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Green and Smart Communications with Energy Harvesting: A Signal Processing Approach

Total Cost €


EC-Contrib. €






Project "GRENHAS" data sheet

The following table provides information about the project.


Organization address
address: -
postcode: 41296

contact info
title: n.a.
name: n.a.
surname: n.a.
function: n.a.
email: n.a.
telephone: n.a.
fax: n.a.

 Coordinator Country Sweden [SE]
 Project website
 Total cost 185˙857 €
 EC max contribution 185˙857 € (100%)
 Programme 1. H2020-EU.1.3.2. (Nurturing excellence by means of cross-border and cross-sector mobility)
 Code Call H2020-MSCA-IF-2014
 Funding Scheme MSCA-IF-EF-ST
 Starting year 2015
 Duration (year-month-day) from 2015-03-01   to  2017-02-28


Take a look of project's partnership.

# participants  country  role  EC contrib. [€] 


 Project objective

Efficient usage of energy resources is a growing concern in today's communication systems. Solutions that consider energy harvesting, where nodes in a communication system utilize other available energy sources, such as solar, wind power or man made signals, instead of completely relying on a fixed battery or the power from the grid, offer a promising perspective. Such approaches have a wide range of applications including wireless sensor networks, smart homes and smart cities. Understanding the information transfer capabilities of communication systems with energy harvesting features have been the attention of a number of recent works. At the moment the main line of research on the subject is typically done in an information theoretic framework with the rate maximization criterion. This line of work is important for understanding the fundamental limits in energy harvesting systems, yet it falls short in applicability in the context of practical scenarios. Here we propose an alternative estimation theoretic perspective where the problem is investigated within a practical signal processing framework. We will focus on efficient transmission and resource allocation strategies. Practical receiver structures with linear filtering, low complexity designs such as linear precoders, power allocation methods will be important ingredients in our work. The resulting solutions will complement the existing information theoretic solutions, and contribute to creating future green and smart communication systems.


year authors and title journal last update
List of publications.
2017 Du, R., Ozcelikkale, A., Fischione, C. and Xiao, M.
Optimal Energy Beamforming and Data Routing for Immortal Wireless Sensor Networks
published pages: , ISSN: , DOI:
2017 IEEE International Conference on Communications (ICC) (2017) 2019-07-23
2016 Michael A. Andersson, Ayca Ozcelikkale, Martin Johansson, Ulrika Engstrom, Andrei Vorobiev, Jan Stake
Feasibility of Ambient RF Energy Harvesting for Self-Sustainable M2M Communications Using Transparent and Flexible Graphene Antennas
published pages: 5850-5857, ISSN: 2169-3536, DOI: 10.1109/ACCESS.2016.2604078
IEEE Access 4 2019-07-23
2017 A. Özçelikkale, T. McKelvey, and M. Viberg
Transmission strategies for remote estimation with an energy harvesting sensor
published pages: , ISSN: 1536-1276, DOI:
IEEE Transactions on Wireless Communications 2019-07-23
2017 Xu, X., Ozcelikkale, A., McKelvey, T. and Viberg, M.
Simultaneous Information and Power Transfer under a Non-Linear RF Energy Harvesting Model
published pages: , ISSN: , DOI:
2017 IEEE International Conference on Communications Workshops (ICC) (2017) 2019-07-23

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The information about "GRENHAS" are provided by the European Opendata Portal: CORDIS opendata.

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