Adaptive Estimation with Varying Position Updation in MIMO-OFDM System

Authors

Keywords:

Adaptive channel estimation, Kalman Filter, MIMO-OFDM system, time variant channel condition

Abstract

Estimation of channel Interference in wireless communication has remain a topic of research from many decades. With rapidly evolving new communication system and randomly varying channels, the existing estimation approaches need a finer updation in mitigating the interference issue. For signal estimation Kalman filtration has been used for its simpler computation and faster processing. Kalman filter are state based estimation which update the estimates based on a priori estimates. Existing Kalman estimation show lower estimation performance under a dynamic varying channel condition. The random deviation in user position with dynamic varying channel results into estimation error. To improve the estimation performance, in this paper an updation to the existing Kalman filtration is proposed. Two adaptively varying monitoring factors were presented to incorporate the varying position in estimation process. Proposed update observes an improvement in system throughput and estimation accuracy with less data loss under dynamic varying interferences.

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Published

24.03.2024

How to Cite

Rajender, G. ., & Sudha, P. S. . (2024). Adaptive Estimation with Varying Position Updation in MIMO-OFDM System. International Journal of Intelligent Systems and Applications in Engineering, 12(19s), 518–524. Retrieved from https://ijisae.org/index.php/IJISAE/article/view/5094

Issue

Vol. 12 No. 19s (2024)

Section

Research Article

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