Flag-Preamble-Based Delay-Doppler Channel Estimation for Next-Evolution Waveforms

TL;DR

This paper introduces a robust delay-Doppler channel estimation method for next-evolution waveforms, combining optimized Flag sequences with advanced algorithms to improve accuracy and robustness over traditional methods.

Contribution

It presents a novel channel estimation algorithm that integrates adaptive Flag sequence optimization with a candidate selection and LS refinement to enhance robustness and reduce complexity.

Findings

Significant improvement in estimation accuracy over traditional algorithms

Effective mitigation of spurious sidelobe peaks

Enhanced robustness against robustness issues in conventional methods

Abstract

Accurate delay-Doppler channel estimation is critical for next-evolution waveforms (NEWs) to enable reliable signal detection. This paper proposes a robust channel estimation algorithm that integrates Flag sequences optimized via an adaptive accelerated parallel majorization-minimization (AP-MM) algorithm with a proposed channel estimation algorithm. To enable efficient, low-complexity parameter extraction and further overcome the robustness issues of conventional greedy estimation, we introduce two key enhancements, i.e., a candidate selection strategy to mitigate spurious sidelobe peaks, and a global least squares (LS) refinement stage to eliminate error propagation caused by sidelobe masking effects. Numerical results demonstrate that the proposed scheme significantly outperforms traditional existing algorithms, achieving the desired estimation accuracy.