RF transceiver and transmission line behavioral modeling in VHDL-AMS for wired RFNoC

Zerioul, Lounis; Ariaudo, Myriam; Bourdel, Emmanuelle

doi:10.1007/s10470-017-0975-6

Cited by 5 publications

(1 citation statement)

References 26 publications

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“…RF network-on-chip (RFNoC) is an open-source framework for developing data processing applications that can be run on FPGAs [25]. It is a method of modularizing signals or data processing components on an FPGA and effectively accessing them.…”

Section: Architecturementioning

confidence: 99%

Implementation of Deep Learning-Based Automatic Modulation Classifier on FPGA SDR Platform

Tang

2018

Electronics

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Intelligent radios collect information by sensing signals within the radio spectrum, and the automatic modulation recognition (AMR) of signals is one of their most challenging tasks. Although the result of a modulation classification based on a deep neural network is better, the training of the neural network requires complicated calculations and expensive hardware. Therefore, in this paper, we propose a master-slave AMR architecture using the reconfigurability of field-programmable gate arrays (FPGAs). First, we discuss the method of building AMR, by using a stack convolution autoencoder (CAE), and analyze the principles of training and classification. Then, on the basis of the radiofrequency network-on-chip architecture, the constraint conditions of AMR in FPGA are proposed from the aspects of computing optimization and memory access optimization. The experimental results not only demonstrated that AMR-based CAEs worked correctly, but also showed that AMR based on neural networks could be implemented on FPGAs, with the potential for dynamic spectrum allocation and cognitive radio systems.

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Section: Architecturementioning

confidence: 99%