Abstract
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.
Highlights
With the advent of Internet of Things (IoT) [1], [2], where Internet extends into the real world [3] and billions of devices sense the surrounding environment and communicate without human intervention, a key issue is the search for energyefficient reliable sensing communication protocols, which can support large-scale and seamless deployment by relaxing battery constraints
The channel taps are modeled as circularly-symmetric complex Gaussian random variables, with path-losses given by [45], [46] σi2k = c2/(4π fcζik )2, for (i, k) ∈ {(1, 2), (2, 4), (1, 4)}, where c = 3·108 m/s is the light speed
This paper dealt with noncoherent detection problem for backscatter communications over ambient Orthogonal Frequency Division Multiplexing (OFDM) signals
Summary
With the advent of Internet of Things (IoT) [1], [2], where Internet extends into the real world [3] and billions of devices sense the surrounding environment and communicate without human intervention, a key issue is the search for energyefficient reliable sensing communication protocols, which can support large-scale and seamless deployment by relaxing battery constraints. For this reason, backscattering communications [4]–[8] have been recently proposed as an effective enabling technology for massive IoT development.
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