A new BPSK demodulation circuit for command transmission in wireless implantable neural recording system

Wu, Zhao; Liang, Zhen; Li, B.

doi:10.1109/apccas.2008.4746323

Cited by 2 publications

(1 citation statement)

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“…So far, the most frequently used hardware platforms include analog circuits using discrete components, application-specific integrated circuits (ASIC), and general-purpose programmable devices. Analog circuit platforms have been rarely used in recent years, due to the instability of the discrete components [15]. ASICs have a small volume and low power consumption, but the cost is much higher and the function cannot be modified once the chip tape-out has been completed [16].…”

Section: Introductionmentioning

confidence: 99%

FPGA Implementation of a BPSK 1D-CNN Demodulator

Yan

Shen

et al. 2018

Applied Sciences

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In this paper, we propose a field programmable gate array (FPGA) implementation of a one-dimensional convolution neural network (1D-CNN) demodulator for binary phase shift keying (BPSK). The 1D-CNN demodulator includes two 1D-CNNs and a decision module. Discrete time series of BPSK signals are imported into the well-trained 1D-CNNs. The 1D-CNNs detect the phase shifts' moment and type, including phase shift from 0 to π and that from π to 0. The decision module combines results of the two 1D-CNNs and outputs the demodulated data. In order to improve the efficiency of resource utilization and operation speed of the FPGA circuit, a time-delay network for convolutional calculation and a structure for piecewise approximation for the activation function were designed. To enhance the performance of the 1D-CNN demodulator, universal and diversity training data considering five impact factors were generated specially. Experimental results under different channel conditions show that the proposed demodulator has good adaptability to frequency offset and short latency. The demodulation loss of the proposed demodulator can almost be kept within 2 dB.

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Section: Introductionmentioning

confidence: 99%