Reduced State MLSE Decoder for PAM4 Signaling
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Solution Overview
Problem
Traditional Maximal Likelihood Sequence Estimation (MLSE) techniques for PAM4 signaling in high-speed serial communication systems are resource-intensive, leading to high complexity, area, and power consumption, which becomes a challenge for implementing at very high data rates.
Innovation Solution
The proposed solution involves reducing the complexity of the MLSE algorithm by reducing the trellis structure from a 4:4 configuration to a 2:2 configuration, where states are grouped into even and odd states, and each state maintains sub-state information and scores, thereby reducing the number of transitions to be considered.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If traditional MLSE techniques with 4:4 trellis structure are used, then symbol error rate performance is improved, but device complexity, area, and power consumption increase significantly
Solution Approach 1:
The patent segments the 4:4 trellis structure into multiple 2:2 sub-trellises by grouping states into even and odd categories. This segmentation reduces the complexity of individual trellis sections while maintaining overall decoding performance through parallel processing of multiple sub-trellises.
Solution Approach 2:
The patent merges multiple reduced-state trellises (2:2 configuration) to achieve the performance of a full 4:4 trellis. By combining results from multiple sub-trellises, the system maintains symbol error rate performance while reducing the complexity burden on any single decoding section.
2Reliability
If traditional MLSE techniques with 4:4 trellis structure are used, then symbol error rate performance is improved, but power consumption increases
Solution Approach 1:
By segmenting the trellis into smaller 2:2 sub-trellises, the patent reduces the computational load and power consumption of each processing stage. The segmentation allows for more efficient resource utilization while achieving the same overall decoding performance.
3Reliability
If traditional MLSE techniques with 4:4 trellis structure are used, then symbol error rate performance is improved, but latency increases
Solution Approach 1:
The segmentation of the trellis structure into parallel 2:2 sub-trellises enables concurrent processing of multiple state transitions. This parallelism reduces the time required to complete the decoding process while maintaining the accuracy benefits of MLSE.
Data Source
AI summary
A method may include: initializing four states of a trellis, the four states corresponding to the four possible symbol levels in PAM4, where a respective initial state starts with an initial score and an empty survivor path; for respective possible transitions between the four initial states and four possible current states of the trellis, determining expected PAM4 symbols; determining error associated with respective transitions based on differences between a received PAM4 symbol and the expected PAM4 symbols; discarding transitions where the error indicates a difference greater than a single signal level, and keep the other transitions; and for respective current state groups of a two state trellis, determining one of the incoming transitions that was not discarded having the highest likelihood of being associated with a transmitted symbol.