Patent Description:
This section introduces aspects that may help facilitate a better understanding of the disclosure.

Communication network operators are facing a fast growth in the bandwidth demand, in part due to the development and deployment of cloud-based services. As a result, there is a need to optimize the capacity and performance of existing fiber-optic cable plants to enable the corresponding networks to efficiently handle the increasing volumes of data. Due to this need, one of the requirements to telecom equipment manufacturers is to provide the network operator(s) with a supervisory system that can be used to monitor the status of various network elements, e.g., to guarantee fault detection, prediction, and diagnostics, improved maintainability, good performance characteristics, and/or any other pertinent benchmarks.

<CIT> discloses components of an optical communication network used to overcome the problem of signal degradation during transmission of the optical signal.

Disclosed herein are various embodiments of a performance monitor configured to unify at least two different signal-quality estimates into a single performance metric, e.g., such that a systematic error associated with the performance metric can be approximately constant or, at least, smaller than a specified fixed limit over a significantly wider range of data-link conditions than that of a conventional performance metric of similar utility. In an example embodiment, the performance metric can be based on a weighted sum of two different signal-to-noise ratio (SNR) estimates, obtained from an error count of the receiver's forward-error-correction (FEC) decoder and from the digital-sample scatter detected using the receiver's symbol decoder, respectively. Different weights for the weighted sum may be selected for different data-link conditions, e.g., using SNR thresholding, analytical or empirical models, and/or pre-computed look-up tables. The performance metric computed in this manner may be supplied to a control entity and considered thereby as a factor in a possible decision to trigger protective switching and/or a transponder-mode change.

According to an example embodiment, provided is an apparatus, comprising: an optical data receiver including one or more light detectors connected to convert modulated light into digital samples and further including a symbol decoder and an FEC decoder connected to process the digital samples to recover a data stream encoded in the modulated light; and a performance monitor to evaluate a performance metric in response to an error count from the FEC decoder and in response to a stream of measured constellation symbols from the symbol decoder, the performance metric being based on a weighted sum of a first signal-quality estimate determined based on the error count and a second signal-quality estimate determined based on deviations of the digital samples from constellation symbols.

According to another example embodiment, provided is a control method, comprising the steps of: (A) generating a first signal-quality estimate based on an error count at an FEC decoder of an optical data receiver; (B) generating a second signal-quality estimate based on deviations of digital samples from constellation symbols, the digital samples being generated by the optical data receiver in response to modulated light, the constellation symbols being determined by a symbol decoder of the optical data receiver by constellation-mapping the digital samples; and (C) computing a weighted sum of the first and second signal-quality estimates to generate a performance metric for a data link, the modulated light being used in the data link to transmit a data stream to the optical data receiver.

Other aspects, features, and benefits of various disclosed embodiments will become more fully apparent, by way of example, from the following detailed description and the accompanying drawings, in which:.

Different performance metrics can be used to quantify the transmission quality in optical communication systems. Some of such performance metrics may be based on measurements of one or more selected signal characteristics at the corresponding optical data receiver(s). For example, the optical signal-to-noise ratio (OSNR) can be measured at the receiver's optical input port using an optical spectrum analyzer. This technique may be available in some optical communication systems, e.g., as a feature inherited from the <NUM> era. However, this particular technique may not be well suited for coherent Dense Wavelength Division Multiplexing (DWDM) channels often employed in modern optical communication systems. The bit-error rate (BER) of a DWDM channel can be estimated, e.g., by counting the number of errors detected and/or corrected by the receiver's forward-error-correction (FEC) decoder. For example, in some implementations, the BER can be captured by inverting the bit-parity-violation rate at the FEC decoder. However, this particular technique may only be useful under poor channel conditions, i.e., when the OSNR is relatively low and the error rate is correspondingly high, and may not be sensitive enough and/or accurate enough in some situations, e.g., when the OSNR is relatively high. The signal-to-noise ratio (SNR) in the electrical domain of the optical receiver (i.e., the electrical SNR, ESNR) can be estimated, e.g., by analyzing or measuring the scatter of signal samples around the corresponding constellation points (see, e.g., <FIG>). However, this particular technique may be able to provide accurate results, e.g., only when the ESNR is relatively high, and may not be accurate enough when the signal quality is relatively poor. Thus, there is a need for a more-generally applicable performance metric, e.g., appropriate for a relatively wide range of channel conditions and/or suitable for capacity optimization under variable channel conditions.

These and possibly some other related problems in the state of the art can beneficially be addressed using at least some embodiments of a closed-loop capacityoptimization scheme disclosed herein. In an example embodiment, a network control entity can be configured to cause configuration changes in response to a performance metric generated by the corresponding performance monitor such that an intrinsic (e.g., systematic) error associated with the performance metric may be approximately constant or, at least, smaller than a specified fixed limit over a significantly wider range of data-link conditions than that of a conventional performance metric of similar utility. Example configuration changes may include but are not limited to protective lightpath switching and changes of the transponder mode. An additional feature of some embodiments may be the ability to generate alarms to alert the control entity to malfunctions requiring fairly expeditious remedial actions.

<FIG> shows a block diagram of an optical communication system <NUM> according to an embodiment. System <NUM> comprises an optical data transmitter <NUM> and an optical data receiver <NUM> connected using a fiber-optic link <NUM>. In some embodiments, optical data transmitter <NUM> and optical data receiver <NUM> may have wavelength-division-multiplexing (WDM) capabilities.

In an example embodiment, link <NUM> can be implemented using one or more spans of optical fiber <NUM>. In addition, link <NUM> may have: (i) one or more optical amplifiers <NUM>, each connected between two respective spans of fiber <NUM>; and one or more optical switches <NUM>, each connected between respective pluralities of spans of fiber <NUM>. In some embodiments, link <NUM> may also include additional optical elements (not explicitly shown in <FIG>), such as optical splitters, combiners, couplers, add-drop multiplexers, etc., as known in the pertinent art.

In an example embodiment, an optical amplifier <NUM> can be implemented as known in the pertinent art, e.g., using an erbium-doped fiber, a gain-flattening filter, and one or more laser-diode pumps. The number n of optical amplifiers <NUM> used in optical link <NUM> depends on the particular embodiment and may be in the range, e.g., from <NUM> to ~<NUM>. A typical length of the fiber span between two adjacent optical amplifiers <NUM> may range from ~<NUM> to ~<NUM>.

In some embodiments, link <NUM> may not have any optical amplifiers <NUM> therein.

In an example embodiment, an optical switch <NUM>i (where i=<NUM>,. , k) is an Ni×Mi optical switch, where Ni and Mi are positive integers. In the shown example, optical switch <NUM><NUM> is a <NUM>×Ml switch, and optical switch <NUM>k is an Nk×<NUM> switch. A person of ordinary skill in the art will understand that other switch parameters and/or other switchconnection topologies are also possible in various alternative embodiments. In some embodiments, some or all of optical switches <NUM> may comprise wavelength-selective switches.

In some embodiments, system <NUM> may be configured to transport, e.g., optical polarization-division-multiplexed (PDM) signals, wherein each of two orthogonal polarizations of each optical WDM channel can be used to carry a different respective data stream.

An example embodiment of optical data receiver <NUM> is described in more detail below in reference to <FIG>. In some embodiments, optical data receiver <NUM> may comprise a direct-detection optical receiver. A direct-detection optical receiver typically employs a light detector configured to measure only light intensities, e.g., the light detector may be a single photodiode as opposed to a pair of photodiodes configured for differential detection. Such a direct-detection optical receiver does not typically employ an optical hybrid. In some embodiments, a direct-detection optical receiver can be implemented by appropriately modifying or reconfiguring the coherent optical receiver of <FIG>. A person of ordinary skill in the art will understand that signal processing in a direct-detection optical receiver <NUM> and in a corresponding performance monitor <NUM> may be different from that corresponding to a coherent optical receiver.

System <NUM> further comprises a performance monitor <NUM> and an electronic controller <NUM>. Performance monitor <NUM> is connected to optical data receiver <NUM> to receive therefrom measurements <NUM> of one or more selected signal characteristics, e.g., as described below in reference to <FIG>. In operation, performance monitor <NUM> processes the received measurements <NUM> and, based on the processing results, generates a feedback signal <NUM> for controller <NUM>. In response to the feedback signal <NUM>, controller <NUM> may generate control signals <NUM>, <NUM><NUM>-<NUM>n, <NUM>, and <NUM><NUM>-<NUM>k. In some embodiments, some or all of control signals <NUM><NUM>-<NUM>n may be optional and, as such, may not be present. In some embodiments, some or all of control signals <NUM><NUM>-<NUM>k may be optional and, as such, may not be present.

Control signal <NUM> is applied to optical data transmitter <NUM> and is used thereat to set and/or change one or more configuration parameters, such as the output optical power, modulation format, baud rate, etc. Each of control signals <NUM><NUM>-<NUM>n can be applied to a respective one of optical amplifiers <NUM><NUM>-<NUM>n to set and/or change the optical gain, current, and/or output optical power thereof. Control signal <NUM> is applied to optical data receiver <NUM> and is typically used to inform the optical data receiver about any pertinent configuration changes effected by control signal <NUM> at optical data transmitter <NUM> to enable the optical data receiver to adjust its configuration parameters accordingly. For example, if control signal <NUM> causes optical data transmitter <NUM> to change the operative constellation, then control signal <NUM> causes optical data receiver <NUM> to similarly change the constellation used in the symbol decoder thereof such that there is no disruption in the data recovery thereat. Each of control signals <NUM><NUM>-<NUM>k can be applied to a respective one of optical switches <NUM><NUM>-<NUM>k to set and/or change the routing configuration thereof. For example, controller <NUM> may be configured to change the configuration of some of the switches <NUM> to reroute the optical signal transmitted between optical data transmitter <NUM> and optical data receiver <NUM> via a different fiber path. In general, controller <NUM> may be programmed to generate control signals <NUM>, <NUM><NUM>-<NUM>n, <NUM>, and <NUM><NUM>-<NUM>k in a mutually dependent manner, e.g., as a self-consistent set of control signals, to ensure proper operation of system <NUM>.

In different embodiments, various components of performance monitor <NUM> and electronic controller <NUM> may be differently distributed within system <NUM>. For example, some components of performance monitor <NUM> may be co-located with optical data receiver <NUM>. Some components of performance monitor <NUM> may be co-located with controller <NUM>. Some components of controller <NUM> may be co-located with optical data receiver <NUM>. Some or all components of controller <NUM> may be implemented using a network controller of system <NUM> (not explicitly shown in <FIG>). In some embodiments, performance monitor <NUM> and controller <NUM> may be implemented using a software package running on one or more processors of system <NUM>. Depending on the specific embodiment, some of such processors may be co-located or distributed over several relatively remote locations.

<FIG> shows a block diagram of one example of an individual-channel optical data receiver <NUM> that can be used in optical data receiver <NUM> (<FIG>) according to an embodiment. For example, in a WDM-compatible embodiment, optical data receiver <NUM> may include two or more instances of receiver <NUM>, each configured to operate using a different respective carrier wavelength as known in the pertinent art. As shown in <FIG>, optical receiver <NUM> comprises a front-end circuit <NUM> and a digital signal processor (DSP) <NUM>.

Front-end circuit <NUM> comprises an optical hybrid <NUM>, light detectors (e.g., sets of photodiodes) <NUM><NUM>-<NUM><NUM>, analog-to-digital converters (ADCs) <NUM><NUM>-<NUM><NUM>, and an optical local-oscillator (OLO) source <NUM>. Optical hybrid <NUM> has (i) two input ports labeled S and R and (ii) four output ports labeled <NUM> through <NUM>. Input port S is connected to receive an optical input signal <NUM> from optical link <NUM> (also see <FIG>). Input port R is connected to receive an OLO signal <NUM> generated by an OLO source (e.g., a laser) <NUM>. OLO signal <NUM> has an optical-carrier wavelength (frequency) that is sufficiently close to that of optical input signal <NUM> to enable coherent (e.g., intradyne) detection of the latter signal. In some embodiments, OLO source <NUM> can be implemented using a relatively stable tunable laser.

Optical hybrid <NUM> operates to mix optical input signal <NUM> and OLO signal <NUM> to generate different relative phase combinations thereof (not explicitly shown in <FIG>). Light detectors <NUM><NUM>-<NUM><NUM>, e.g., balanced pairs of photodiodes connected for differential detection from corresponding optical outputs, may then convert the corresponding mixed optical signals into electrical signals <NUM><NUM>-<NUM><NUM> that are indicative of complex values corresponding to two orthogonal-polarization components of signal <NUM>. For example, electrical signals <NUM><NUM> and <NUM><NUM> may be an analog in-phase (I) signal and an analog quadrature-phase (Q) signal, respectively, corresponding to a first (e.g., horizontal, h) polarization component of signal <NUM>. Electrical signals <NUM><NUM> and <NUM><NUM> may similarly be an analog I signal and an analog Q signal, respectively, corresponding to a second (e.g., vertical, v) polarization component of signal <NUM>.

In some embodiments, to enable separate detection of orthogonal polarization components, the optical hybrid <NUM> may include two separate about <NUM>-degree optical hybrids and a polarization splitter connecting one of the optical inputs <NUM> or <NUM> to the optical hybrids. Then, the other of the optical inputs <NUM> or <NUM> is connected to the two separate about <NUM>-degree optical hybrids by a power splitter or another polarization splitter.

Each of electrical signals <NUM><NUM>-<NUM><NUM> is converted into digital form in a corresponding one of ADCs <NUM><NUM>-<NUM><NUM>. Optionally, each of electrical signals <NUM><NUM>-<NUM><NUM> may be amplified in a corresponding electrical amplifier (not explicitly shown in <FIG>) prior to the resulting signal being converted into digital form. Digital signals <NUM><NUM>-<NUM><NUM> produced by ADCs <NUM><NUM>-<NUM><NUM> are then processed by DSP <NUM> to recover one or more original data streams <NUM> encoded in the optical input signal <NUM> by optical data transmitter <NUM> (also see <FIG>).

In an example embodiment, DSP <NUM> may perform, inter alia, one or more of the following: (i) signal processing directed at dispersion compensation; (ii) signal processing directed at reducing nonlinear distortions; (iii) electronic polarization de-multiplexing and/or signal processing to correct effects of polarization rotation; (iv) signal processing to correct relative phase misalignment of the OLO <NUM>; (v) signal processing to correct mixing phase misalignment to measure the I and Q signals; and (vi) FEC-based error correction. The processing applied by DSP <NUM> to digital signals <NUM><NUM>-<NUM><NUM> may be (re)configured based on control signal <NUM>, e.g., as mentioned above in reference to <FIG>. Example embodiments of DSP <NUM> are described in more detail below in reference to <FIG>.

<FIG> shows a block diagram of DSP <NUM> (<FIG>) according to an embodiment. Digital signals <NUM><NUM>-<NUM><NUM> and data stream <NUM> are also shown in <FIG> to better illustrate the relationship between the circuits shown in <FIG> and <FIG>.

Ideally, digital signals <NUM><NUM> and <NUM><NUM> represent the I and Q components, respectively, of the horizontal polarization component of optical signal <NUM>, and digital signals <NUM><NUM> and <NUM><NUM> represent the I and Q components, respectively, of the vertical polarization component of that optical signal. However, various transmission, measurement, and/or fabrication impairments, signal distortions in front-end circuit <NUM>, and/or configuration inaccuracies and errors generally cause each of digital signals <NUM><NUM>-<NUM><NUM> to have various linear and nonlinear distortions and/or mixing of both of the original PDM and/or the original I and Q components generated by optical data transmitter <NUM> (<FIG>). The signal-processing chain of DSP <NUM> is generally directed at reducing the adverse effects of such signal distortions and mixing in the digital signals <NUM><NUM>-<NUM><NUM> so that the transmitted data can be properly recovered to generate the output data stream <NUM>.

In an example embodiment shown in <FIG>, DSP <NUM> comprises a signal pre-processing module <NUM> configured to receive digital signals <NUM><NUM>-<NUM><NUM>. One of the functions of module <NUM> may be to adapt the signal samples received via digital signals <NUM><NUM>-<NUM><NUM> to a form that is more suitable for the signal-processing algorithms implemented in the downstream circuits of DSP <NUM>. For example, module <NUM> may be configured to (i) resample digital signals <NUM><NUM>-<NUM><NUM> and/or (ii) convert real-valued signal samples into the corresponding complex-valued signal samples. The resulting complex-valued digital signals generated by signal-pre-processing module <NUM> are labeled <NUM><NUM>-<NUM><NUM>.

Complex-valued digital signals <NUM><NUM> and <NUM><NUM> are applied to a dispersion-compensation module <NUM> for dispersion-compensation processing therein, and the resulting dispersion-compensated signals are complex-valued digital signals <NUM><NUM>-<NUM><NUM>. Example circuits that can be used to implement dispersion-compensation module <NUM> are disclosed, e.g., in U. Patent Nos. <NUM>,<NUM>,<NUM>, <NUM>,<NUM>,<NUM>, <NUM>,<NUM>,<NUM>.

Digital signals <NUM><NUM> and <NUM><NUM> are applied to a <NUM>×<NUM> MIMO (multiple-input/multiple-output) equalizer <NUM> for MIMO-equalization processing therein, and the resulting equalized signals are complex-valued digital signals <NUM>X and <NUM>Y. In an example embodiment, equalizer <NUM> can be a butterfly equalizer configured to perform electronic polarization rotation/demultiplexing. Example <NUM>×<NUM> MIMO equalizers that can be used to implement equalizer <NUM> are disclosed, e.g., in <CIT> and <CIT>.

Digital signals <NUM>X and <NUM>Y generated by equalizer <NUM> are applied to a carrier-recovery module <NUM> that is configured to perform signal processing generally directed at (i) compensating the frequency and/or phase mismatch between the carrier frequencies of optical LO signal <NUM> and optical input signal <NUM> and/or (ii) reducing the effects of phase noise of optical source(s). Various signal-processing techniques that can be used to implement the frequency-mismatch-compensation processing in carrier-recovery module <NUM> are disclosed, e.g., in <CIT> and <CIT>. Example signal-processing techniques that can be used to implement phase-error-correction processing in carrier-recovery module <NUM> are disclosed, e.g., in <CIT>.

Typically, DSP <NUM> also includes a clock-recovery circuit (not explicitly shown in <FIG>). In some embodiments, the clock-recovery circuit may be directly inserted into the data-recovery chain of DSP <NUM>, e.g., between equalizer <NUM> and carrier-recovery module <NUM>. In some other embodiments, the clock-recovery circuit may be connected in a feedback configuration outside the direct data-recovery chain of DSP <NUM>, with the feedback being provided to signal pre-processing module <NUM>, a signal interpolator (not explicitly shown in <FIG>), or ADCs <NUM>. Example clock-recovery circuits that can be used for this purpose are disclosed, e.g., in <CIT>.

Digital signals <NUM>X and <NUM>Y generated by carrier-recovery module <NUM> are applied to a symbol decoder <NUM> that converts these digital signals into data streams <NUM>X and <NUM>Y, respectively. In an example embodiment, symbol decoder <NUM> is configured to use the complex values conveyed by digital signals <NUM>X and <NUM>Y to appropriately map each complex value onto the operative constellation to determine the corresponding constellation symbol and, based on said mapping, determine the corresponding bit-word encoded in the complex value. Symbol decoder <NUM> then appropriately multiplexes and concatenates the determined bit-words to generate data streams <NUM>X and 352y.

Symbol decoder <NUM> is further configured to provide each of the determined constellation symbols to a signal-quality analyzer <NUM> by way of digital signals <NUM>X and 354y. More specifically, digital signals <NUM>X and 354y are generated to carry the complex values of the constellation points onto which the complex values supplied by digital signals <NUM>X and <NUM>Y, respectively, have been mapped by symbol decoder <NUM>. Each of the constellation points is represented by a respective complex value corresponding to the location of the constellation point on the complex I-Q plane.

An FEC decoder <NUM> is configured to apply FEC processing to data streams <NUM>X and <NUM>Y. In an example embodiment, such processing may include the steps of:
(i) multiplexing data streams <NUM>X and <NUM>Y; (ii) correcting errors (if any) in blocks of data provided by multiplexed data streams <NUM>X and <NUM>Y using data redundancies therein and using the applicable FEC code; (iii) discarding the parity bits; and (iv) outputting information bits via data stream <NUM>. FEC decoder <NUM> is further configured to count the errors detected and/or corrected at step (ii) and then provide a resulting error count <NUM> to signal-quality analyzer <NUM>.

In an example embodiment, signal-quality analyzer <NUM> can be a part of performance monitor <NUM> (<FIG>). In operation, signal-quality analyzer <NUM> processes digital signals <NUM>X, <NUM>Y, 354x, <NUM>Y, and <NUM> to generate a performance metric <NUM>, e.g., as described in more detail below. Performance monitor <NUM> and controller <NUM> may then use the performance metric <NUM> to generate control signals <NUM>, <NUM><NUM>-<NUM>n, <NUM>, and <NUM><NUM>-<NUM>k, e.g., as described in more detail below in reference to <FIG>.

In an example embodiment, signal-quality analyzer <NUM> may be configured to use the error count <NUM> to compute the pre-FEC bit error probability (BEP). The BEP can then be used to compute a first SNR estimate (SNR<NUM>). (<NUM>)-(<NUM>) provide mathematical formulas that can be used to program signal-quality analyzer <NUM> for such computations in example embodiments corresponding to a Quadrature Phase Shift Keying (QPSK) constellation and a <NUM>-ary Quadrature Amplitude Modulation (<NUM>-QAM) constellation, respectively: <MAT> <MAT> A person of ordinary skill in the pertinent art will understand how to program signal-quality analyzer <NUM> for such computations in other embodiments, e.g., corresponding to other constellations.

<FIG> graphically illustrates some of the signal processing that can be implemented in signal-quality analyzer <NUM> (<FIG>) according to an embodiment. More specifically, <FIG> shows a constellation scatter plot <NUM> that graphically illustrates a second SNR estimate (SNR<NUM>), which may be evaluated by signal-quality analyzer <NUM> based on digital signals <NUM>X, <NUM>Y, <NUM>X, and <NUM>Y. Scatter plot <NUM> corresponds to a QPSK constellation. In particular, the scatter of points about a value of a constellation symbol are indicative the noise. A person of ordinary skill in the pertinent art will understand that similar scatter plots can be generated for other constellations and how a DSP can use the measured scatter to determine the second SNR estimate.

The complex I-Q plane of scatter plot <NUM> has four quadrants, labeled A, B, C, and D, each hosting a corresponding one of the four constellation points of the QPSK constellation. Digital signals <NUM>X and <NUM>Y provide signal samples that are typically clustered around the constellation points. The lateral sizes (e.g., approximate diameters) of the clusters are related to the SNR, e.g., the larger the cluster diameter, the smaller the SNR. The probability distributions mathematically describing the clusters can thus be analyzed to determine the SNR. Qualitatively, the amplitude of the constellation point can represent the "signal" while Euclidean distances of the different signal samples from the corresponding constellation point on the I-Q plane can represent the "noise" in such an analysis.

In an example embodiment, signal-quality analyzer <NUM> can be configured to calculate SNR<NUM> from the noise variance, after normalizing the signal samples with respect to the average power. One should note however that an SNR estimate obtained in this manner might contain some intrinsic bias. For example, the SNR estimate computed in this manner can be relatively accurate when the signal quality (e.g., OSNR) is relatively high because most of the signal samples land in the same quadrant of the I-Q plane as the corresponding original constellation point. In contrast, when the signal quality is poor, the relatively high noise may cause a significant number of the signal samples to land in the quadrant(s) different from the quadrant of the corresponding original constellation point. When the probability-distribution analysis is performed on payload data (as opposed to training or pilot sequences), the receiver has no a priori knowledge of the transmitted data, which causes some of the signal samples to be attributed to incorrect sample clusters. As a result, the accuracy of noise-variance measurements may be detrimentally affected.

In some embodiments, e.g., for QPSK modulation where all constellation symbols have the same magnitude, a fourth power of the digital signal may be taken to eliminate the data dependence. The remaining scatter may be more-simply evaluated to determine noise values and a noise variance, e.g., to enable a determination of the SNR<NUM>. In such embodiments, digital signals <NUM> may not be needed for or used by analyzer <NUM> to determine SNR<NUM>.

For illustration purposes and without any implied limitations, some example embodiments are described herein below in reference to a performance metric <NUM> computed based on the above-mentioned SNR estimates SNR<NUM> and SNR<NUM> to generate a third SNR estimate (SNR<NUM>) in accordance with Eq. (<NUM>): <MAT> where a is a suitably chosen real value from the interval (<NUM>,<NUM>). Alternative forms of performance metric <NUM> are also possible in different alternative embodiments. In general, the performance metric <NUM> may be based on any of: (i) the quality factor Q<NUM>; (ii) the Q value expressed in decibel; (iii) BER; (iv) BEP; and (v) SNR. These quantities can be inter-converted, e.g., as known in the pertinent art. Furthermore, the term "performance metric" should be construed to cover any other value or quantity that can be unambiguously mapped onto SNR<NUM>.

For example, for QPSK modulation, the BEP can be computed from the SNR as follows: <MAT>.

The quality factor Q<NUM> and BEP have a one-to-one correspondence that can be expressed, e.g., as follows: <MAT> where Q[dB] = 10log<NUM>(Q<NUM>). Various combinations of the above-mentioned quantities may also be computed and interconverted accordingly.

<FIG> graphically illustrates some properties of the performance metric <NUM> according to an embodiment. More specifically, <FIG> graphically illustrates example contributions to an intrinsic error of SNR<NUM> (denoted as δSNR<NUM>) as functions of the true effective SNR (denoted as SNRt). The results shown in <FIG> were obtained using computer simulations, in which SNRt was a controllable parameter. The simulated system was modeled for <NUM> Gbps, PDM-QPSK modulation. The acquisition time of error count <NUM> and of the statistics of signals <NUM>X, <NUM>Y, <NUM>X, and <NUM>Y was set to <NUM> second.

From Eq. (<NUM>), δSNR<NUM> can be expressed as follows: <MAT> where δSNR<NUM> is an intrinsic error of SNR<NUM>; and δSNR<NUM> is an intrinsic error of SNR<NUM>. Curve <NUM> shows δSNR<NUM> as a function of SNRt. Curve <NUM> shows δSNR<NUM> as a function of SNRt. The inset shows a more-detailed view of curves <NUM> and <NUM> in the <NUM>-<NUM> dB interval of SNRt. Therein, curves <NUM> and <NUM> intersect at SNRt = S<NUM> ≈ <NUM> dB. In other embodiments, the threshold value S<NUM> may be set to or have a different value, e.g., for a different modulation format.

When SNRt < S<NUM>, δSNR<NUM> can be the bigger contributor to δSNR<NUM>. When SNRt > S<NUM>, δSNR<NUM> can be the bigger contributor to δSNR<NUM>. Based on this observation, signal-quality analyzer <NUM> can be programmed in several different ways to curtail δSNR<NUM> by appropriately selecting the weight a.

For example, in one possible embodiment, the weight a can be selected in accordance with Eq. (<NUM>): <MAT> where SNRt is estimated based on signals <NUM>X, <NUM>Y, <NUM>X, <NUM>Y, and <NUM> using Eq. (<NUM>): <MAT> where 〈•〉 denotes a time average. In this particular embodiment, the weight a is changed when the estimated SNRt crosses the threshold S<NUM>.

In another example embodiment, the weight a can be computed in accordance with Eq. (<NUM>): <MAT> where Δ<NUM> is a constant; the time-averaged error 〈δSNR<NUM>〉 is computed based on signal <NUM> and the corresponding analytical or empirical model of δSNR<NUM>; and the time-averaged error 〈δSNR<NUM>〉 is computed based on signals <NUM>X, <NUM>Y, <NUM>X, <NUM>Y and the corresponding analytical or empirical model of δSNR<NUM>. Curves <NUM> and <NUM> shown in <FIG> provide examples of such models. In this particular embodiment, the value of δSNR<NUM> can be approximately constant (i.e., δSNR<NUM> ≈ Δ<NUM>) under different link conditions within the selected range of SNRt, wherein the value of SNRt is estimated using Eq. (<NUM>). For example, the value of Δ<NUM> can be selected to be Δ<NUM> = <NUM> dB.

In yet another example embodiment, a pre-computed look-up table (LUT) can be used instead of Eq. (<NUM>). For example, such a LUT can be computed based on an analytical or empirical model of δSNR<NUM> and specific performance targets (such as Δ<NUM>) for different operating regimes of system <NUM> and/or different observed values of SNRt.

<FIG> shows a flowchart of a control method <NUM> that can be used in system <NUM> according to an embodiment.

At step <NUM> of method <NUM>, system <NUM> is transmitting data from optical data transmitter <NUM> to optical data receiver <NUM> via a selected lightpath L, delivering a capacity CL through a selected transponder mode ML. The transponder mode can be defined by several selectable configuration parameters, such as the modulation format, symbol rate, channel spacing, etc..

At step <NUM>, performance monitor <NUM> operates to collect signals <NUM>X, <NUM>Y, <NUM>X, <NUM>Y, and <NUM> during a measurement period Tm. The collected digital samples are then processed, e.g., as indicated above, to compute some or all of the following quantities or of functional equivalents thereof: SNR<NUM>, δSNR<NUM>, 〈SNR<NUM>〉, 〈δSNR<NUM>〉, SNR<NUM>, δSNR<NUM>, 〈δSNR<NUM>〉, 〈δSNR<NUM>〉, and SNRt. The computations of step <NUM> can be performed, e.g., using signal-quality analyzer <NUM>. In some cases, the computation of time-averaged values may also use the results obtained during one or more previous measurement periods Tm.

At step <NUM>, performance monitor <NUM> operates to compute some or all of the following quantities or of functional equivalents thereof: SNR<NUM>, δSNR<NUM>, 〈SNR<NUM>〉, 〈δSNR<NUM>〉, and one or more statistical characteristics thereof. Step <NUM> also includes a sub-step of determining the weight a as outlined above, e.g., using Eqs. (<NUM>), (<NUM>) or using a corresponding LUT. The computations of step <NUM> rely on at least some of the quantities computed at step <NUM>. After completing the computations and based on the results thereof, performance monitor <NUM> may generate feedback signal <NUM> for controller <NUM>. In some embodiments, feedback signal <NUM> may contain some or all of the quantities computed at step <NUM>.

At step <NUM>, controller <NUM> operates to determine whether or not a change of lightpath L and/or transponder mode ML is warranted. Although the determination of step <NUM> typically takes into consideration the feedback signal <NUM> of step <NUM>, it may also depend on other pertinent information available to controller <NUM>, such as the short-term operator strategy, traffic patterns, additional monitored performance parameters, etc..

In an example embodiment, step <NUM> may include evaluation of the following inequality: <MAT> where SNRFEC is the FEC-code limit; and M is the operator-specified SNR margin. More specifically, SNRFEC is a fixed SNR value below which the FEC-decoding processing performed by FEC decoder <NUM> typically breaks down due to the number of errors exceeding the error-correction capacity of the employed FEC code. If Inequality (<NUM>) is satisfied, then the effective SNR is deemed to be too close to the FEC-code limit, which typically warrants some reconfiguration of system <NUM>.

If controller <NUM> determines that a configuration change is warranted, then the processing of method <NUM> is directed to step <NUM>. Otherwise, the processing of method <NUM> is directed back to step <NUM>.

At step <NUM>, controller <NUM> operates to change the configuration of system <NUM>. The configuration change may include rerouting the transmitted optical signal through a different selected lightpath L and/or selecting a new transponder mode ML. Example changes may include but are not limited to selecting a different fiber path, a different wavelength channel, a different modulation format, a different symbol rate, and/or a different FEC code. One or more appropriate control signals may be generated by controller <NUM> to enact the configuration change, including some or all of control signals <NUM>, <NUM>, <NUM>, and <NUM>. Depending on the situation, the new transponder mode ML may cause the capacity CL to increase or decrease.

After step <NUM> is completed, the processing of method <NUM> is directed back to step <NUM>.

Example advantages and/or benefits of at least some of the above-described embodiments can be illustrated using the following observations. In a regularly performing system <NUM>, the SNR can typically fluctuate by <NUM>-<NUM> dB, e.g., when polarization-dependent loss is present. However, in a malfunctioning system <NUM>, the SNR can fluctuate by more than <NUM> dB, possibly signifying an imminent outage in the next few hours or even minutes. In the latter scenario, conventional SNR metrics typically provide SNR estimates characterized by relatively large uncertainties (i.e., large measurement error bars) and, as such, may misinform the control entity. In contrast, δSNR<NUM> can be relatively small and approximately constant over an even wider SNR range than <NUM> dB. As a result, SNR<NUM> may be a more suitable indicator for real-time capacity optimization and other corrective actions than some of the conventional SNR metrics. Furthermore, system-alarm triggers and controller decisions may become more reliable, e.g., because abnormal SNR fluctuations are less likely to be buried in (obscured by) the measurement noise of SNR<NUM> than in the measurement noise of conventional SNR metrics. An additional benefit may be derived from the fact that SNR<NUM> tends to necessitate lesser resources than several individual metrics of similar combined utility, e.g., in terms of signaling bandwidth, memory usage, and/or computational power.

The following description provides an example analytical model that can be used, e.g., to program performance monitor <NUM>, controller <NUM>, and/or signal-quality analyzer <NUM> in some embodiments.

The relative error of the BEP estimated by Monte Carlo error counting is approximately equal to the inverse of the square root of the number Ne of errors counted by FEC decoder <NUM>: <MAT> where σBEP is the standard deviation of the BEP; and 〈BEP〉 is the true average value of the BEP. The 〈BEP〉 value can be estimated as: <MAT> where <MAT>; Ne,k is the error count <NUM> over a block of Nb,k bits received in the k-th time period of duration Tg; the number NT is <MAT>; and TBEP is the total errorcounting time. For a fixed bit rate Rb, the number Ne can be estimated as: <MAT>.

(<NUM>) and (<NUM>), the uncertainty of BEP (denoted as δBEP) can be estimated as: <MAT> For QPSK modulation, Eq. (<NUM>) can then be used to rewrite Eq. (<NUM>) as follows: <MAT> where 〈BEP〉 can be estimated from BER measurements, e.g., using Eq. (<NUM>) or another suitable approximation.

When assessing SNR<NUM> from a measured scatter, e.g., similar to the scatter of scatter plot <NUM> (<FIG>), a straightforward decision by the quadrant (i.e., A, B, C, D; <FIG>) results in four sets of complex samples. For each of the sets, one can calculate the expected value and variance and therefore assess the average value of SNR<NUM> over the entire scatter plot. In such cases, it is customary to normalize the total received power (i.e., signal + noise) to <NUM>. After normalization, SNRt can be estimated as: <MAT> where V is the true complex-sample variance. Based on Eq. (<NUM>), δSNR<NUM> can be estimated as follows: <MAT> where SNRt can be linked to 〈BEP〉 via Eq. (<NUM>). It is also known that the variance V estimated from signal samples affected by additive white Gaussian noise (AWGN) has a standard deviation δ V expressed as follows: <MAT> where Ns is the number of signal samples. Using Eq. (<NUM>), Eq. (<NUM>) can be rewritten as: <MAT> A person of ordinary skill in the art will understand that Eq. (<NUM>) can be used to obtain another estimate of δSNR<NUM>. Eq. (<NUM>) clearly shows that, for high values of SNRt, δSNR<NUM> does not depend on SNRt and is simply a function of the number Ns of signal samples.

If training symbols are used to calculate the scatter variance (i.e. the transmitted symbols are known to the receiver), then Eq. (<NUM>) provides an accurate estimate of the uncertainty. If no training symbols are used and the variance is calculated based on symbol decisions, then δSNR<NUM> can be estimated as: <MAT> where the overbar denotes the average over the observation time. For practical purposes, the overall uncertainty can be found as an appropriate function of the uncertainties given by Eqs. (<NUM>), (<NUM>), (<NUM>), and (<NUM>), e.g., with the function being constructed to reflect the specific method used for acquiring the SNR estimates and/or statistics.

According to an example embodiment disclosed above, e.g., in the summary section and/or in reference to any one or any combination of some or all of <FIG>, provided is an apparatus comprising: an optical data receiver (e.g., <NUM>, <FIG>; <NUM>, <FIG>) including one or more light detectors (e.g., <NUM>, <FIG>) connected to convert modulated light into digital samples (e.g., <NUM>, <FIG>) and further including a symbol decoder (e.g., <NUM>, <FIG>) and an FEC decoder (e.g., <NUM>, <FIG>) connected to process the digital samples to recover a data stream (e.g., <NUM>, <FIG>, <FIG>) encoded in the modulated light; and a performance monitor (e.g., <NUM>, <FIG>) to evaluate a performance metric (e.g., <NUM>, <FIG>) in response to an error count (e.g., <NUM>, <FIG>) from the FEC decoder and in response to a stream of measured constellation symbols (e.g., <NUM>, <FIG>) from the symbol decoder, the performance metric being based on a weighted sum of a first signal-quality estimate (e.g., SNR<NUM>, Eq. (<NUM>)) determined based on the error count and a second signal-quality estimate (e.g., SNR<NUM>, Eq. (<NUM>)) determined based on deviations of the digital samples from constellation symbols.

In some embodiments of the above apparatus, the performance monitor is configured to select a weight (e.g., a, Eq. (<NUM>)) for the weighted sum based on an SNR estimate corresponding to the digital samples.

In some embodiments of any of the above apparatus, the performance monitor is configured to select the weight such that the weight has a first value for one value of the SNR estimate and a different second value for another value of the SNR estimate.

In some embodiments of any of the above apparatus, the performance monitor is configured to select the weight using a look-up table having stored therein different fixed values of the weight for different signal-to-noise ratios.

In some embodiments of any of the above apparatus, the performance monitor is configured to select a first value of the weight if the SNR estimate is smaller than a fixed threshold value (e.g., first line of Eq. (<NUM>)); and wherein the performance monitor is configured to select a different second value of the weight if the SNR estimate is larger than the fixed threshold value (e.g., second line of Eq. (<NUM>)).

In some embodiments of any of the above apparatus, the performance monitor is configured to compute the SNR estimate based on both the error count and the deviations (e.g., Eq. (<NUM>)).

In some embodiments of any of the above apparatus, the performance monitor is configured to select a weight (e.g., a, Eq. (<NUM>)) for the weighted sum such that a systematic error of the performance metric does not exceed a fixed limit (e.g., Δ<NUM>, Eq. (<NUM>)).

In some embodiments of any of the above apparatus, the performance monitor is configured to select a weight (e.g., a, Eq. (<NUM>)) for the weighted sum such that a systematic error of the performance metric is approximately constant (e.g., Δ<NUM>, Eq. (<NUM>)) within an SNR range at least <NUM> dB wide (or at least <NUM> dB wide).

In some embodiments of any of the above apparatus, the performance metric directly provides an estimate of one of: a quality factor Q<NUM>; a Q value expressed in decibel; a bit-error rate; a bit-error probability; and a signal-to-noise ratio.

In some embodiments of any of the above apparatus, the performance monitor comprises a signal-quality analyzer (e.g., <NUM>, <FIG>) configured to compute the performance metric, the signal-quality analyzer being co-located with the optical data receiver.

In some embodiments of any of the above apparatus, the apparatus further comprises: an optical data transmitter (e.g., <NUM>, <FIG>) connected to apply the modulated light to the optical data receiver; and an electronic controller (e.g., <NUM>, <FIG>) configured to cause a change of a transponder mode (e.g., at <NUM>, <FIG>) for the optical data transmitter in response to the performance metric received from the performance monitor.

In some embodiments of any of the above apparatus, the electronic controller is connected to inform the optical data receiver (e.g., via <NUM>, <FIG>) about the change.

In some embodiments of any of the above apparatus, the apparatus further comprises an electronic controller (e.g., <NUM>, <FIG>) configured to cause a change of a lightpath (e.g., at <NUM>, <FIG>) via which the optical data receiver receives the modulated light, the change being caused in response to the performance metric received from the performance monitor.

In some embodiments of any of the above apparatus, the performance monitor is separated from the optical data receiver by a distance greater than <NUM>.

In some embodiments of any of the above apparatus, the optical data receiver comprises a coherent optical receiver (e.g., <NUM>, <FIG>).

According to another example embodiment disclosed above, e.g., in the summary section and/or in reference to any one or any combination of some or all of <FIG>, provided is a control method comprising the steps of: (A) generating a first signal-quality estimate (e.g., SNR<NUM>, Eq. (<NUM>)) based on an error count (e.g., <NUM>, <FIG>) at an FEC decoder (e.g., <NUM>, <FIG>) of an optical data receiver; (B) generating a second signal-quality estimate (e.g., SNR<NUM>, Eq. (<NUM>)) based on deviations of digital samples (e.g., <NUM>, <FIG>) from constellation symbols (e.g., <NUM>, <FIG>), the digital samples being generated by the optical data receiver in response to modulated light, the constellation symbols being determined by a symbol decoder of the optical data receiver by constellation-mapping the digital samples; and (C) computing a weighted sum of the first and second signal-quality estimates to generate a performance metric (e.g., <NUM>, <FIG>; Eq. (<NUM>)) for a data link, the modulated light being used in the data link to transmit a data stream (e.g., <NUM>, <FIG>, <FIG>) to the optical data receiver.

In some embodiments of the above control method, the control method further comprises the step of changing (e.g., at <NUM>, <FIG>), based on the performance metric, at least one of a lightpath in the data link and a transponder mode used for generating the modulated light.

While this disclosure includes references to illustrative embodiments, this specification is not intended to be construed in a limiting sense. Various modifications of the described embodiments, as well as other embodiments within the scope of the disclosure, which are apparent to persons skilled in the art to which the disclosure pertains are deemed to lie within the principle and scope of the disclosure, e.g., as expressed in the following claims.

It will be further understood that various changes in the details, materials, and arrangements of the parts which have been described and illustrated in order to explain the nature of this disclosure may be made by those skilled in the art without departing from the scope of the disclosure, e.g., as expressed in the following claims.

Although the elements in the following method claims, if any, are recited in a particular sequence with corresponding labeling, unless the claim recitations otherwise imply a particular sequence for implementing some or all of those elements, those elements are not necessarily intended to be limited to being implemented in that particular sequence.

Unless otherwise specified herein, the use of the ordinal adjectives "first," "second," "third," etc., to refer to an object of a plurality of like objects merely indicates that different instances of such like objects are being referred to, and is not intended to imply that the like objects so referred-to have to be in a corresponding order or sequence, either temporally, spatially, in ranking, or in any other manner.

Unless otherwise specified herein, in addition to its plain meaning, the conjunction "if" may also or alternatively be construed to mean "when" or "upon" or "in response to determining" or "in response to detecting," which construal may depend on the corresponding specific context. For example, the phrase "if it is determined" or "if [a stated condition] is detected" may be construed to mean "upon determining" or "in response to determining" or "upon detecting [the stated condition or event]" or "in response to detecting [the stated condition or event].

Also for purposes of this description, the terms "couple," "coupling," "coupled," "connect," "connecting," or "connected" refer to any manner known in the art or later developed in which energy is allowed to be transferred between two or more elements, and the interposition of one or more additional elements is contemplated, although not required. Conversely, the terms "directly coupled," "directly connected," etc., imply the absence of such additional elements. The same type of distinction applies to the use of terms "attached" and "directly attached," as applied to a description of a physical structure. For example, a relatively thin layer of adhesive or other suitable binder can be used to implement such "direct attachment" of the two corresponding components in such physical structure.

The described embodiments are to be considered in all respects as only illustrative and not restrictive. In particular, the scope of the disclosure is indicated by the appended claims rather than by the description and figures herein. All changes that come within the meaning and range of equivalency of the claims are to be embraced within their scope.

A person of ordinary skill in the art would readily recognize that steps of various above-described methods can be performed by programmed computers. Herein, some embodiments are intended to cover program storage devices, e.g., digital data storage media, which are machine or computer readable and encode machine-executable or computer-executable programs of instructions where said instructions perform some or all of the steps of methods described herein. The program storage devices may be, e.g., digital memories, magnetic storage media such as a magnetic disks or tapes, hard drives, or optically readable digital data storage media. The embodiments are also intended to cover computers programmed to perform said steps of methods described herein.

The functions of the various elements shown in the figures, including any functional blocks labeled as "processors" and/or "controllers," may be provided through the use of dedicated hardware as well as hardware capable of executing software in association with appropriate software. Moreover, explicit use of the term "processor" or "controller" should not be construed to refer exclusively to hardware capable of executing software, and may implicitly include, without limitation, digital signal processor (DSP) hardware, network processor, application specific integrated circuit (ASIC), field programmable gate array (FPGA), read only memory (ROM) for storing software, random access memory (RAM), and non volatile storage.

As used in this application, the term "circuitry" may refer to one or more or all of the following: (a) hardware-only circuit implementations (such as implementations in only analog and/or digital circuitry); (b) combinations of hardware circuits and software, such as (as applicable): (i) a combination of analog and/or digital hardware circuit(s) with software/firmware and (ii) any portions of hardware processor(s) with software (including digital signal processor(s)), software, and memory(ies) that work together to cause an apparatus, such as a mobile phone or server, to perform various functions); and (c) hardware circuit(s) and or processor(s), such as a microprocessor(s) or a portion of a microprocessor(s), that requires software (e.g., firmware) for operation, but the software may not be present when it is not needed for operation. " This definition of circuitry applies to all uses of this term in this application, including in any claims.

It should be appreciated by those of ordinary skill in the art that any block diagrams herein represent conceptual views of illustrative circuitry embodying the principles of the disclosure.

Claim 1:
An apparatus, comprising:
an optical data receiver (<NUM>) including one or more light detectors (<NUM>) connected to convert modulated light into digital samples (<NUM>) and further including a symbol decoder (<NUM>) and an FEC decoder (<NUM>) connected to process the digital samples to recover a data stream (<NUM>) encoded in the modulated light; characterized in that the apparatus also comprises:
a performance monitor (<NUM>) to evaluate a performance metric (<NUM>) in response to an error count (<NUM>) from the FEC decoder and in response to a stream of measured constellation symbols (<NUM>) from the symbol decoder, the performance metric being based on a weighted sum of a first signal-quality estimate determined based on the error count and a second signal-quality estimate determined based on deviations of the digital samples from constellation symbols.