Combating Error Propagation in Window Decoding of Braided Convolutional Codes

TL;DR

This paper proposes new decoding techniques for braided convolutional codes that significantly reduce error propagation and computational complexity, improving performance in streaming applications.

Contribution

Introduction of a window extension algorithm and resynchronization mechanism to mitigate error propagation in sliding window decoding of BCCs.

Findings

Error performance improved by up to three orders of magnitude

Reduced computational complexity through a soft bit-error-rate stopping rule

Effective mitigation of error propagation in streaming scenarios

Abstract

In this paper, we study sliding window decoding of braided convolutional codes (BCCs) in the context of a streaming application, where decoder error propagation can be a serious problem. A window extension algorithm and a resynchronization mechanism are introduced to mitigate the effect of error propagation. In addition, we introduce a soft bit-error-rate stopping rule to reduce computational complexity, and the tradeoff between performance and complexity is examined. Simulation results show that, using the proposed window extension algorithm and resynchronization mechanism, the error performance of BCCs can be improved by up to three orders of magnitude with reduced computational complexity.