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

Institutions

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
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Enhanced Channel Estimation using Artificial Neural Networks in MIMO Systems

S. Dhanalakshmi, K. S. Kavin, S. Sengottaian, Manasi Malik et al.
Advanced MIMO Systems Optimization
article

Enhanced Channel Estimation using Artificial Neural Networks in MIMO Systems

S. Dhanalakshmi, K. S. Kavin, S. Sengottaian, Manasi Malik, C. S. Sree Thayanandeswari, S. Niyas Ahamed
article en

Abstract

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.

Vol. 19
Government of Tamil Nadu (IN), Anna University, Chennai (IN)
Affordable and clean energy
Openalex Percentile: Top 87%
Advanced MIMO Systems Optimization
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

Enhanced Channel Estimation using Artificial Neural Networks in MIMO Systems — S. Dhanalakshmi, K. S. Kavin, et al. · (2024) | TGRS Research Map | TGRS