A Comprehensive Review and Deep Learning-Based Methodology for Channel Estimation in Next-Generation Wireless Communication Systems
Volume: 14 - Issue: 07 - Date: 01-07-2025
Approved ISSN: 2278-1412
Published Id: IJAECESTU495 | Page No.: 101-105
Author: Jyotsna Sagar
Co- Author: Dr. Rajesh Kumar Rai, Dr. Vamshi Talla,,
Abstract:-The process of compressive review of channel estimation methods based on conventional and
dynamic methods for next generation wireless communication. The neural network and machine learning
based channel estimation enhance the capacity and performance of communication service and model. The
deep learning-based channel estimator provides good accuracy and estimation but face a bottleneck problem
of false alarm rate and false negative rate. The neural network-based channel estimation faces a problem of
channel discontinue of estimation, this problem also finds in MLP based channel estimator The deep
learning-based channel face a problem of pilot sequence training time is very high and decline the
performance of communication model. , This paper describes the several approaches of channel estimation in
communication systems. Also describes different types of deep learning algorithm and employed algorithm
of machine learning for channel estimation ,This chapter describe as the proposed methodology of channel
estimation in wireless communication. The proposed methodology design two algorithms based on deep
learning and classification for channel estimation. .This paper includes the simulation tool parameters with its
simulation analysis. Here we also consider the result analysis and performance analysis.. As wireless
networks expand in size and complexity, particularly in mmWave-based 5G deployments, these legacy
approaches become impractical. Therefore, scalable, efficient signal processing algorithms are essential to
manage the vast amounts of real-time mobile data, ensuring performance is not compromised by network
scale.
Key Words:- Channel Estimation Next-Generation Wireless Communication, Machine Learning (ML), Deep Learning (DL), Neural Networks, 5G Wireless Networks
Area:-Engineering
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