Performance Comparison of 112-Gb/s DMT, Nyquist PAM4, and Partial-Response PAM4 for Future 5G Ethernet-Based Fronthaul Architecture
Abstract
For a future 5G Ethernet-based fronthaul architecture, 100G trunk lines of a transmission distance up to 10 km standard single mode fiber (SSMF) in combination with cheap grey optics to daisy chain cell site network interfaces are a promising cost- and power-efficient solution. For such a scenario, different intensity modulation and direct detect (IMDD) Formats at a data rate of 112 Gb/s, namely Nyquist four-level pulse amplitude modulation (PAM4), discrete multi-tone Transmission (DMT) and partial-response (PR) PAM4 are experimentally investigated, using a low-cost electro-absorption modulated laser (EML), a 25G driver and current state-of-the-art high Speed 84 GS/s CMOS digital-to-analog converter (DAC) and analog-to-digital converter (ADC) test chips. Each modulation Format is optimized independently for the desired scenario and their digital signal processing (DSP) requirements are investigated. The performance of Nyquist PAM4 and PR PAM4 depend very much on the efficiency of pre- and post-equalization. We show the necessity for at least 11 FFE-taps for pre-emphasis and up to 41 FFE coefficients at the receiver side. In addition, PR PAM4 requires an MLSE with four states to decode the signal back to a PAM4 signal. On the contrary, bit- and power-loading (BL, PL) is crucial for DMT and an FFT length of at least 512 is necessary. With optimized parameters, all Modulation formats result in a very similar performances, demonstrating a transmission distance of up to 10 km over SSMF with bit error rates (BERs) below a FEC threshold of 4.4E-3, allowing error free transmission.
- Publication:
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Journal of Lightwave Technology
- Pub Date:
- May 2018
- DOI:
- arXiv:
- arXiv:1801.10574
- Bibcode:
- 2018JLwT...36.1807E
- Keywords:
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- Electrical Engineering and Systems Science - Signal Processing;
- Computer Science - Networking and Internet Architecture
- E-Print:
- The work leading to these results has received funding from the European Union's Seventh Framework Programme under Grant Agreement No. 644526 (ABACUS), the European Union's Horizon 2020 Research and Innovation Programme under Grant Agreement No. 644526 (iCIRRUS), and the German Ministry of Education and Research (BMBF) under contract numbers 16KIS0477K (SENDATE Secure-DCI) and 13N13744 (SPeeD)