Neural network based receiver diversity combination for high-fadng channels
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Author |
J. Raja Chidambaram, Barath Balaji, Saravanan K. and Bagubali A.
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e-ISSN |
1819-6608 |
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On Pages
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1686-1691
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Volume No. |
18
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Issue No. |
14
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Issue Date |
September 30, 2023
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DOI |
https://doi.org/10.59018/0723209
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Keywords |
receiver, neural network, MRC, BER, SNR, Python.
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Abstract
In today’s modern world, many improvements and developments in Wireless Networks have brought changes in
the convenience of people’s life. In this paper, we are proposing a new method on the topic of receiver diversity
combining. Selection diversity, maximal ratio combining, equal gain combining, and switched diversity are existing
methods for space diversity techniques. We have used various neural network models to predict the received message
based on the received signals in multi-receiver environments, therefore, proposing a new method for space diversity
combination. Comparisons with the existing methods are done in Python through simulations.
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