A Novel Channel Estimation Framework in MIMO Using Serial Cascaded Multiscale Autoencoder and Attention LSTM with...

Area of Science:

• Wireless Communication
• Signal Processing
• Optimization Techniques

Background:

• Multi-Input Multi-Output (MIMO) systems utilize multiple antennas for enhanced wireless communication, but face challenges in system intricacy and power consumption, particularly with Analog-to-Digital Converters (ADCs).
• Accurate channel estimation is crucial for MIMO system performance, yet traditional methods struggle with the complexity and data loss issues associated with ADCs.

Purpose of the Study:

• To propose an efficient heuristic-based optimization technique for enhancing channel estimation in MIMO systems.
• To develop a novel channel prediction framework that accurately estimates channel coefficients at the transmitter based on receiver feedback.
• To minimize Root Mean Square Error (RMSE), Bit Error Rate (BER), and Mean Square Error (MSE) in channel estimation.

Main Methods:

• A Hybrid Serial Cascaded Network (HSCN) was developed, integrating a multi-scaled cascaded autoencoder with Long Short-Term Memory (LSTM) and an attention mechanism.
• Channel coefficients are predicted at the transmitter using the receiver's error ratio obtained via feedback.
• The parameters of the HSCN and Attention LSTM were optimized using a Hybrid Revised Position-based Wild Horse and Energy Valley Optimizer (RP-WHEVO) algorithm.

Main Results:

• The developed MIMO model demonstrated enhanced convergence rate and prediction performance.
• Significant reduction in computational costs was achieved compared to existing methods.
• The proposed RP-WHEVO algorithm effectively minimized RMSE, BER, and MSE for channel estimation.

Conclusions:

• The proposed heuristic-based optimization technique offers an efficient solution for improving channel estimation in MIMO systems.
• The integration of HSCN, Attention LSTM, and RP-WHEVO provides a robust framework for accurate and computationally efficient wireless communication.
• This research contributes to overcoming the challenges posed by ADCs and enhances overall MIMO system functionality.