A Flexible Channel Coding Approach for Short-Length Codewords

TL;DR

This paper presents a flexible channel coding framework for short codewords that balances error rate performance by adjusting a single parameter, combining convolutional coding with linear combinations and energy allocation.

Contribution

It introduces a novel coding scheme that allows easy tradeoff adjustments without full redesign, using EXIT chart analysis and simulations for validation.

Findings

Adjusts error rate performance efficiently

Maintains lower error floors at very low bit-error rates

Slight performance penalty at mid-range bit-error rates

Abstract

This letter introduces a novel channel coding design framework for short-length codewords that permits balancing the tradeoff between the bit error rate floor and waterfall region by modifying a single real-valued parameter. The proposed approach is based on combining convolutional coding with a $q$-ary linear combination and unequal energy allocation, the latter being controlled by the aforementioned parameter. EXIT charts are used to shed light on the convergence characteristics of the associated iterative decoder, which is described in terms of factor graphs. Simulation results show that the proposed scheme is able to adjust its end-to-end error rate performance efficiently and easily, on the contrary to previous approaches that require a full code redesign when the error rate requirements of the application change. Simulations also show that, at mid-range bit-error rates, there is a small performance penalty with respect to the previous approaches. However, the EXIT chart analysis and the simulation results suggest that for very low bit-error rates the proposed system will exhibit lower error floors than previous approaches.