基于集成分类器的超5G大规模MIMO (mMIMO)通信调制识别

Md. Habibur Rahman, M. Shahjalal, Y. Jang
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引用次数: 3

摘要

大规模MIMO通信被认为是满足第五代(5G)及5G以后系统预期需求的关键和重要技术。它通过在基站部署过多的天线,为5G系统提供了巨大的潜力。因此,为了降低误码率和提高数据速率,增加了不同发射机采用不同调制方式的可能性。从而开发出能够对精确调制数据进行有效分类识别和解码的智能接收机。为了解决这一问题,本文研究了基于集成分类器的调制自动识别方案。本文对集成分类器在几种调制无线电信号下的总体性能进行了分析。仿真结果证明了集成分类器作为一种有效的调制分类器的准确性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Ensemble Classifier Based Modulation Recognition for Beyond 5G Massive MIMO (mMIMO) Communication
Massive MIMO (mMIMO) communication has been considered as pivotal and significant technology to furnish the expected demand of Fifth-generation (5G) and beyond 5G systems. It provides enormous potentiality to 5G systems by the deployment of excessive antennas at base station. Therefore, the probability of using different modulation by different transmitters has been increased aiming to reduce bit error rate as well as enhance data rate. It leads to develop intelligent receiver that can efficiently classify and recognize accurate modulation and decodes data. To shed light on this issue, automatic modulation recognition scheme based on ensemble classifier has been studied in this paper. The overall performance analysis of the ensemble classifier for several modulated radio signal has been presented in this article. The simulation results justify the exactitude of ensemble classifier as efficient one for modulation classification.
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