Semi-Parallel Polar Code Decoder for Lower Hardware Complexity
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Solution Overview
Problem
Polar codes require large code lengths to approach channel capacity, leading to complex and costly decoder implementations due to the need for numerous processing elements and memory elements, which increases latency and reduces efficiency in hardware implementation.
Innovation Solution
A method of decoding polar codes using a semi-parallel architecture with reduced processing elements and memory, employing a decision unit and computation block to generate estimated bits based on likelihood ratios and frozen bits, and converting data flow graphs to tree graphs for efficient decoding.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If large code lengths are used to approach channel capacity, then data transmission reliability is improved, but decoder complexity and hardware cost increase
Solution Approach 1:
The decoder is divided into multiple processing stages, where each stage processes a subset of the code bits. This segmentation allows the overall complex decoding task to be broken down into smaller, more manageable sub-tasks that can be executed in parallel or sequentially with reduced resource requirements at each stage.
Solution Approach 2:
The decoder architecture employs dynamic resource allocation where processing elements and memory resources are activated based on the current decoding stage and requirements. This dynamic approach allows the hardware to adapt its complexity to the actual needs of the decoding process, reducing unnecessary resource consumption while maintaining reliability.
2Measurement precision
If numerous processing elements and memory elements are used, then decoding accuracy is improved, but latency increases
Solution Approach 1:
The decoding process is organized into periodic stages with regular patterns of processing element activation and memory access. This periodic structure enables predictable timing behavior and allows for optimization of the critical path, reducing overall latency while maintaining the necessary processing accuracy through structured repeated operations.
Solution Approach 2:
The architecture maintains continuous processing by overlapping computation and memory access operations, and by keeping processing elements actively engaged in useful work throughout the decoding process. This eliminates idle time and ensures that the full computational capacity is utilized continuously, reducing total decoding time while maintaining accuracy.
3Productivity
If large code lengths are used, then channel capacity utilization is improved, but hardware implementation efficiency decreases
Solution Approach 1:
The processing elements and memory structures are designed to perform multiple functions across different decoding stages. The same hardware resources are reused for different computational tasks by reconfiguring their operation, which reduces the total amount of hardware needed while still supporting long code lengths that approach channel capacity.
Solution Approach 2:
The decoder architecture allows dynamic adjustment of operational parameters such as processing depth, memory allocation, and computation intensity based on the code length and channel conditions. This flexibility enables the hardware to efficiently handle variable code lengths, optimizing the balance between channel capacity utilization and implementation efficiency for different scenarios.
Data Source
AI summary
A polar code decoder includes: processing elements each receiving a pair of input values and applying a first or a second predetermined mathematical function depending on a provided function control signal; a first memory that stores at least one of the outputs from processing elements and a plurality of channel values relating to a received polar code to be decoded; a second memory that stores indices of a plurality of frozen bits each representing a bit within an information-bit vector of the polar code being decoded; and a computation block that receives a plurality of inputs from a portion of the processing elements and generates an output that is can be set to a predetermined frozen value or to a calculated value, depending on whether a current index of the bit being decoded is indicated as frozen or not frozen.