Noise Recycling

TL;DR

Noise Recycling is a novel method that improves decoding performance in channels with correlated noise by estimating and utilizing noise information from one channel to assist another, applicable across various coding schemes.

Contribution

The paper introduces Noise Recycling, a versatile technique that enhances decoding in correlated noise environments without joint decoding, demonstrating higher rates and BLER improvements.

Findings

Higher achievable rates with noise recycling in Gauss-Markov noise models.

BLER benefits when using the same decoding order as for rate enhancement.

Short code BLER improvements via racing noise recycling with dynamic lead channel selection.

Abstract

We introduce Noise Recycling, a method that enhances decoding performance of channels subject to correlated noise without joint decoding. The method can be used with any combination of codes, code-rates and decoding techniques. In the approach, a continuous realization of noise is estimated from a lead channel by subtracting its decoded output from its received signal. This estimate is then used to improve the accuracy of decoding of an orthogonal channel that is experiencing correlated noise. In this design, channels aid each other only through the provision of noise estimates post-decoding. In a Gauss-Markov model of correlated noise, we constructive establish that noise recycling employing a simple successive order enables higher rates than not recycling noise. Simulations illustrate noise recycling can be employed with any code and decoder, and that noise recycling shows Block Error Rate (BLER) benefits when applying the same predetermined order as used to enhance the rate region. Finally, for short codes we establish that an additional BLER improvement is possible through noise recycling with racing, where the lead channel is not pre-determined, but is chosen on the fly based on which decoder completes first.