概括
使用艾伦方差分析车辆可见光通信 (VVLC) 噪声,揭示白噪声和随机步行. 一个高斯混合模型显示,由于这种复杂的噪声,VVLC系统的性能下降.
科学领域:
- 电气工程 电气工程
- 通信工程 通信工程 通信工程
- 智能运输系统 智能运输系统
背景情况:
- 车载可见光通信 (VVLC) 使用LED技术进行智能运输.
- 噪音显著降低了VVLC系统的性能.
- 传统的噪声模型通常假定增量白色高斯噪声 (AWGN).
研究的目的:
- 分析VVLC通道中的时间相关和白噪声组件.
- 为VVLC系统开发一个更准确的噪声模型.
- 在复杂的噪声条件下评估VVLC系统的错误性能.
主要方法:
- 使用艾伦方差对时间序列数据进行噪声分析.
- 基于自适应高斯混合 (GM) 模型的运动检测算法的开发.
- 在BPSK和QPSK星座中的错误概率分析表达式的推导.
主要成果:
- 艾伦差异分析在VVLC系统中发现了白噪声和随机步行.
- 为VVLC频道噪声生成一个双高斯模型.
- 与AWGN相比,错误性能分析显示GM噪声存在的显著降解.
结论:
- VVLC通道噪声表现出超出简单AWGN的特征,包括与时间相关的组件.
- 拟议的GM噪声模型准确地反映了观察到的噪声行为.
- 在VVLC中的系统性能对GM噪声分布的混合系数敏感,需要先进的错误减轻策略.
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