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In this paper, we show numerically and experimentally that turbo equalization (TE) is an efficient technique to mitigate performance degradations stemming from optical fiber propagation effects in both optical fiber dispersion managed and unmanaged coherent detection links. The effectiveness of the proposed solution can be appreciated in both linear and nonlinear regimes for either scenario. We report on a system employing a polarization division multiplexing (PDM) 16-quadrature amplitude modulation (QAM) format for which we accomplish an increment in tolerance to link input power of up to 3 dB that represents a substantial improvement margin. The best bit error rate (BER) performances will therefore be guaranteed in a larger window, 6 dB, of link input power thanks to the implemented TE scheme. Moreover, our proposed approach is also proven to effectively mitigate interchannel impairments from surrounding amplitude shift-keying interfering channels in a dispersion managed link achieving also in this case an increment in power tolerance of 3 dB. Furthermore, in terms of BER performances, our proposed TE approach guarantees a gain of about a half order of magnitude at the best operational point. As TE can be included in the current coherent detection transceiver technologies and complement other equalization techniques, it has prospects for application in next-generation high-capacity and long-reach optical transmission links. [ABSTRACT FROM PUBLISHER]

High order modulation formats allow to reach higher spectral efficiency and data rate. However, their practical implementation is limited by their reduced tolerance to noise and to the optical signal power that can be launched into the fiber without generating excessive nonlinear signal distortions. In this paper, it is demonstrated that Turbo Equalization routines can be used to mitigate performance degradations stemming from optical fiber propagation effects both in optical fiber dispersion managed and unmanaged coherent detection links. The effectiveness of this solution is analyzed both numerically and experimentally for different transmission systems. [ABSTRACT FROM PUBLISHER]

We present a technique for modulation format recognition for heterogeneous reconfigurable optical networks. The method is based on Stokes space signal representation and uses a variational Bayesian expectation maximization machine learning algorithm. Differentiation between diverse common coherent modulation formats is successfully demonstrated numerically and experimentally. The proposed method does not require training or a constellation diagram to operate, is insensitive to polarization mixing or frequency offset and can be implemented in any receiver capable of measuring Stokes parameters. [ABSTRACT FROM PUBLISHER]

The flexibility and elasticity of the spectrum is an important topic today. As the capacity of deployed fiber-optic systems is becoming scarce, it is vital to shift towards solutions ensuring higher spectral efficiency. Working in this direction, we report an extensive experimental study on adaptive allocation of superchannels in spectrum-flexible heterogeneous optical network. In total, three superchannels were transmitted. Two 5-subcarrier 14-GHz-spaced, 14 Gbaud, polarization-division-multiplexed (PDM) quadrature-phase-shift-keyed (QPSK) superchannels were separated by a spectral gap, the band of interest (BOI). The bandwidth of the BOI was varied. The BOI was subsequently filled with another superchannel, constituted by a different number of either 14 Gbaud PDM-QPSK or PDM-16-ary quadrature amplitude modulation (16-QAM) subcarriers. The optical signal-to-noise ratio (OSNR) for transmission of the subcarriers inserted into the BOI, depending on the modulation format, subcarrier count and spacing to the neighboring superchannels, was extracted through experimental implementation of different scenarios. The obtained values were interpolated to yield the required OSNR necessary to maintain a 1×10−3 bit error rate of the central BOI subcarrier. The results provide a rule of thumb that can be exploited in resource allocation mechanisms of future spectrum-flexible optical networks. [ABSTRACT FROM PUBLISHER]