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• W2969293103 abstract "Ambient Backscattering Communication (AmBC) is regarded as a promising approach for green Internet-of-Things (IoT) networks. However, the noise nature of the ambient radio-frequency (RF) signal poses great difficulty for the signal processing at the receiver, resulting in an unsatisfied Bit Error Rate (BER) performance at a long communication distance. Aiming at improving AmBC performance in practical noisy environments, this letter introduces the concept of nonlinear dynamics to AmBC signal processing and thereby designs a novel Stochastic Resonance (SR) based nonlinear AmBC receiver architecture. As such, the received Signal-to-Noise Ratio (SNR) can be greatly improved, as the analog nonlinear filtering module constructively utilizes useless noise to enhance the target signal. This further allows us to realise sub-symbol level sampling with low rate, i.e. avoiding high speed Analog-to-Digital Convertor (ADC) with high power expenditure. Signal detection is finally accomplished via simple averaging and automatic thresholding, which hence greatly facilitates the efficient hardware design. Simulation results demonstrate the superiority of our nonlinear AmBC signal receiving system." @default.
• W2969293103 created "2019-08-29" @default.
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• W2969293103 date "2019-12-01" @default.
• W2969293103 modified "2023-10-16" @default.
• W2969293103 title "Hardware-Efficient Signal Detection for Ambient Backscattering Communications" @default.
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• W2969293103 doi "https://doi.org/10.1109/lcomm.2019.2936380" @default.
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