Noise-suppression method for UAV-OFDM systems by introducing CV-VSS-NLMS algorithm and single-antenna architecture
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Date
2025
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Abstract
In this paper, we address the critical challenge of impulsive interference in
orthogonal frequency division multiplexing (OFDM)-based unmanned aerial
vehicle (UAV) communication systems, which can severely degrade data
transmission reliability. Specifically, we propose a novel complex-valued
variable step-size normalized least mean square (CV-VSS-NLMS) adaptive
filtering algorithm dedicated for adaptive filtering of complex-valued
signals, providing real-time, lightweight, and efficient impulsive-noise
suppression for UAV-OFDM signals. In contrast, real-valued VSS-LMS
filters treat the real and imaginary parts separately, resulting in poorer mean
square error (MSE) convergence for complex signals. The algorithm is
developed by efficiently adapting LMS-based filtering strategies to
impulsive interference scenarios and adequately integrating prior concepts of
electromagnetic pulse suppression within a well-designed single-antenna
UAV architecture. This new configuration is especially suited for size,
weight, and power-constrained UAV platforms, where reducing complexity
is highly desirable. In contrast to conventional blind source separation
approaches, the proposed solution ensures reliable communication without
excessive processing demands, since it efficiently suppresses impulsive
noise and greatly reduces the number of matrix operations. Simulation
results demonstrate a significant improvement in bit error rate (BER),
confirming that the proposed CV-VSS-NLMS technique provides a robust,
dependable, and practical solution for modern UAV communication links.