A Modified KNN Algorithm for High-Performance Computing on FPGA of Real-Time m-QAM Demodulators
نویسندگان
چکیده
A methodology for scalable and concurrent real-time implementation of highly recurrent algorithms is presented experimentally validated using the AWS-FPGA. This paper presents a parallel KNN algorithm focused on m-QAM demodulators high-level synthesis fast prototyping, parameterization, scalability design. The proposed design shows successful interchannel interference mitigation in 3 × 16 Gbaud 16-QAM Nyquist WDM system. Additionally, we present modified version which comparisons among data symbols are reduced by identifying closest neighbor rule 8-connected clusters used image processing. Real-time Xilinx Virtex UltraScale+ VU9P AWS-FPGA board was compared with results obtained previous work same from experimental setup but offline DSP Matlab. show that difference negligible below FEC limit. reduction operations 43 percent to 75 percent, depending symbol’s position constellation, achieving 47.25% total computational time 100 K input processed 20 cores algorithm.
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ژورنال
عنوان ژورنال: Electronics
سال: 2021
ISSN: ['2079-9292']
DOI: https://doi.org/10.3390/electronics10050627