Low-Complexity Multi-Symbol LLR Calculation for Optical Receivers
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Solution Overview
Problem
Current optical communication systems face challenges in increasing capacity, particularly in long-haul transmissions, where higher-order modulation schemes like 12 QAM are needed to achieve 200 Gb/s, but existing methods for computing log-likelihood ratios (LLRs) in dual-12 QAM systems are computationally demanding and expensive due to the requirement of jointly minimizing four-dimensional (4D) square Euclidean distances (SEDs).
Innovation Solution
The proposed solution involves a receiver apparatus and method that independently selects nearest candidate symbols for each 12 QAM symbol based on two-dimensional (2D) SEDs, reducing computational complexity by computing separate 2D SEDs for each symbol, and determining soft decision values by summing or subtracting minimum distance metrics, depending on valid or invalid symbol combinations, thereby reducing the complexity of LLR calculations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If higher-order modulation schemes like 12 QAM are employed to increase transmission capacity, then the data rate is improved, but the computational complexity of LLR calculation increases
Solution Approach 1:
The patent segments the joint 4D SED minimization problem into separate 2D SED minimization problems for each 12 QAM symbol. Instead of treating the dual-12 QAM super-symbol as a single complex entity requiring joint optimization, the invention divides it into independent sub-problems that can be solved separately, significantly reducing computational complexity while maintaining performance.
Solution Approach 2:
The invention extracts and removes the joint minimization requirement from the LLR calculation process. By taking out the constraint that requires simultaneous optimization of both symbols, the patent allows independent processing of each symbol's constellation points, eliminating the computationally expensive 4D search space exploration.
2Measurement precision
If joint minimization of four-dimensional square Euclidean distances is performed for dual-12 QAM systems, then accurate soft decision values are obtained, but hardware costs and power consumption increase
Solution Approach 1:
The patent segments the hardware implementation into separate processing units for each 12 QAM symbol. Each unit independently calculates 2D SEDs and performs minimization for its assigned symbol, avoiding the need for complex hardware that would simultaneously handle 4D distance calculations and joint optimization, thus reducing hardware complexity while preserving accuracy.
Solution Approach 2:
The invention replaces expensive, complex joint minimization hardware with simpler, independent 2D minimization units. Each unit performs a less computationally intensive task that can be implemented with lower-cost hardware components, achieving the same functional outcome with reduced hardware investment.
3Measurement precision
If joint minimization of four-dimensional square Euclidean distances is performed, then accurate LLR values are computed, but power consumption increases
Solution Approach 1:
The patent segments the power-consuming minimization operation into separate, independent tasks for each symbol. By dividing the computational workload and allowing parallel or sequential execution of simpler 2D minimization operations, the invention reduces the peak power consumption and total energy required compared to the monolithic 4D joint minimization approach.
Data Source
AI summary
An apparatus comprising a receiver configured to receive a super-symbol comprising a first modulation symbol and a second modulation symbol, wherein the first modulation symbol comprises a first modulation format, and wherein the second modulation symbol comprises a second modulation format, and a processor coupled to the receiver and configured to select, for the first modulation symbol, a first nearest candidate symbol from a first set of candidate symbols associated with the first modulation format, select, for the second modulation symbol, a second nearest candidate symbol independent of the first nearest candidate symbol from a second set of candidate symbols associated with the second modulation format, and determine a soft decision value for a first hit in the super-symbol according to the first nearest candidate symbol and the second nearest candidate symbol.