Predictive analog-digital-conversion in fiber optics communication

Advances in digital hardware had enabled a new generation of fiber optics communication receivers. Extensive digital-signal-processing (DSP) allows compensating for channel impairments and, in turn, scaling up in data rate. One of the main challenges in modern receivers is implementing a high-rate, high-precision analog-to-digital-converter (ADC) that could meet the system requirements. Since ADCs technology is usually far from the highest rates available, reducing required resolution is imperative for present and future receivers. In this paper a predictive quantization approach is investigated. We show that common optical channel and components impairments introduce sufficient waveform correlation, which may be leveraged to significantly improve the Analog-to-digital-conversion process. Simulation results had shown that implementing low-complexity predictive quantization systems improves SNR performance, and may be used to reduce required resolution.