On the Impact of Fixed Point Hardware for Optical Fiber Nonlinearity Compensation Algorithms

Nonlinearity mitigation using digital signal processing has been shown to increase the achievable data rates of optical fiber transmission links. One especially effective technique is digital back propagation (DBP), an algorithm capable of simultaneously compensating for linear and nonlinear channel distortions. The most significant barrier to implementing this technique, however, is its high computational complexity. In order to fully characterize the performance of DBP, there is a need to model the algorithm under the constraint of a fixed hardware complexity which, crucially, would include the bit-depth of the multiplication operation. In this work, DBP and a single nonlinear step DBP implementation, the Enhanced Split Step Fourier method (ESSFM), are compared with linear equalization using a generic software model of fixed point hardware. The requirements of bit depth and fast Fourier transform (FFT) size are discussed to examine the optimal operating regimes for these two schemes of digital nonlinearity compensation. For a 1000 csv system, it was found that (assuming an optimized FFT size), in terms of SNR, the ESSFM algorithm outperformed the conventional DBP for all hardware resolutions up to 13 bits.