Characterization of Blind Code Rate Recovery in Linear Block Codes

TL;DR

This paper introduces a new metric for assessing the quality of blind code rate recovery in linear block codes, deriving expressions for improved estimates in noisy environments and validating them through LDPC code simulations.

Contribution

It presents a novel metric for blind code rate recovery, derives closed-form expressions for high noise conditions, and validates the approach with LDPC code simulations.

Findings

The metric effectively characterizes recovery quality.

Derived expressions improve code rate estimates in noisy environments.

Simulation results validate the theoretical expressions.

Abstract

Forward Error Correction (FEC) is used ubiquitously in the communication pipeline. We explore noncooperative decoding where we aim to recover the code rate of a linear block code. We present a metric to characterize the quality of the code rate recovery which uses any rank based estimation technique. We derive a closed form expression for this metric in terms of the algorithmic and the environmental parameters and assert that it should be low for good recovery. We use this metric to derive an expression for a better code rate estimate in high noise conditions and compare it with existing estimates. Finally we validate the derived expression for the metric and the improved performance in the code rate estimate by simulating the recovery of a Low Density Parity Check (LDPC) code. This also enables us to derive the optimal algorithmic parameters for recovery.