On the Practical Performance of Noise Modulation for Ultra-Low-Power IoT: Limitations, Capacity, and Energy Trade-offs
For IoT system designers, this work provides practical energy trade-offs and limitations of NoiseMod, showing it is only beneficial for short-range links.
This paper benchmarks Noise Modulation (NoiseMod) against BPSK and NC-FSK for ultra-low-power IoT, finding that NoiseMod suffers an 8 dB SNR penalty at 10^{-3} BER in AWGN and a catastrophic error floor in fading, but offers superior energy efficiency below a critical crossover distance that decreases with frequency.
Ultra-low-power (ULP) IoT applications demand communication architectures with minimal energy consumption. Noise Modulation (NoiseMod) addresses this by encoding data through the statistical variance of a noise-like signal, eliminating the need for a coherent carrier. To bridge the gap between theoretical potential and practical deployment, this paper benchmarks NoiseMod against standard modulations like BPSK and NC-FSK. We analytically derive the optimal detection threshold and Bit Error Rate (BER) for AWGN and Rayleigh fading channels. Our results show that non-coherent NoiseMod suffers a catastrophic error floor in fading environments, making architectural additions like 2-antenna selection diversity mandatory. Using an ADC-aware energy model, we reveal that NoiseMod's oversampling severely bottlenecks capacity and imposes an 8 dB SNR penalty compared to NC-FSK for a $10^{-3}$ BER in AWGN. Despite its oscillator-free design drastically reducing baseline circuit power, these limitations establish a critical energy crossover distance, which decreases with frequency. Below this distance, NoiseMod offers superior energy efficiency; beyond it, the radiated power needed to overcome its SNR penalty makes coherent schemes like BPSK vastly superior.