author : Aruna R, Pushpa Mala S, Keerti Kulkarni |
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| DOI : 10.14445/22315381/IJETT-V73I3P123 | ||
How to Cite?
Aruna R, Pushpa Mala S, Keerti Kulkarni, "Hybrid Method for Wireless Channel Estimation," International Journal of Engineering Trends and Technology, vol. 73, no. 3, pp. 315-323, 2025. Crossref, https://doi.org/10.14445/22315381/IJETT-V73I3P123
Abstract
Channel estimation involves the process of estimating the characteristics of the communication channel, particularly the channel's impulse response or frequency response. This information is essential for the receiver to compensate for the effects of the channel and properly decode the transmitted signal. The novelty of this work is integrating the deep learning framework with the compressive sensing approach for channel estimation. Combining Compressive Sensing (CS) with Convolutional Neural Networks (CNNs) for channel estimation leverages the strengths of both approaches: the ability of CS to exploit sparsity and the powerful feature extraction and learning capabilities of CNNs. The output is then compared with the channel estimated using the pilot-based channel estimation, least square estimation, and maximum likelihood estimation. It is found that the results obtained with the proposed fusion give a lower RMSE (0.11) and lower BER (1.82 x 10-6) compared with the other methods. This indicates the effectiveness of the proposed method for channel estimation.
Keywords
Channel Estimation, CNN, Compressive Sensing, RMSE, BER.
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