Digital-to-analog converter (DAC) plays an important role in a communication system, which determines the quality of the generated signal. A high-resolution DAC is necessary to guarantee the system performance. However, the application of a high-resolution DAC results in high system cost and power consumption, which is incompatible with the future low-cost data centers. To be cost-effective and energy-efficient, a system with low-resolution DAC and negligible quantization noise induced performance degradation is highly desirable. Noise shaping (NS) technique is proposed to effectively suppress the quantization noise induced by low-resolution DAC. In this paper, we review the principle of the NS technique, and its effectiveness is investigated experimentally in 100 Gb/s intensity modulation and direct detection (IM/DD) PAM-4 system with low-resolution DAC. The experimental results show that the system with 4-bit DAC coupled with NS technique shows almost the same receiver sensitivity as the system with 8-bit DAC without NS technique over 2-km and 10-km single mode fiber (SMF) transmission in O-band. It indicates that significant performance improvement can be achieved by using NS technique in low-resolution DAC systems, and it is a promising solution for future low-cost data centers.

A non-iterative electrical dispersion pre-compensation (pre-EDC) scheme based on a multi-output neural network (NN) is proposed. The scheme is evaluated in an O-band simulation system utilizing the 1270nm optical carrier with the dispersion coefficient of -5 ps/(nm.km). The simulation results show that the multi-output NN pre-EDC realizes the same performance as the traditional iterative modified GS pre-EDC while surpassing previously proposed non-iterative pre-EDC. Additionally, the proposed multi-output NN-based pre-EDC can reduce the time consumption of the pre-EDC procedure by 50%.