LAUSR

Backscattering communications have been recently proposed as an effective enabling technology for massive Internet of Things (IoT) development. A novel application of backscattering, called ambient backscattering (AmBC), has been gaining much attention, wherein backscattering communications exploit existing RF signals without the need for a dedicated transmitter. In such a system, data demodulation process is strongly complicated by the random nature of the illuminating signal, as well as by the presence of the direct-link interference (DLI) from the legacy system. To overcome these shortcomings, one can resort to noncoherent detection strategies, aimed at reducing or even nullifying the amount of a priori information needed to reliably perform signal demodulation. In this paper, we investigate noncoherent detection strategies for backscatter communications over ambient OFDM signals and solve the noncoherent maximum-likelihood (ML) detection problem for a general $Q$ -ary signal constellation. Additionally, we derive a suboptimal detector, which takes the form of the classical energy-detector (ED), whose performance is evaluated in closed-form. Finally, the performance of the proposed detectors is corroborated through Monte Carlo simulations.