Enhanced Channel Estimation using Artificial Neural Networks in MIMO Systems
The Multiple Input Multiple Output (MIMO) is a wireless technology that consist of multiple transmitter and multiple receiver to transmit the multiple data within a time period. The signals have some noise and distortion when it reaches the destination, to eliminate the noise and distortion and to characteristics the channel, the Channel Estimation is used. This study uses the Artificial Neural Network (ANN) for improved network forecasting for MIMO system. The multiple bit streams are given to the transmitting terminal. In the transmitting terminal the Channel encoding is used to reduce the noise and bit error and the modulation process is carried out. The transmitted signal is passed through the Rayleigh fading which assumes the many random components with the same phase and amplitude. In the Receiving terminal, Detection and Decoding is carried out using the ANN and thereby the output bit stream obtained without noise channel. The suggested approaches perform better than the current ones and are robust and efficient, according to simulation data.
Authors
- S. Dhanalakshmi
- K. S. Kavin (ORCID: https://orcid.org/0000-0002-8884-1538)
- S. Sengottaian
- Manasi Malik (ORCID: https://orcid.org/0000-0002-8564-6032)
- C. S. Sree Thayanandeswari
- S. Niyas Ahamed
Institutions
- Government of Tamil Nadu (IN)
- Anna University, Chennai (IN)
Publication Details
- Published
- 2024-08-08
- DOI
- https://doi.org/10.1109/iccpct61902.2024.10672925
- Primary Topic
- Advanced MIMO Systems Optimization
- Type
- article
- Field-Weighted Citation Impact
- 0.00