Adaptive BitLabeling Design for Probabilistic Shaping Based on Residual Source Redundancy
Abstract
:1. Introduction
 By studying the effects of bitlabeling in JSCCM systems, it is found that good bitlabelings for different source codes or different source probabilities could be different.
 Based on the achievable system rate analysis, a new shaping scheme for the JSCCM system is proposed by optimizing the bitlabeling.
 In contrast to the fixed Gray labeling [16], the adaptive design of bitlabelings for the JSCCM system is proposed according to the source codes and the source probabilities. Since it is much simpler to switch between labelings than to optimize the sourcechannel code pairs for different source probabilities, it is attractive for systems with changing source statistics.
2. System Model
3. Analysis and Design of BitLabeling
3.1. Effects of BitLabelings
3.2. An Adaptive Design Scheme of BitLabeling
Algorithm 1 Adaptive BitLabeling Design 
Require: $p,{B}_{s},R,\mathsf{\Delta},{\varphi}_{ini}$

4. Experimental Results
5. Conclusions
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Conflicts of Interest
Abbreviations
AWGN  Additive white Gaussian noise 
BER  Bit error rate 
BICM  Bit interleaved coded modulation 
DM  Distribution matcher 
JSCC  Joint sourcechannel coding 
JSCCM  Joint sourcechannel coded modulation 
PAS  Probabilistic amplitude shaping 
PEG  Progressive edge growth 
QAM  Quadrature amplitude modulation 
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Source Probability  Source Code  Target Rate (Bits/Symbol)  Optimized Labeling 

$p=0.05$  ${\mathbf{B}}^{s,1}$  6  ${L}_{opt1}$ 
$p=0.05$  ${\mathbf{B}}^{R4JA}$  6  ${L}_{opt2}$ 
$p=0.03$  ${\mathbf{B}}^{s,2}$  8  ${L}_{opt3}$ 
$p=0.03$  ${\mathbf{B}}^{s,3}$  8  ${L}_{opt2}$ 
$p=0.94$  ${\mathbf{B}}^{s,1}$  6  ${L}_{opt4}$ 
$p=0.94$  ${\mathbf{B}}^{R4JA}$  6  ${L}_{opt2}$ 
$p=0.98$  ${\mathbf{B}}^{s,2}$  8  ${L}_{opt5}$ 
$p=0.98$  ${\mathbf{B}}^{s,3}$  8  ${L}_{opt6}$ 
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Chen, C.; Chen, Q.; Liu, S.; Zhou, L. Adaptive BitLabeling Design for Probabilistic Shaping Based on Residual Source Redundancy. Entropy 2023, 25, 586. https://doi.org/10.3390/e25040586
Chen C, Chen Q, Liu S, Zhou L. Adaptive BitLabeling Design for Probabilistic Shaping Based on Residual Source Redundancy. Entropy. 2023; 25(4):586. https://doi.org/10.3390/e25040586
Chicago/Turabian StyleChen, Chen, Qiwang Chen, Sanya Liu, and Lin Zhou. 2023. "Adaptive BitLabeling Design for Probabilistic Shaping Based on Residual Source Redundancy" Entropy 25, no. 4: 586. https://doi.org/10.3390/e25040586