Analog Variance Noise Modulation: Detection by Extended Rao-Blackwellized Particle Filtering
Nargess Sadeghzadeh-Nokhodberiz, Hadi Zayyani, Mohammad Salman, Felipe Augusto Pereira De Figueiredo, Rausley A. A. de Souza · IEEE Open Journal of the Communications Society · 2026
This paper presents a novel framework foranalog variance noise modulation (VNM)and its correspondingvariance-based demodulationtechnique. Unlike traditional digital noise communication systems such as Kirchhoff–Law–Johnson–Noise (KLJN) schemes that encode binary data using discrete noise levels, the proposed analog VNM continuously maps a signal’s amplitude onto the variance of a white Gaussian noise (WGN) carrier. In this way, information is embedded within thestatistical behaviorof noise rather than its waveform, enabling inherently secure and noise-like transmission. To accurately reconstruct the transmitted signal, we develop a newstate-space modeling and inference frameworkinspired by the Discrete Fourier Transform (DFT). This model captures the temporal structure of the analog baseband signal through its harmonic components while treating the noise variance as a time-varying latent process. Building upon this structure, aRao–Blackwellized Particle Filter (RBPF)is designed to estimate the underlying signal by jointly inferring its harmonic dynamics and the hidden variance states, enabling robust demodulation under stochastic noise conditions. Simulation results demonstrate that the proposed analog VNM achieves accurate signal recovery and exhibits strong concealment properties compared to classical amplitude and frequency modulation schemes. Overall, this work introduces a new class ofanalog noise-based communicationwith an inherently simple and energy-efficient transmitter, while employing a higher-complexity receiver-side inference framework for accurate signal recovery. This asymmetric architecture makes the proposed VNM particularly suitable for low-power sensing and Internet of Things (IoT) scenarios where ultra-lightweight transmitters communicate with computationally capable gateways or base stations.