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Article . 2020
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https://doi.org/10.1109/isit44...
Article . 2020 . Peer-reviewed
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Article . 2020
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Article . 2020
License: arXiv Non-Exclusive Distribution
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Noise Recycling

Authors: Cohen, Alejandro; Solomon, Amit; Duffy, Ken R.; Médard, Muriel;

Noise Recycling

Abstract

We introduce Noise Recycling, a method that substantially enhances decoding performance of orthogonal channels subject to correlated noise without the need for joint encoding or 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. The estimate is recycled to reduce the Signal to Noise Ratio (SNR) of an orthogonal channel that is experiencing correlated noise and so improve the accuracy of its decoding. In this design, channels only aid each other only through the provision of noise estimates post-decoding. For a system with arbitrary noise correlation between orthogonal channels experiencing potentially distinct conditions, we introduce an algorithm that determines a static decoding order that maximizes total effective SNR. We prove that this solution results in higher effective SNR than independent decoding, which in turn leads to a larger rate region. We derive upper and lower bounds on the capacity of any sequential decoding of orthogonal channels with correlated noise where the encoders are independent and show that those bounds are almost tight. We numerically compare the upper bound with the capacity of jointly Gaussian noise channel with joint encoding and decoding, showing that they match. Simulation results illustrate that Noise Recycling can be employed with any combination of codes and decoders, and that it gives significant Block Error Rate (BLER) benefits when applying the static predetermined order used to enhance the rate region. We further establish that an additional BLER improvement is possible through Dynamic Noise Recycling, where the lead channel is not pre-determined but is chosen on-the-fly based on which decoder provides the most confident decoding.

Countries
United States, Ireland
Keywords

FOS: Computer and information sciences, Computer Science - Information Theory, Information Theory (cs.IT)

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citations
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
5
Top 10%
Average
Average
Green