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- Title
Performance of Channel Estimation Schemes in the presence of Gaussian Mixture Model.
- Authors
Bai, Saveeta; Khan, Abid Muhammad; Rauf, Muhammad; Kumar, Suresh; Kumar, Haresh
- Abstract
Channel estimation (CE) plays a crucial role in establishing a wireless link, specifically at the receiver node. Most of the receivers that estimate the channel is in the presence of AWGN. However, these schemes perform expressively worse when the impulsive noise is added in AWGN which is introduced by manmade sources (pressure cooker, motorbike, electric supply) as well as natural noises (earthquakes and thundering). The major contribution of this research is to analyze the channel estimation schemes in the Gaussian mixture model (GMM) environment. The performance of channel estimation schemes has been compared in terms of mean square error (MSE) and bit error rate (BER). Four channel estimation schemes e.g., MMSE, DFT, correlation- based methods like Gauss-Seidel (GS) and Successive Over-Relaxation (SOR), are studied and analyzed. The study reveals that the correlation scheme based on the method of SOR is more effective as compared to the methods of DFT, MMSE and GS because of faster convergence rate along with the minimum number of iteration. SOR shows sustainable results up to the probability of an impulsive element of 5 Percent.
- Subjects
CHANNEL estimation; GAUSSIAN mixture models; BIT error rate; ERROR rates
- Publication
International Journal on Electrical Engineering & Informatics, 2021, Vol 13, Issue 3, p653
- ISSN
2085-6830
- Publication type
Article
- DOI
10.15676/ijeei.2021.13.3.10