Polar Decoding for Deletion and Insertion Error Correction
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Solution Overview
Problem
Current communication systems lack effective coding schemes for correcting symbol deletion and insertion errors, which lead to synchronization issues and impair data transmission reliability.
Innovation Solution
The implementation of polar coding and decoding methodologies that utilize successive cancellation decoding to estimate and correct deletion and insertion errors, enhancing the system's resilience to synchronization errors and other channel impairments.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If conventional FEC codes are used to combat noise and channel fading, then reliability against noise is improved, but capability to correct symbol deletion and insertion errors is lacking
Solution Approach 1:
The patent segments the decoding process into multiple layers (at least log2(N)+1 layers) with processing nodes at each layer to handle different types of errors independently. Each layer processes specific aspects of the received signal, allowing the system to separately address noise errors and synchronization errors (deletions/insertions) through distinct decoding paths.
Solution Approach 2:
The polar code decoder is designed with multi-functionality to handle multiple types of channel errors simultaneously. The successive cancellation decoder structure can correct both random noise errors and synchronization errors (deletions and insertions) using the same coding framework, making the system universally applicable to various channel impairments without requiring separate coding schemes.
2Reliability
If polar codes are used to correct deletions and insertions, then synchronization error resiliency is improved, but decoding complexity increases
Solution Approach 1:
The patent employs dynamic adaptation in the decoding process by using successive cancellation decoding with recursive calculations. The decoder dynamically adjusts its processing based on the received signal characteristics and error patterns, allowing it to handle variable numbers of deletions and insertions efficiently without requiring a fixed, overly complex structure for all possible error scenarios.
Solution Approach 2:
The patent introduces an additional dimensional structure to the decoder by organizing processing nodes into multiple layers (at least log2(N)+1 layers) with N groups per layer. This layered architecture transforms the decoding process from a single-level operation into a multi-dimensional hierarchical structure, enabling efficient error correction while managing complexity through structured organization of processing elements.
3Reliability
If successive cancellation decoding with multiple layers is implemented, then error correction capability is improved, but computational complexity scales with block size
Solution Approach 1:
The decoder segments the computational task across multiple layers, with each layer containing N groups of processing nodes. This segmentation divides the overall complexity into manageable chunks that can be processed in parallel or sequentially across layers, reducing the computational burden at any single processing stage while maintaining overall error correction capability.
Solution Approach 2:
The patent implements a practical balance by using at least log2(N)+1 layers, which provides sufficient error correction capability without implementing unnecessarily excessive layers that would increase complexity without proportional benefit. This partial action approach achieves the necessary error correction performance while avoiding the computational overhead of a fully exhaustive multi-layer structure.
Data Source
AI summary
Disclosed are devices, systems and methods for polar coding and decoding for correcting deletion and insertion errors caused by a communication channel. One exemplary method for error correction includes receiving a portion of a block of polar-coded symbols that includes d≥2 insertion or deletion symbol errors, the block comprising N symbols, the received portion of the block comprising M symbols; estimating, based on one or more recursive calculations in a successive cancellation decoder (SCD), a location or a value corresponding to each of the d errors; and decoding, based on estimated locations or values, the portion of the block of polar-coded symbols to generate an estimate of information bits that correspond to the block of polar-coded symbols, wherein the SCD comprises at least log2(N)+1 layers, each comprising up to d2N processing nodes arranged as N groups, each of the N groups comprising up to d2 processing nodes.