Abstract: Features related to a system and method for scheduling a resources to perform discrete tasks are described. The scheduling features include generating schedules predicted to appeal to the tasked resource (e.g., delivery partner) such as by time, day of the week, location, item types, etc. Using machine learning, the schedule and terms thereof can be dynamically generated to suit the tastes of each tasked resource and the overall demand for services. Using historical data, the modeling also accounts for likelihood an offer will be accepted and risk of cancellation for a given resource. The machine learning may be based on a mixed integer problem as constrained by partner and system capacity parameters.

Abstract: A signal generation apparatus and method. The apparatus includes: a memory, and a processor coupled to the memory to control execution of a process to: perform dispersion processing on a two-dimensional reference signal to obtain a two-dimensional dispersion signal; perform at least one time of equiprobability processing, perturbation processing and isospectral processing on a two-dimensional input signal according to the two-dimensional dispersion signal; and output a two-dimensional isospectral equiprobability signal generated, when an equiprobability processed signal or an isospectral processed signal satisfies a predetermined condition, wherein in the equiprobability processing.

Abstract: An apparatus and method to measure nonlinear system noises may include a processor to generate a bilateral notch signal, a unilateral notch signal and a multi-tone signal; to measure power of an additive Gaussian white noise of a nonlinear system by using the multi-tone signal; to measure a first power-to-noise ratio of the nonlinear system by using the bilateral notch signal; to measure a second power-to-noise ratio of the nonlinear system by using the unilateral notch signal. The processor is to calculate a nonlinear power-to-noise ratio of the nonlinear system and a power-to-noise ratio introduced by IQ imbalance according to the power of the additive Gaussian white noise, the first power-to-noise ratio and the second power-to-noise ratio.

Abstract: A polarization change tracking apparatus, a processing apparatus for a received signal and methods thereof. The polarization change tracking method includes: estimating a polarization change speed in a link according to a received signal; setting a response coefficient of polarization tracking according to a relationship between an estimated polarization change speed and a predetermined value, to make a response of polarization tracking and a response of adaptive equalization be consecutive; and performing compensation for polarization change on the received signal according to a set response coefficient of polarization tracking.

Abstract: A polarization recovery apparatus, a method thereof and an optical receiver. The method includes: performing adaptive equalization processing and polarization recovery on a received signal, wherein a polarization state of the received signal, after the adaptive equalization processing and polarization recovery being performed, is aligned with a principal axis of polarization of an optical receiver.

Abstract: An apparatus and method to monitor a polarization change by inserting pilot signals in a transmission signal and converting the pilot signals in the receiving signal from a Jones space into a Stokes space. A velocity of a polarization change of the optical link is estimated by using the Stokes vectors of the pilot signals, thereby directly and accurately estimating the polarization change of the optical link. Moreover, estimation of the velocity of the polarization may be applicable where rotation of state of polarization and polarization-dependent loss coexist in an optical link.

Abstract: A polarization recovery apparatus, a method thereof and an optical receiver. The method includes: performing adaptive equalization processing and polarization recovery on a received signal, wherein a polarization state of the received signal, after the adaptive equalization processing and polarization recovery being performed, is aligned with a principal axis of polarization of an optical receiver.

Abstract: A polarization change tracking apparatus, a processing apparatus for a received signal and methods thereof. The polarization change tracking method includes: estimating a polarization change speed in a link according to a received signal; setting a response coefficient of polarization tracking according to a relationship between an estimated polarization change speed and a predetermined value, to make a response of polarization tracking and a response of adaptive equalization be consecutive; and performing compensation for polarization change on the received signal according to a set response coefficient of polarization tracking.

Abstract: An apparatus and method to monitor a polarization change by inserting pilot signals in a transmission signal and converting the pilot signals in the receiving signal from a Jones space into a Stokes space. A velocity of a polarization change of the optical link is estimated by using the Stokes vectors of the pilot signals, thereby directly and accurately estimating the polarization change of the optical link. Moreover, estimation of the velocity of the polarization may be applicable where rotation of state of polarization and polarization-dependent loss coexist in an optical link.

Abstract: A state of polarization tracking recovery method and apparatus. The apparatus at least includes a processor configured to fit Stokes vectors to which predetermined symbols correspond of two states of polarization in a received dual-polarization multiplexing optical signal on a Poincare sphere to obtain a fitted plane. The processor calculates a compensation matrix for polarization-dependent loss (PDL) in a Jones space by moving a center of the fitted plane to the origin of the Poincare sphere, and calculates a demultiplexing matrix used for polarization demultiplexing in a Jones space by rotating the fitted plane with the center being moved to the origin until a normal vector of the fitted plane is parallel with a first axis of the Stokes space and rotating the fitted plane with the center being moved to the origin to a plane constituted by a second axis and a third axis of the Stokes space.

Abstract: A state of polarization tracking recovery method and apparatus. The apparatus at least includes a processor configured to fit Stokes vectors to which predetermined symbols correspond of two states of polarization in a received dual-polarization multiplexing optical signal on a Poincare sphere to obtain a fitted plane. The processor calculates a compensation matrix for polarization-dependent loss (PDL) in a Jones space by moving a center of the fitted plane to the origin of the Poincare sphere, and calculates a demultiplexing matrix used for polarization demultiplexing in a Jones space by rotating the fitted plane with the center being moved to the origin until a normal vector of the fitted plane is parallel with a first axis of the Stokes space and rotating the fitted plane with the center being moved to the origin to a plane constituted by a second axis and a third axis of the Stokes space.

Abstract: Features related to a system and method for scheduling a resources to perform discrete tasks are described. The scheduling features include generating schedules predicted to appeal to the tasked resource (e.g., delivery partner) such as by time, day of the week, location, item types, etc. Using machine learning, the schedule and terms thereof can be dynamically generated to suit the tastes of each tasked resource and the overall demand for services. Using historical data, the modeling also accounts for likelihood an offer will be accepted and risk of cancellation for a given resource. The machine learning may be based on a mixed integer problem as constrained by partner and system capacity parameters.

Abstract: Embodiments of this disclosure provide a method and apparatus for establishing a transmission impairment decomposition model for a Raman amplified system and a system. The method includes: converting a Jones vector of a test signal after passing through a Raman amplified system into a Stokes vector; calculating transmission impairments to which the test signal is subjected by using the Stokes vector according to a pre-established transmission impairment decomposition model; and substituting values of the transmission impairments into the pre-established transmission impairment decomposition model to obtain a complete transmission impairment decomposition model used for estimating transmission impairments.

Abstract: Embodiments of this disclosure provide a method and apparatus for monitoring a modulation depth of a dither signal and an optical transmitter.

Abstract: Features related to a system and method for scheduling a resources to perform discrete tasks are described. The scheduling features include generating schedules predicted to appeal to the tasked resource (e.g., delivery partner) such as by time, day of the week, location, item types, etc. Using machine learning, the schedule and terms thereof can be dynamically generated to suit the tastes of each tasked resource and the overall demand for services. Using historical data, the modeling also accounts for likelihood an offer will be accepted and risk of cancellation for a given resource. The machine learning may be based on a mixed integer problem as constrained by partner and system capacity parameters.

Abstract: Embodiments of this disclosure provide a method and apparatus for monitoring a modulation depth of a dither signal and an optical transmitter.

Abstract: Embodiments of this disclosure provide a method and apparatus for establishing a transmission impairment decomposition model for a Raman amplified system and a system. The method includes: converting a Jones vector of a test signal after passing through a Raman amplified system into a Stokes vector; calculating transmission impairments to which the test signal is subjected by using the Stokes vector according to a pre-established transmission impairment decomposition model; and substituting values of the transmission impairments into the pre-established transmission impairment decomposition model to obtain a complete transmission impairment decomposition model used for estimating transmission impairments.