TY - JOUR

T1 - Non-Asymptotic Achievable Rates for Gaussian Energy-Harvesting Channels

T2 - Save-and-Transmit and Best-Effort

AU - Fong, Silas L.

AU - Yang, Jing

AU - Yener, Aylin

N1 - Funding Information:
Manuscript received May 30, 2018; revised January 13, 2019 and June 3, 2019; accepted June 20, 2019. Date of publication July 5, 2019; date of current version October 18, 2019. This work was supported by NSF under Grant CCF-1422347, Grant CNS-1526165, Grant ECCS-1650299, and Grant ECCS-1748725. This paper was presented in part at the 2018 IEEE International Symposium on Information Theory.
Funding Information:
This work was supported by NSF under Grant CCF-1422347, Grant CNS-1526165, Grant ECCS-1650299, and Grant ECCS- 1748725.
Publisher Copyright:
© 1963-2012 IEEE.

PY - 2019/11

Y1 - 2019/11

N2 - An additive white Gaussian noise energy-harvesting channel with an infinite-sized battery is considered. The energy arrival process is modeled as a sequence of independent and identically distributed random variables. The channel capacity $\frac {1}{2}\log (1+P)$ is achievable by the so-called best-effort and save-and-transmit schemes where $P$ denotes the battery recharge rate. This paper analyzes the save-and-transmit scheme whose transmit power is strictly less than $P$ and the best-effort scheme as a special case of save-and-transmit without a saving phase. In the finite blocklength regime, we obtain new non-asymptotic achievable rates for these schemes that approach the capacity with gaps vanishing at rates proportional to /\sqrt {n}$ and $({(\log n)/n})^{1/2}$ respectively where $n$ denotes the blocklength. The proof technique involves analyzing the escape probability of a Markov process. When $P$ is sufficiently large, we show that allowing the transmit power to back off from $P$ can improve the performance for save-and-transmit. The results are extended to a block energy arrival model where the length of each energy block $L$ grows sublinearly in $n$. We show that the save-and-transmit and best-effort schemes achieve coding rates that approach the capacity with gaps vanishing at rates proportional to $\sqrt {L/n}$ and $({\max \{\log n, L\}/n})^{1/2}$ , respectively.

AB - An additive white Gaussian noise energy-harvesting channel with an infinite-sized battery is considered. The energy arrival process is modeled as a sequence of independent and identically distributed random variables. The channel capacity $\frac {1}{2}\log (1+P)$ is achievable by the so-called best-effort and save-and-transmit schemes where $P$ denotes the battery recharge rate. This paper analyzes the save-and-transmit scheme whose transmit power is strictly less than $P$ and the best-effort scheme as a special case of save-and-transmit without a saving phase. In the finite blocklength regime, we obtain new non-asymptotic achievable rates for these schemes that approach the capacity with gaps vanishing at rates proportional to /\sqrt {n}$ and $({(\log n)/n})^{1/2}$ respectively where $n$ denotes the blocklength. The proof technique involves analyzing the escape probability of a Markov process. When $P$ is sufficiently large, we show that allowing the transmit power to back off from $P$ can improve the performance for save-and-transmit. The results are extended to a block energy arrival model where the length of each energy block $L$ grows sublinearly in $n$. We show that the save-and-transmit and best-effort schemes achieve coding rates that approach the capacity with gaps vanishing at rates proportional to $\sqrt {L/n}$ and $({\max \{\log n, L\}/n})^{1/2}$ , respectively.

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U2 - 10.1109/TIT.2019.2927006

DO - 10.1109/TIT.2019.2927006

M3 - Article

AN - SCOPUS:85077504740

VL - 65

SP - 7233

EP - 7252

JO - IRE Professional Group on Information Theory

JF - IRE Professional Group on Information Theory

SN - 0018-9448

IS - 11

M1 - 8756021

ER -