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在多用户白光OFDMA VLC系统中的AL辅助AMC通过光扩散纤维循环传输光

Zixian Wei, Codey Nacke, Mostafa Khalil

|July 14, 2023

概括

本研究介绍了使用人工智能用于可见光通信 (VLC) 系统的自适应调制方案. 新方法提高了多用户数据传输速度和准确性,在白光网络.

科学领域:

光学通信是指光学通信.
人工智能在通信中的应用
无线网络无线网络.

背景情况:

可见光通信 (VLC) 系统使用照明提供高速无线数据传输.
适应式调制对于优化动态多用户环境中的性能至关重要.
在VLC中,直角频率分割多重复合接入 (OFDMA) 可实现高效的频谱利用.

研究的目的:

为灵活,高速,多用户VLC开发一个自适应调制方案.
实施自动调制分类 (AMC) 来监控基于OFDMA的VLC中的调制格式.
提高VLC系统中调制分类的效率和准确性.

主要方法:

一种联合的卷积神经网络 (CNN),主动学习 (AL) 和数据增强 (DA) 方法用于AMC.
扩散白光VLC系统与OFDMA框架的集成.
实验性演示与两个用户的访问场景和不平等的带宽分配.

主要成果:

实现了325.5 Mbps的数据速率,比特错误率 (BER) 在前向错误纠正 (FEC) 门内为2.163 × 10-3.
在使用AL辅助CNN AMC方案的OFDMA信号子载波中,证明了分类准确率为95.48%.
与传统的基于CNN的AMC相比,与有限的培训数据 (240个样本) 展现了更快的融合.

结论:

拟议的AL辅助CNN AMC方案有效地支持高速多用户VLC的自适应调制.
该系统提供可靠的白光照明和无处不在的访问.
这种方法提高了下一代VLC网络的光谱效率和适应性.

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