Polar Encoder Bit Type Lookup for Low-Latency 5G Coding
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Solution Overview
Problem
Existing Polar encoders or decoders in 5G systems face prolonged latency due to the need for multiple iterations through sequentially connected circuit blocks, which results in impractical data storage requirements for precomputed Polar codes to accommodate all subscribers in a transmission time interval.
Innovation Solution
A circuit for Polar code generation or decoding that includes a processor and memory to store lookup tables, allowing for the determination of bit types based on reliability indices and code parameters, enabling the generation of Polar codes in a single loop, thereby reducing latency and eliminating the need for large precomputed code libraries.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If multiple sequentially connected circuit blocks are used for Polar code generation, then each bit position can be processed with dedicated circuit blocks for CRC attachment, interleaving, puncturing, parity insertion, padding, and sorting, but this results in prolonged latency due to multiple iterations of bit positions
Solution Approach 1:
The patent pre-calculates and stores reliability indices for all bit positions in lookup tables before encoding begins. This preliminary action allows the encoder to quickly determine bit types during encoding without performing complex calculations, thereby reducing latency while maintaining accuracy in bit type determination
Solution Approach 2:
The patent divides the code generation process into separate functional modules: reliability index lookup, bit type determination logic, and code generation. Each module operates independently with defined interfaces, allowing parallel processing and reducing the sequential iteration overhead that causes latency
2Productivity
If precomputed Polar codes are stored in memory to avoid multiple iterations, then encoding speed can be improved, but this requires a prohibitively large data store to accommodate all codes for all subscribers in one transmission time interval
Solution Approach 1:
The patent changes the approach from storing complete precomputed codes to storing only reliability indices and bit type indicators. By changing what parameters are stored (from full code sequences to compact metadata), the system achieves fast encoding without requiring prohibitively large memory storage
Solution Approach 2:
Instead of storing actual code sequences for all possible subscriber combinations, the patent stores compact templates containing reliability indices and bit type patterns. These templates can be efficiently copied and applied to generate codes for different subscribers, reducing memory requirements while maintaining encoding speed
3Loss of time
If a single loop iteration is used for code generation, then latency is reduced, but this requires real-time determination of bit types based on reliability indices without relying on precomputed code libraries
Solution Approach 1:
The patent performs complex reliability index calculations and stores them in lookup tables before the single-loop encoding process. This preliminary action simplifies the real-time processing during encoding, as the processor only needs to retrieve pre-stored indices and apply simple bit type determination logic, reducing the complexity of real-time operations
Solution Approach 2:
The patent introduces lookup tables as an intermediary structure between the reliability indices and the bit type determination logic. This intermediary organizes and pre-processes the data, allowing the single-loop processor to efficiently determine bit types without directly implementing complex reliability calculations, thereby reducing real-time processing complexity
Data Source
AI summary
Embodiments described herein provide a code generation mechanism (FIG. 3, 301) in a Polar encoder (FIG. 2, 204) to determine a bit type (FIG. 3, 312) corresponding to each coded bit in the Polar code before sending the data bits for encoding (FIG. 3, 303). For example, each bit in the Polar code is determined to have a bit type of a frozen bit, parity bit, an information bit, or a cyclic redundancy check (CRC) bit based at least on the respective reliability index of the bit from a pre-computed reliability index lookup table (FIG. 4A, 411). In this way, the bit type determination can be completed in one loop by iterating the list of entries in the pre-computed reliability index lookup table.