Mao, Wei and Hassibi, Babak (2017) Capacity Analysis of Discrete Energy Harvesting Channels. IEEE Transactions on Information Theory, 63 (9). pp. 5850-5885. ISSN 0018-9448. doi:10.1109/TIT.2017.2726070. https://resolver.caltech.edu/CaltechAUTHORS:20170712-150437770
![]() |
PDF
- Submitted Version
See Usage Policy. 970kB |
Use this Persistent URL to link to this item: https://resolver.caltech.edu/CaltechAUTHORS:20170712-150437770
Abstract
We study the channel capacity of a general discrete energy harvesting channel with a finite battery. Contrary to traditional communication systems, the transmitter of such a channel is powered by a device that harvests energy from a random exogenous energy source and has a finite-sized battery. As a consequence, at each transmission opportunity, the system can only transmit a symbol whose energy is no more than the energy currently available. This new type of power supply introduces an unprecedented input constraint for the channel, which is simultaneously random, instantaneous, and influenced by the full history of the inputs and the energy harvesting process. Furthermore, naturally, in such a channel, the energy information is observed causally at the transmitter. Both of these characteristics pose great challenges for the analysis of the channel capacity. In this paper, we use techniques developed for channels with side information and finite-state channels, to obtain lower and upper bounds on the capacity of energy harvesting channels. In particular, in a general case with Markov energy harvesting processes, we use stationarity and ergodicity theory to compute and optimize the achievable rates for the channels, and derive a series of computable capacity upper and lower bounds.
Item Type: | Article | ||||||||||||||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
Related URLs: |
| ||||||||||||||||||
ORCID: |
| ||||||||||||||||||
Additional Information: | © 2017 IEEE. Manuscript received June 19, 2016; revised April 18, 2017; accepted June 21, 2017. Date of publication July 12, 2017; date of current version August 16, 2017. This work was supported in part by the National Science Foundation under Grant CNS-0932428, Grant CCF-1018927, Grant CCF-1423663, and Grant CCF-1409204, in part by a grant from Qualcomm Inc., in part by the NASA’s Jet Propulsion Laboratory through the President and Director’s Fund, in part by King Abdulaziz University, and in part by the King Abdullah University of Science and Technology. This paper was presented in part at the 2013 and 2015 IEEE International Symposiums on Information Theory [1], [2], and the 2014 IEEE Information Theory Workshop [3]. | ||||||||||||||||||
Funders: |
| ||||||||||||||||||
Subject Keywords: | Channel capacity, energy harvesting, causal CSIT, finite state channel, ergodicity | ||||||||||||||||||
Issue or Number: | 9 | ||||||||||||||||||
DOI: | 10.1109/TIT.2017.2726070 | ||||||||||||||||||
Record Number: | CaltechAUTHORS:20170712-150437770 | ||||||||||||||||||
Persistent URL: | https://resolver.caltech.edu/CaltechAUTHORS:20170712-150437770 | ||||||||||||||||||
Official Citation: | W. Mao and B. Hassibi, "Capacity Analysis of Discrete Energy Harvesting Channels," in IEEE Transactions on Information Theory, vol. 63, no. 9, pp. 5850-5885, Sept. 2017. doi: 10.1109/TIT.2017.2726070 | ||||||||||||||||||
Usage Policy: | No commercial reproduction, distribution, display or performance rights in this work are provided. | ||||||||||||||||||
ID Code: | 79029 | ||||||||||||||||||
Collection: | CaltechAUTHORS | ||||||||||||||||||
Deposited By: | Kristin Buxton | ||||||||||||||||||
Deposited On: | 13 Jul 2017 01:38 | ||||||||||||||||||
Last Modified: | 15 Nov 2021 17:45 |
Repository Staff Only: item control page