Low-Complexity Adaptive Channel Estimation over Multipath Rayleigh Fading Non-Stationary Channels Under CFO

TL;DR

This paper introduces low-complexity adaptive channel estimation methods for mobile wireless channels affected by Rayleigh fading, CFO, and non-stationary variations, emphasizing partial updates for improved efficiency.

Contribution

It proposes a selective partial update approach for adaptive channel estimation that balances performance and computational complexity in challenging wireless environments.

Findings

Partial update methods outperform full updates in complexity-performance trade-off.

Simulation results validate the effectiveness of the proposed techniques.

The methods adapt well to non-stationary channel conditions.

Abstract

In this paper, we propose novel low-complexity adaptive channel estimation techniques for mob ile wireless chan- n els in presence of Rayleigh fading, carrier frequency offsets (CFO) and random channel variations. We show that the selective p artial update of the estimated channel tap-weight vector offers a better trade-off between the performance and computational complexity, compared to the full update of the estimated channel tap-weight vector. We evaluate the mean-square weight error of th e proposed methods and demonstrate the usefulness of its via simulation studies.