Multi-stage Phase Estimation for High-order QAM
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Solution Overview
Problem
High-order QAM signals in optical communication systems face challenges with laser phase noise tolerance due to the complexity of conventional feed-forward blind carrier phase estimation algorithms, which are difficult to expand for high-order modulation formats, leading to increased implementation complexity and cost.
Innovation Solution
A multi-stage phase estimation method and apparatus where each stage has a different average time window length, using a plurality of metric computation modules to compute distance metrics and select search phase angles, reducing the total number of phase angles needed and overcoming the pattern effect, thereby lowering implementation complexity and cost.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If conventional feed-forward blind carrier phase estimation algorithms are used for high-order QAM signals, then the spectral efficiency is improved, but the implementation complexity increases significantly
Solution Approach 1:
The patent divides the single-stage phase estimation process into multiple stages, where each stage performs partial phase estimation with fewer phase angles. This segmentation reduces the computational complexity at each stage while maintaining the overall estimation accuracy needed for high-order QAM signals, thereby enabling spectral efficiency improvement without excessive implementation complexity.
2Reliability
If the number of phase angles in phase search is increased to improve phase noise tolerance, then the laser phase noise tolerance is improved, but the implementation complexity increases
Solution Approach 1:
The patent segments the phase search process into multiple stages, distributing the total phase angle search across stages. Each stage uses a reduced set of phase angles compared to a single-stage approach, reducing per-stage complexity while collectively achieving the phase noise tolerance required for reliable high-order QAM signal reception.
Solution Approach 2:
Each stage performs partial phase estimation with a subset of phase angles rather than exhaustively searching all possible phases in one step. This partial action at each stage, when combined across multiple stages, achieves the necessary phase noise tolerance without requiring the full computational burden in a single operation.
3Ease of operation
If identical average time window lengths are used in multi-stage configuration, then the algorithm simplicity is maintained, but the pattern effect cannot be effectively overcome
Solution Approach 1:
The patent applies different average time window lengths to different stages of the phase estimation process. Earlier stages use longer time windows to mitigate pattern effects, while later stages use shorter windows for refined estimation. This local differentiation of window lengths optimizes each stage's performance, effectively overcoming pattern effects while maintaining algorithmic clarity.
Data Source
AI summary
The embodiments provide a multi-stage phase estimation method and apparatus. The apparatus is a multi-stage phase estimation configuration. Each stage of the phase estimation configuration includes metric computation modules. Each of the metric computation modules computing a distance metric and search phase angles according to an input signal and an initial search phase angle or a search phase angle of the former stage phase estimation configuration. The number of the metric computation modules is equal to that of the search phase angles of this stage. A selection module selects the search phase angle corresponding to the minimal distance metric as the phase estimation result output of this stage according to the computation results of all metric computation modules. The average time window length of the former stage phase estimation configuration is larger than that of the subsequent stage phase estimation configuration.