Feedforward carrier recovery for polarization demultiplexed signals with unequal signal to noise ratios

Abstract

We investigate feedforward carrier recovery (FFCR) in coherent polarization diversity receivers where the signal to noise ratio (SNR) of polarization demultiplexed signals can be unequal, such as in polarization-dependent loss impaired systems. A joint-polarization FFCR mechanism for estimating the carrier phase noise based on samples from both polarizations is proposed and compared with three other plausible alternatives. We evaluated each architecture using Monte Carlo simulations and observed that the joint-polarization FFCR yields a 1.1 dB SNR penalty for a given laser linewidth x baud rate product, while the other three architectures offer 1.8 dB, 2.0 dB and 3.9 dB, for QPSK at BER = 10(-3) and 3 dB SNR imbalance.

Filtered Carrier Phase Estimator for High-Order QAM Optical Systems

“…where w n are the low-pass filter coefficients, x k are the resulting symbols after QPSK partition, N is the FIR filter length, and P U M is the phase unwrapper operation, which constrains the incremental phase variation to the interval [−π/M, π/M ] by adding multiples of ±2π/M whenever absolute phase variation between consecutive elements is greater than π/M . One possible implementation of phase unwrapper is as follows [12], [19]:…”

“…Averaging of the additive noise through joint-polarization processing has been extensively used in carrier recovery [3], [19], [20], [21]. In this work, we also investigate jointpolarization processing, whose architecture is shown in Fig.…”

“…There is an additional threshold-based QPSK partition and a raising to the fourth power. This structure is similar to the flat-filter feedforward carrier recovery architecture proposed in [19]. However, in [19], the sum of the QPSK-partitioned symbols of the two polarizations is further divided by two (an averaging operation).…”

Phase recovery for QPSK transmission without using complex multipliers

“…4, Im(z k ) + Im(z k-1 ) is a positive number. Thus, the imaginary part of the output signal is positive and the magnitude is |Im(z k )| + |Im(z k-1 )| according to (13). Accordingly, the signal s k in (13) can lead to correct estimated phase noise.…”

Analysis of signal processing techniques for optical 112 Gb/s DP-QPSK receivers with experimental data

“…The first step of the algorithm is to remove the data dependency by raising the complex signal to the fourth power. Afterwards, the sequence is filtered in order to minimize the influence of additive noise in the estimation process [6], and the signal argument is divided by four. The resulting argument sequence is then submitted to a phase unwrapper (PU) [7], to allow the resulting phase to vary between −∞ to +∞, instead of being limited between − గ ସ and + గ ସ…”