Comparison of High-Speed PAM4 and QAM-OFDM Data Transmission Using Single-Mode VCSEL in OM5 and OM4 MMF Links

IEEE Journal of Selected Topics in Quantum Electronics(2020)

引用 22|浏览16
暂无评分
摘要
To realize the superiority of data transmission with reduced modal dispersion in OM4- and OM5-mulitmode fiber (MMF), a single transverse mode (SM) vertical cavity surface emitting laser (VCSEL), directly encoded with large-capacity data formats for transmissions in OM5-MMF and OM4-MMF, are compared. The SM-VCSEL contains a 12- μ m mesa formed by double-oxidized AlGaAs layers, which confines a current-flow area within an aperture of 3 μ m. The SM-VCSEL is lasing with a carrier-to-noise ratio of 34.4 dB and a linewidth of 0.05 nm. The SM-VCSEL is biased at 10Ith to provide a modulation bandwidth of 21.4 GHz and a relative intensity noise of −138 dBc/Hz. By encoding the SM-VCSEL with four-level pulse amplitude modulation (PAM-4) at 64 Gbit/s, the bit error ratio (BER) of 32-GBaud PAM-4 data is improved from 7.9 × 10 −5 to 4.9 × 10 −5 under a KP4-FEC criterion by replacing OM4-MMF with OM5-MMF. After OM5-MMF transmission, a bathtub BER plot shows bottom-eye, middle-eye, and top-eye jitter tolerances of 9.3, 10.6, and 7.1 ps, which are much wider than 6.9, 10.1, and 6.5 ps for OM4-MMF, respectively. When encoding the 16-QAM OFDM at 100 Gbit/s, OM5-MMF allows data transmission at 96-Gbit/s with a corresponding error vector magnitude, signal-to-noise ratio, and BER of 16.7%, 15.4 dB, and 3.6 × 10 −3 under preleveling at a slope of 0.3 dB/GHz. Because of the high effective modal bandwidth and low modal dispersion of the OM5-MMF, a relatively low receiving power penalty of 0.1 dB between 100-m and back-to-back (BtB) transmissions is obtained with either the pre-emphasized PAM-4 or the pre-leveled QAM-OFDM data format. By contrast, the receiving power penalty is 1.04 dB between 100 m and BtB cases during OM4-MMF transmission.
更多
查看译文
关键词
Vertical cavity surface emitting lasers,Data communication,Apertures,Dispersion,OFDM,Bandwidth,Modulation
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要