Digital filters for coherent optical receivers

Abstract

Digital filters underpin the performance of coherent optical receivers which exploit digital signal processing (DSP) to mitigate transmission impairments. We outline the principles of such receivers and review our experimental investigations into compensation of polarization mode dispersion. We then consider the details of the digital filtering employed and present an analytical solution to the design of a chromatic dispersion compensating filter. Using the analytical solution an upper bound on the number of taps required to compensate chromatic dispersion is obtained, with simulation revealing an improved bound of 2.2 taps per 1000ps/nm for 10.7GBaud data. Finally the principles of digital polarization tracking are outlined and through simulation, it is demonstrated that 100krad/s polarization rotations could be tracked using DSP with a clock frequency of less than 500MHz.

Optimal Least-Squares FIR Digital Filters for Compensation of Chromatic Dispersion in Digital Coherent Optical Receivers

“…This results in CD [1]- [5] thus limiting the transmission distance and/or data rate [6]. The CD is traditionally compensated using optical devices with opposite dispersion [5] but such approaches cannot be easily tuned/improved to accommodate different fiber spans/properties and quality measures [6].…”

Augmenting data rate performance for higher order modulation in triangular index profile multicore fiber interconnect

“…The pre-convergence is processed by an equalizer containing 15 tap FIR filters driven by constant modulus algorithm (CMA) [24], having coefficients adjusted through decision directed least mean squares (DD-LMS) method that finally provides the required numerical value of symbol error probability. Crosstalk (dB) Symbol error probability = log 10 SEP Step index ( )…”

Robust Multilevel Coherent Optical Systems With Linear Processing at the Receiver

“…However, we must force to zero the 9 The transmission of the training sequence, although not necessary for small constellations such as QPSK since convergence can still be achieved, could be avoided by resorting to some of the available algorithms for blind equalization (see [30] and references therein). An example of such a technique is the constant modulus algorithm (CMA), tailored in [21] for these applications. However, after the acquisition phase, it is more convenient to adopt the algorithm described in Section III-B, since it exhibits a better performance, converging to the matched filter, and has a lower complexity, as the reader can easily notice.…”

“…Hence, in this case a two-dimensional (2-D) matched filter can achieve perfect compensation. 1 This kind of solution was recently proposed or experimentally demonstrated by many authors (see e.g., [17]- [21] and references therein).…”