Transceiver imperfections become the primary source of impairment as baud rate and modulation order grow in advanced optical coherent communications. Thus, transceiver imperfections, both linear and nonlinear, need to be appropriately characterized, measured, and specified. Treatments for linear imperfections are relatively mature. This study reviews the transceiver's linear imperfection modeling, characterization, and measurement technologies. In practical applications, in-field measurement using the transceiver and a few low speed additional devices is preferred. In the case of nonlinear imperfections, the situation is complex. One important task is to estimate the nonlinear system performance from the nonlinear characteristics of the devices. In this study, we attempt to establish a connection between them by examining different technologies. Although the orthogonal component has a good correlation with nonlinear system performance, its measurement is prohibitively complex. In the nonlinear noise to power ratio measurement, a certain frequency component of the input signal is notched, and the re-growth component at the notch frequency is measured at the nonlinear device output. The ratio between the re-growth component power and the output signal power is the noise to power ratio. While this method is easy to carry out, it does not correctly estimate nonlinear impairment in general. The reason for this is that the signal incurs different nonlinear responses in two conditions, i.e., with or without a notch. This method accurately estimates the nonlinear impairment in some special but useful cases, such as Gaussian input signals and nonlinear systems whose dominant nonlinear term is the even order term.

Nonlinear distortion (noise) limits many communication systems, demanding a means of estimating system performance via device nonlinear characteristics. The noise power ratio (NPR) method which was proposed in 1971 solves this problem for systems with Gaussian stimuli or with special nonlinearity, but practical and accurate methods for many communication systems with non-Gaussian stimuli are rare. Here we propose a probability-maintained (PM) NPR method to accurately measure the spectrum of nonlinear noise via a spectrum analyzer in non-specific systems, including systems with non-Gaussian stimuli. Using an equivalent additive noise model in which the spectrum of equivalent nonlinear noise is the measurement result of PM NPRs, nonlinear system performance could be estimated with an error of 0.5 dB. Further, we find that zero-mean Chi-square noise, instead of Gaussian noise, should be selected for large memory and low-order nonlinear systems. Our method is verified in seven different scenarios with various nonlinear mechanisms and communication applications.