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.

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