TBCC Decoding With Trace-Back Convergence Termination

Resolve Bottlenecks,
Find Innovative Solutions
Generate Solutions

Solution Overview

Problem

Existing decoding algorithms for tail-biting convolutional codes (TBCCs) in wireless communications require a large number of iterations and memory, which increases complexity and decoding time, limiting efficiency in forward error correction schemes.

Innovation Solution

A novel TBCC decoding algorithm that implements an early termination condition based on a trace-back convergence check (TCC), reducing the number of iterations and trace-backs by sorting paths by state metric values and terminating early when a tail-biting path is found, thereby decreasing the computational resources needed for decoding.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Reliability

If existing decoding algorithms for tail-biting convolutional codes are used, then decoding accuracy is maintained, but the number of iterations and memory consumption increase, leading to higher complexity and longer decoding time

Engineering Contradiction:
Improvedecoding accuracyVSAvoidnumber of iterations and memory consumption
Core Design Contradiction:
ReliabilityVSDevice complexity

Solution Approach 1:

The patent applies preliminary action by performing a convergence check before completing the full decoding process. The algorithm checks whether the trace-back has converged to a valid tail-biting path earlier in the decoding process, allowing it to terminate before completing all predetermined iterations. This preliminary check prevents unnecessary computations and memory allocations that would otherwise be required to complete the full iteration cycle, thereby reducing complexity while maintaining decoding accuracy.

Inventive Principle:
Principle #10Preliminary action

Solution Approach 2:

The patent implements dynamics by making the decoding process adaptive rather than static. The number of iterations is dynamically adjusted based on the convergence status of the trace-back process. When convergence is detected, the algorithm terminates early; when convergence is not detected, it continues with additional iterations. This dynamic approach allows the system to adapt its resource consumption to the actual complexity of each decoding task, reducing average complexity while preserving reliability.

Inventive Principle:
Principle #15Dynamics

2Reliability

If existing decoding algorithms are used, then complete decoding is achieved, but decoding time increases due to the required number of iterations

Engineering Contradiction:
Improvedecoding completenessVSAvoiddecoding time
Core Design Contradiction:
ReliabilityVSLoss of time

Solution Approach 1:

The patent applies the skipping principle by rushing through the decoding process as soon as convergence is achieved. Instead of completing all predetermined iterations regardless of convergence status, the algorithm skips the remaining iterations once convergence is detected. This allows the system to complete the decoding process faster for cases where convergence occurs early, significantly reducing decoding time while ensuring that decoding completeness is maintained through the convergence check.

Inventive Principle:
Principle #21Skipping (Rushing through)

3Measurement precision

If more iterations are performed in decoding, then decoding accuracy is improved, but computational resources and memory usage increase

Engineering Contradiction:
Improvedecoding accuracyVSAvoidcomputational resources and memory usage
Core Design Contradiction:
Measurement precisionVSQuantity of substance

Solution Approach 1:

The patent applies partial action by performing only the necessary number of iterations required to achieve convergence rather than performing all predetermined iterations. The algorithm monitors convergence status and terminates the process as soon as the trace-back has converged to a valid tail-biting path, performing partial iterations when possible. This reduces the quantity of computational resources and memory usage required while maintaining decoding accuracy through the convergence-based termination criterion.

Inventive Principle:
Principle #16Partial or excessive action

Data Source

PatentEP2464022B1Decoding tail-biting convolutional codes
Publication Date: 2014.04.23 BLACKBERRY LTD
  • EP2464022B1 patent drawingFigure 1
  • EP2464022B1 patent drawingFigure 2
  • EP2464022B1 patent drawingFigure 3

AI summary

A user equipment (UE) comprising at least one component configured to decode a tail-biting convolution code (TBCC) by calculating a plurality of paths that correspond to a plurality of encoder starting states and trace back at least one of the calculated paths per at least one iteration until a trace-back convergence check (TCC) condition fails, wherein the TCC condition fails if a starting state of a first traced back path among the calculated paths is not equal to a starting state of a subsequent traced back path. Also disclosed is an access device that includes at least one component configured to decode a tail-biting convolution code (TBCC) by calculating a plurality of paths that correspond to a plurality encoder starting states in at least one iteration and trace back at least one of the calculated paths per at least one iteration until a trace-back convergence check (TCC) condition fails, wherein the TCC condition fails if a starting state of a first traced back path among the calculated paths is not equal to a starting state of a subsequent traced back path.