Modulation recognition using an FPGA-based convolutional neural network

被引：0
|
作者：
Liu, Xueyuan [1 ]
Shang, Jing [1 ]
Leong, Philip H. W. [2 ]
Liu, Cheng [1 ]
机构：
[1] Harbin Inst Technol, Sch Elect Engn & Automat, Harbin, Peoples R China
[2] Univ Sydney, Sch Elect & Informat Engn, Sydney, NSW, Australia
来源：
2019 22ND INTERNATIONAL CONFERENCE ON ELECTRICAL MACHINES AND SYSTEMS (ICEMS 2019) | 2019年
关键词：
modulation; FPGA; neural network;
D O I：
暂无
中图分类号：
TM [电工技术]; TN [电子技术、通信技术];
学科分类号：
0808 ; 0809 ;
摘要：
As wireless communications continues to gain in importance and spectrum traffic becomes more and more dense, the challenge of fast modulation classification is also increasing. Although modulation classification has been a well-studied problem, achieving high accuracy from a small number of samples is difficult. Moreover, most methods are not designed for line-speed operation over multiple channels or bands. In this paper, a deep learning model using a constellation diagram approach and its FPGA implementation are applied to solve this problem.
引用
收藏
页码：3165 / 3170
页数：6
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