Ultra-low-power (ULP) Internet of Things (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 channel state information (CSI) estimation and 2-antenna selection diversity desirable. 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.

翻译：超低功耗（ULP）物联网应用要求通信架构具有极低的能耗。噪声调制通过噪声类信号的统计方差对数据进行编码，从而消除了对相干载波的需求。为弥合理论潜力与实际部署之间的差距，本文以BPSK和NC-FSK等标准调制方式为基准对噪声调制进行了评估。我们解析推导了AWGN和瑞利衰落信道下的最优检测阈值与误码率（BER）。结果表明，非相干噪声调制在衰落环境中会出现灾难性错误平层，这使得信道状态信息估计和两天线选择分集等架构增强成为必要。借助考虑模数转换器能耗的模型，我们发现噪声调制的过采样严重制约了容量，并在AWGN信道下为达到$10^{-3}$误码率需付出比NC-FSK高8 dB的信噪比代价。尽管其无振荡器设计大幅降低了基础电路功耗，但这些局限性确立了一个随频率递减的关键能量交叉距离。在此距离内，噪声调制具有更优的能效；超出该距离后，克服信噪比代价所需的辐射功率使BPSK等相干方案更具优势。