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Capacity bounds for bandlimited Gaussian channels with peak-to-average-power-ratio constraint

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Yizhu Wang, Jing Zhou, Wenyi Zhang

Information Theory · Submitted 30 May 2018

abstract compiled · 2026-09-23 · no language-model review

The authors' main claim By combining our upper and lower bounds, the capacity of PAPR constrained BLGC is bounded to within a finite gap which tends to zero as the PAPR constraint tends to infinity.

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arXiv ID1805.11898 (version 2)
Pith IDEH5WKBER, Pith's permanent record of this paper and its review
CitationJing Zhou, Wenyi Zhang, Yizhu Wang. "Capacity bounds for bandlimited Gaussian channels with peak-to-average-power-ratio constraint." arXiv:1805.11898 (2018). https://pith.science/paper/EH5WKBER
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What the abstract itself states, as probabilities: claims first 0.05 · states limitation 0.33 · human participants 0.01 · controlled comparison 0.10 · randomized assignment 0.01 · states quantitative result 0.47 · compares with prior results 0.94 · mentions code or data availability 0.02.

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We revisit Shannon's problem of bounding the capacity of bandlimited Gaussian channel (BLGC) with peak power constraint, and extend the problem to the peak-to-average-power-ratio (PAPR) constrained case. By lower bounding the achievable information rate of pulse amplitude modulation with independent and identically distributed input under a PAPR constraint, we obtain a general capacity lower bound with respect to the shaping pulse. We then evaluate and optimize the lower bound by employing some parametric pulses, thereby improving the best existing result. Following Shannon's approach, capacity upper bound for PAPR constrained BLGC is also obtained. By combining our upper and lower bounds, the capacity of PAPR constrained BLGC is bounded to within a finite gap which tends to zero as the PAPR constraint tends to infinity. Using the same approach, we also improve existing capacity lower bounds for bandlimited optical intensity channel at high SNR.

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#sentencerolethe authors' own workstates the main conclusionstrength
s0 We revisit Shannon's problem of bounding the capacity of bandlimited Gaussian channel (BLGC) with peak power constraint, and extend the problem to the peak-to-average-power-ratio (PAPR) constrained case. contribution 0.60 0.84 0.05 asserted 0.95
s1 By lower bounding the achievable information rate of pulse amplitude modulation with independent and identically distributed input under a PAPR constraint, we obtain a general capacity lower bound with respect to the shaping pulse. method 0.60 0.96 0.08 asserted 1.00
s2 We then evaluate and optimize the lower bound by employing some parametric pulses, thereby improving the best existing result. method 0.44 0.96 0.08 asserted 1.00
s3 Following Shannon's approach, capacity upper bound for PAPR constrained BLGC is also obtained. contribution 0.51 0.90 0.06 asserted 1.00
s4 By combining our upper and lower bounds, the capacity of PAPR constrained BLGC is bounded to within a finite gap which tends to zero as the PAPR constraint tends to infinity. result 0.99 0.95 0.76 asserted 1.00
s5 Using the same approach, we also improve existing capacity lower bounds for bandlimited optical intensity channel at high SNR. contribution 0.51 0.93 0.06 asserted 1.00

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Every quoted sentence on this record is the authors'. Every label is from Pith's closed vocabulary, with the probability shown beside it. Every number in the measurements table is the authors', checked by code. Record as JSON

The paper
Original abstract

We revisit Shannon's problem of bounding the capacity of bandlimited Gaussian channel (BLGC) with peak power constraint, and extend the problem to the peak-to-average-power-ratio (PAPR) constrained case. By lower bounding the achievable information rate of pulse amplitude modulation with independent and identically distributed input under a PAPR constraint, we obtain a general capacity lower bound with respect to the shaping pulse. We then evaluate and optimize the lower bound by employing some parametric pulses, thereby improving the best existing result. Following Shannon's approach, capacity upper bound for PAPR constrained BLGC is also obtained. By combining our upper and lower bounds, the capacity of PAPR constrained BLGC is bounded to within a finite gap which tends to zero as the PAPR constraint tends to infinity. Using the same approach, we also improve existing capacity lower bounds for bandlimited optical intensity channel at high SNR.

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