Digital Signal Processor Nonlinearity Compensation via Down-Sampling
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Solution Overview
Problem
Current digital signal processing techniques for compensating nonlinear optical effects in optical fiber communication systems have high computational complexity, making them difficult to implement in digital signal processors (DSPs) of optical data transceivers and receivers, and perturbation-based optical nonlinearity compensation (PNC) while less complex, still poses challenges due to its complexity for coherent optical fiber communication systems.
Innovation Solution
The implementation of a digital signal processor that calculates multiplicative factors for correcting optical data signals by down-sampling and interpolating, using convolutions of channel coefficients with products of optical data signals, reducing computational complexity through decimation and anti-alias filtering, and performing pre- and post-compensation of nonlinear optical effects in optical data transmitters and receivers respectively.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If perturbation-based optical nonlinearity compensation (PNC) is implemented in DSPs, then digital compensation of nonlinear optical effects is achieved, but computational complexity remains high making implementation difficult
Solution Approach 1:
The patent segments the calculation of multiplicative factors by separating full-rate signal processing from reduced-rate processing. It divides the computation into: (1) calculating factors at a reduced symbol rate using fewer multiplications, and (2) interpolating these factors to obtain full-rate correction values. This segmentation reduces the number of complex multiplications required while maintaining compensation effectiveness.
Solution Approach 2:
The patent changes the parameter of symbol rate from full rate to reduced rate during the calculation phase. By evaluating multiplicative factors at a reduced symbol rate (lower than the original symbol rate) and then interpolating to recover full-rate values, the system reduces computational complexity. This parameter change transforms a high-complexity full-rate calculation into a lower-complexity reduced-rate calculation followed by simple interpolation.
2Ease of manufacture
If computational complexity of DSP is reduced for PNC implementation, then ease of manufacture and cost are improved, but compensation effectiveness may be degraded
Solution Approach 1:
The patent introduces interpolation as an intermediary process between reduced-rate factor calculation and full-rate compensation application. The interpolator acts as a mediator that reconstructs full-rate multiplicative factors from reduced-rate values, ensuring that the compensation effectiveness is maintained despite the reduced calculation rate. This intermediary step bridges the gap between low-complexity calculation and high-fidelity compensation.
Solution Approach 2:
The patent performs preliminary calculation of multiplicative factors at a reduced rate before the actual compensation is applied. By pre-calculating factors at fewer time instants and storing them, the system prepares compensation data in advance with reduced computational effort. This preliminary action at reduced rate is followed by interpolation to generate the full-rate correction values needed for actual signal compensation.
Data Source
AI summary
An apparatus includes a digital signal processor to perform perturbation-based optical nonlinearity compensation of optical data signals of a communication stream. The digital signal processor includes first digital circuits to calculate multiplicative factors for corrections to the optical data signals from products of values of the optical data signals at a reduced set of times. The reduced set is a down-sampling of the sequence of consecutive symbol times of the communication stream. The digital signal processor also includes second digital circuits to calculate the multiplicative factors for corrections to the optical data signals at the consecutive symbol times by interpolating the multiplicative factors evaluated at the reduced set of times.