On the Capacity Region of Optical Intensity Broadcast Channels

This paper investigates the capacity region of the optical intensity broadcast channels (OI-BCs), where the input is subject to a peak-intensity constraint, an average-intensity constraint, or both. By leveraging the decomposition results of several random variables, i.e., uniform, exponential, and...

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Published inIEEE transactions on communications Vol. 72; no. 4; pp. 1967 - 1982
Main Authors Yang, Sufang, Li, Longguang, Wang, Jintao
Format Journal Article
LanguageEnglish
Published New York IEEE 01.04.2024
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
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ISSN0090-6778
1558-0857
DOI10.1109/TCOMM.2023.3345384

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Abstract This paper investigates the capacity region of the optical intensity broadcast channels (OI-BCs), where the input is subject to a peak-intensity constraint, an average-intensity constraint, or both. By leveraging the decomposition results of several random variables, i.e., uniform, exponential, and truncated exponential random variables, and adopting a superposition coding (SC) scheme, the inner bound on the capacity region is derived. Then, the outer bound is derived by applying the conditional entropy power inequality (EPI). In the high signal-to-noise ratio (SNR) regime, the inner bound asymptotically matches the outer bound, thus characterizing the high-SNR asymptotic capacity region. The bounds are also extended to the general <inline-formula> <tex-math notation="LaTeX">K </tex-math></inline-formula>-user BCs without loss of high-SNR asymptotic optimality.
AbstractList This paper investigates the capacity region of the optical intensity broadcast channels (OI-BCs), where the input is subject to a peak-intensity constraint, an average-intensity constraint, or both. By leveraging the decomposition results of several random variables, i.e., uniform, exponential, and truncated exponential random variables, and adopting a superposition coding (SC) scheme, the inner bound on the capacity region is derived. Then, the outer bound is derived by applying the conditional entropy power inequality (EPI). In the high signal-to-noise ratio (SNR) regime, the inner bound asymptotically matches the outer bound, thus characterizing the high-SNR asymptotic capacity region. The bounds are also extended to the general [Formula Omitted]-user BCs without loss of high-SNR asymptotic optimality.
This paper investigates the capacity region of the optical intensity broadcast channels (OI-BCs), where the input is subject to a peak-intensity constraint, an average-intensity constraint, or both. By leveraging the decomposition results of several random variables, i.e., uniform, exponential, and truncated exponential random variables, and adopting a superposition coding (SC) scheme, the inner bound on the capacity region is derived. Then, the outer bound is derived by applying the conditional entropy power inequality (EPI). In the high signal-to-noise ratio (SNR) regime, the inner bound asymptotically matches the outer bound, thus characterizing the high-SNR asymptotic capacity region. The bounds are also extended to the general <inline-formula> <tex-math notation="LaTeX">K </tex-math></inline-formula>-user BCs without loss of high-SNR asymptotic optimality.
Author Yang, Sufang
Wang, Jintao
Li, Longguang
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Snippet This paper investigates the capacity region of the optical intensity broadcast channels (OI-BCs), where the input is subject to a peak-intensity constraint, an...
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StartPage 1967
SubjectTerms Asymptotic properties
Capacity region
Channel capacity
Channels
Encoding
High-speed optical techniques
Integrated optics
intensity modulation-direct detection
optical broadcast channel
optical wireless communication
peak- or/and average-intensity constraints
Random variables
Signal to noise ratio
Wireless communication
Title On the Capacity Region of Optical Intensity Broadcast Channels
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