面向毫米波无线接入网的数字型光载无线技术

doi:10.11959/j.issn.2096-3750.2019.00128

摘要/Abstract

摘要：

随着5G空口标准将毫米波段定为无线接入网络的重要载波频段，毫米波通信成为提高移动通信系统传输性能的关键技术。首先介绍了面向毫米波无线接入网的数字型光载无线（DRoF）传输技术，然后对目前应用于 DRoF 系统中的不同量化编码算法进行了比较与总结，对系统的误差矢量幅度（EVM）、系统复杂度及频谱利用率等重要性能指标进行了分析，以期为毫米波无线接入网的构建提供参考。

关键词: 毫米波通信, 无线接入网, 数字型光载无线, 移动前传

Abstract:

As the air interface standard of 5G confirms the millimeter wave as one important frequency band for the signal carrier,millimeter-wave communication is considered as the key technique to improve the transmission performance of the mobile communication system.Firstly,the digital radio over fiber (DRoF) link in 5G application was introduced.Then,the different quantization coding algorithms applied in DRoF system were compared and summarized.In order to provide reference for the construction of millimeter-wave radio access network,the important performance indexes such as the error vector amplitude (EVM),system complexity and spectrum utilization were analyzed.

Key words: millimeter-wave communication, radio access network, digital radio over fiber, mobile fronthaul

中图分类号:

TN929.5

叶佳,罗健威,郭仪,潘炜. 面向毫米波无线接入网的数字型光载无线技术[J]. 物联网学报, 2019, 3(4): 17-24.

Jia YE,Jianwei LUO,Yi GUO,Wei PAN. Digital radio over fiber transmission technique for millimeter-wave radio access network[J]. Chinese Journal on Internet of Things, 2019, 3(4): 17-24.

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调制格式	EVM	量化比特/bit	频谱效率/倍
4QAM	9.40%	3	10
16QAM	4.98%	4	7.5
64QAM	3.71%	5	6
256QAM	2.85%	6	5
1024QAM	0.96%	8	3.75
4096QAM	0.47%	9	3.33

量化编码算法	优点	缺点
DPCM	较PCM编码技术在EVM性能、频谱效率上有明显提升	使用高阶预测器时会出现过拟合，且抗噪能力弱
NS-DPCM	同样的量化比特数下，EVM 性能较DPCM提升40%	引入 FIR 滤波器回路，增加系统内存资源和功耗负荷
DCT-MBQ	在相同的压缩比下，较上述两种算法均有更好的EVM性能	算法不能自动划分量化段，移植性和适应新模式的能力差
自适应DPCM-Lloyd	能够自适应地在不同的调制模式下保持较好的性能	系统较复杂，在低量化比特数时性能一般

算法	调制格式	EVM	QB/Sa
K-means	4QAM	16.15%	3
	16QAM	8.43%	4
	64QAM	5.01%	5
	256QAM	2.76%	6
VLP-VQ	4QAM	13.41%	3
	16QAM	7.00%	4
	64QAM	3.89%	5
	256QAM	2.33%	6
SOFM	4QAM	12.112%	3
	16QAM	6.211%	4
	64QAM	3.771%	5
	256QAM	2.85%	6

量化算法	优点	缺点
K-means	结构简单，系统时延低	低量化位数时 EVM 性能较差
VLP-VQ	EVM 性能和频谱效率较K-means有较大的提升	系统结构复杂，预测阶数高时会出现过拟合
SOFM	实时性能较好，EVM 性能较好	线下训练时间较长