A KLJN-Based Thermal Noise Modulation Scheme With Enhanced Reliability for Low-Power IoT Communication

Kirchhoff’s Law Johnson Noise (KLJN)-based thermal noise modulation (Ther-Mod) represents a viable answer for secure Internet of Things (IoT) communication at ultra-low power levels. However, the conventional symmetric KLJN systems are not reliable, unless a large number of noise samples are employed, giving rise to a high latency and a low effective bitrate. We propose P-Ther-Mod, a new asymmetric KLJN-based modulation scheme, which utilizes a four-resistor structure in order to improve the bit error rate (BER) without imposing additional noise samples per bit. Theoretical bit error probability (BEP) expressions are developed for both wired and wireless IoT channels where the additive white Gaussian noise (AWGN) and Rayleigh fading models are considered. Simulation results demonstrate that the proposed P-Ther-Mod technique reduces the noise samples by up to 35% (e.g., reaching BER ${=} 10{^{-}5 }$ at N ${=}35$ compared to BER ${=}10^{-5}$ at N ${=}50$ in existing methods), and achieves BER $\approx ~10^{-8}$ at N = 200, improving previous approaches by 5 orders of magnitude. The asymmetric approach allows balancing higher bit rates by decreasing oversampling of noise. Furthermore, optimizing the detection threshold parameter (delta representing signal-to-noise ratio (SNR) in detection) enhances robustness and enables 7 dB savings in the SNR even under the fading channel. These developments render P-Ther-Mod a reliable, secure and scalable approach for IoT deployments with a vulnerable environment to interference, such as industrial sensor networks and wearable devices.