Coherent Receiver Frequency Offset Estimation

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Solution Overview

Problem

Optical communication systems face unbounded phase errors due to frequency mismatches and phase noise, leading to cycle slips that are difficult to compensate, resulting in erroneous data interpretation and increased error correction requirements.

Innovation Solution

The method involves estimating frequency offsets using SYNC bursts with known symbol sequences and periodicity, applying phase rotations to data symbol estimates, and using bounded filters to determine the most likely symbol values, thereby reducing the impact of cycle slips and eliminating the need for differential encoding.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Reliability

If unbounded phase error compensation is used to handle frequency mismatch and phase noise, then data recovery is possible in presence of large phase errors, but cycle slips occur leading to erroneous data interpretation

Engineering Contradiction:
Improvedata recovery reliabilityVSAvoiddata interpretation errors
Core Design Contradiction:
ReliabilityVSLoss of information

Solution Approach 1:

The patent applies preliminary action by using SYNC bursts with known symbol sequences before data transmission to pre-determine and compensate for frequency offset and phase error. This preliminary calibration establishes a reference frame that prevents cycle slips during subsequent data recovery, thereby maintaining data interpretation accuracy while enabling reliable recovery despite large phase errors.

Inventive Principle:
Principle #10Preliminary action

Solution Approach 2:

The patent implements feedback mechanisms where the receiver continuously monitors phase error using the known SYNC burst sequences and adjusts the phase compensation accordingly. This closed-loop feedback ensures that phase error remains bounded and prevents cycle slips, resolving the contradiction between handling large phase errors and avoiding data interpretation errors.

Inventive Principle:
Principle #23Feedback

2Reliability

If bounded filtering is applied to compensate phase error, then cycle slips are reduced, but the filtering function must be carefully designed to maintain effectiveness

Engineering Contradiction:
Improvecycle slip reductionVSAvoidfiltering function design
Core Design Contradiction:
ReliabilityVSDevice complexity

Solution Approach 1:

The patent changes the parameter of phase error from unbounded to bounded by using bounded filtering functions that constrain the phase compensation within acceptable limits. This parameter transformation reduces cycle slips while the filtering design is simplified by using standard bounded functions rather than complex unbounded compensation mechanisms.

Inventive Principle:
Principle #35Parameter changes

3Reliability

If differential encoding is used to mitigate phase error effects, then data recovery robustness improves, but system complexity increases

Engineering Contradiction:
Improvephase error robustnessVSAvoidencoding complexity
Core Design Contradiction:
ReliabilityVSDevice complexity

Solution Approach 1:

The patent extracts and compensates for phase error effects directly in the frequency domain using bounded filtering, rather than relying on differential encoding. By separating and independently handling the phase error compensation function, the system achieves phase error robustness without incorporating the complexity of differential encoding schemes.

Inventive Principle:
Principle #2Taking out (Extraction)

Data Source

PatentUS8315528B2Zero mean carrier recovery
Publication Date: 2012.11.20 CIENA CORP
  • US8315528B2 patent drawing
  • US8315528B2 patent drawing
  • US8315528B2 patent drawing

AI summary

A method of data symbol recovery in a coherent receiver of an optical communications system. Two or more SYNC bursts, having a known symbol sequence and periodicity, are processed to derive an estimate of a frequency offset Δf between a transmit laser and a Local Oscillator (LO) of the receiver. A phase rotation κ(n) is computed based on the estimate of the frequency offset Δf, and applied to a plurality of data symbol estimates to generate corresponding rotated symbol estimates. The rotated symbol estimates are then filtered to generate corresponding decision values of each data symbol.