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Abstract

Introduction

In a recent study, a generalized implicit transmission (GIT) technique that can transmit multiple implicit sequences while transmitting a single explicit sequence over a channel has been introduced. Instead of considering all sequences as independent, as in the previous study, this study considers the explicit sequence and all implicit sequences of a GIT collectively as a single code, referred to as a GIT coding scheme.

Methods

The overall code rate and the inherent coding gain achieved by a GIT coding scheme due to the transmission of information implicitly, are discussed.

The overall code rate and the inherent coding gain achieved by a GIT coding scheme, due to the transmission of information, is discussed implicitly. A GIT coding scheme constructed from a rate code to function as a rate code, on average, transmits number of codewords of a rate code for every single codeword transmitted over the channel by transmitting number of codewords over all implicit sequences. A simple way to convert existing practical codes into GIT coding schemes is also discussed.

Results

The numerical results presented with the LDPC codes employed in the WiFi and the 5G standards demonstrate that GIT coding schemes can achieve very high coding gains over conventional codes while functioning as high-rate codes.

Conclusion

Due to its ability to transmit the majority of information implicitly, which does not require any additional bandwidth or transmitted power, it is demonstrated here that GIT coding schemes can operate in the so-called unreachable region relative to the Shannon-Hartley bound.

© 2026 The Author(s). Published by Bentham Science Publishers.
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2026-01-05
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Analysis of Generalized Implicit Transmission
Bentham Science Publishers ; https://doi.org/10.2174/0122103279435726251111053110
/content/journals/swcc/10.2174/0122103279435726251111053110
/content/journals/swcc/10.2174/0122103279435726251111053110
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  • Article Type:     Research Article
Keywords: inherent coding gain ; LDPC codes ; performance enhancement ; Implicit transmission ; channel capacity ; iterative decoding ; conditional mutual information ; shannon limit

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