DC-Based Superposition Signaling for Low-Power IoT Receivers

Abstract

This letter presents a novel orthogonal frequency division multiplexing (OFDM) system serving both Internet-of-Things (IoT) and legacy receivers. Motivated by the noise modulation (NoiseMod) paradigm, which embeds information into statistical parameters of random signals, we leverage the Gaussian statistics of time-domain OFDM signals to enable low-complexity IoT detection without FFT-based processing. Exploiting the zero-mean Gaussian nature of time-domain OFDM signals, the transmitter superimposes a direct current (DC)-biased signal, representing a single IoT information symbol, onto a standard OFDM signal and alters the statistical mean of the transmitted waveform. Furthermore, we present a novel receiver architecture for both the IoT receiver and the legacy receiver, and derive exact bit error probability (BEP) expressions for both receivers over Rician and Rayleigh fading channels, respectively. The IoT receiver operates without requiring OFDM demodulation, enabling reduced hardware cost for energy-constrained devices. Theoretical BEP results and Monte Carlo BER results are provided across various configurations.