International audienceLately, WSNs have attracted lot of attention due to their ubiquitous nature and their varied utilization in IOT, Cyber Physical Systems, and other emerging fields. The restricted energy related to wireless sensor networks is a considerable bottleneck of these networks. To surpass this serious limitation, the design and development of high performance and efﬁcient energy harvesting systems for WSN environments are being inspected. We present a comprehensive taxonomy of the different energy harvesting sources that can be adopted by wireless sensor networks. We discuss also many freshly suggested energy prediction models that have the ability to boost the energy harvested in wireless sensor networks. To finish, we identify some of the challenges that still need to be addressed to develop cost-effective, efﬁcient, and reliable energy harvesting systems for the WSN environment

Lagraini, Hajar

MOUHSEN, AHMED

Ouldzira, Hicham

English

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A Survey on RF Energy Harvesting-RFEH- in WSNs
Hicham Ouldzira, Hajar Lagraini, Ahmed Mouhsen
To cite this version:
Hicham Ouldzira, Hajar Lagraini, Ahmed Mouhsen. A Survey on RF Energy Harvesting-RFEH- in
WSNs. Colloque sur les Objets et systèmes Connectés, Ecole Supérieure de Technologie de Casablanca
(Maroc), Institut Universitaire de Technologie d’Aix-Marseille (France), Jun 2019, CASABLANCA,
Morocco. ￿hal-02296957￿
A Survey on RF Energy Harvesting-RFEH- in WSNs 
Hicham  Ouldzira
1
 , Hajar Lagraini
2
  ,  Ahmed Mouhsen
3 
(Auteurs 10pt centré) 
odzira@yahoo.fr 
Adresses : Laboratoire IMMIII , FST Settat, Université Hassan 1
ér
 
Abstract : Lately, WSNs have attracted lot of attention due to their ubiquitous nature and their varied utilization in 
IOT, Cyber Physical Systems, and other emerging fields. The restricted energy related to wireless sensor networks is a 
considerable bottleneck of these networks. To surpass this serious limitation, the design and development of high per-
formance and efﬁcient energy harvesting systems for WSN environments are being inspected. We present a comprehen-
sive taxonomy of the different energy harvesting sources that can be adopted by wireless sensor networks. We discuss 
also many freshly suggested energy prediction models that have the ability to boost the energy harvested in wireless 
sensor networks. To finish, we identify some of the challenges that still need to be addressed to develop cost-effective, 
efﬁcient, and reliable energy harvesting systems for the WSN environment. 
Keywords : WSN, energy harvesting , IoT.
INTRODUCTION  
Power scavenging or (Energy harvesting) is without 
any ambiguity a very captivating method for a wide 
variety of autonomous-powered microsystems. Exam-
ples of such systems are WSNs, biomedical implants, 
military monitoring devices, structure-embedded in-
strumentation, remote weather station, calculators, 
watches, Bluetooth headsets. Recently power scaveng-
ing gets a huge attention and research report number 
has kept growing. The focus of this paper is to provide 
the research community with an update of the state-of-
the-art of power scavenging from vibration, thermal, 
and RF sources. The principle of energy harvesting 
approaches can be found in Ref. [7].In the following; 
we list the energy harvesting sources (Section 2), a 
brief history of energy scavenging (Section 3), state-of-
the-art based on the review of several recently pub-
lished papers (Section 4) and Conclusion. 
 
Motivations for energy harvesting in WSNs 
It is a well-known that one of the main hitches WSNs 
face is energy[1-2]. When the power of a SN is ingest-
ed, it will no longer accomplish its role in the network 
except either the power source is changed or some 
harvesting techniques are introduced to stop the energy 
gap. The main existing power energy source adopted 
by the SNs is battery-power, but many issues are relat-
ed to batteries. First, the current that flows ingests the 
battery even if not in usage. Second, severe climate 
conditions can cease to function of batteries, causing in 
chemical leakages that may provoke many environ-
mental troubles[3]. Finally, the battery's energy capaci-
ty is restricted, and that can block or handicap the SN 
activity over a long time [4]. There are various wireless 
sensor network application scenarios where the 
lifespan of the SN varieties from months to many years 
based on the application necessities[5]. For that reason, 
the lifespan of the SNs should end many years before 
their power batteries get depleted and they become 
useless due to the deficiency of power supply. To oper-
ate continuously in most situations, SNs necessitate a 
uninterrupted power supply, either that supply is in an 
active mode to communicate and treat data or a passive 
mode when SNs go to sleep as presented in Fig.1.  
Normally, deficiency of a few SNs is not a major prob-
lem for the appropriate functioning of a WSN, but the 
damage of those SNs undoubtedly affects performance 
and overhead. Ultimately, the network cannot sur-
mount the loss of the nodes or fulfill the application's 
anticipated requests. Over time, the connected SNs will 
leak the energy kept in the storage components. The 
sensor nodes, treating, broadcasting, and data transfer 
frequency significantly influence the lifespan of the 
battery. 
 
Fig. 1. Sensor node architecture with battery 1as 
main source[6]. 
All these features support the use of power harvesting 
in wireless sensor networks. A wireless sensor network 
must be self-powering, long lasting, and almost 
maintenance free. Thus, energy harvesting may be 
defined as a technique utilized to generate energy from 
networks ambient environments to afford a continuous 
power supply for a particular SN and for the whole 
network. Moreover, we can classify 2 types of energy 
scavenging systems: (1) where ambient energy is di-
rectly transformed to electrical energy to power the 
SNs (no battery storage is necessary as represented in 
Fig. 2(a)), and (2) where the transformed electrical 
energy is first stored before being supplied to the SN as 
presented in Fig. 2(b). For the time being, wireless 
sensor network applications will remain to use nonre-
fundable and life-long batteries. That being said, for 
applications demanding high power above the lifespan 
of the wsn, the energy scavenging mechanism will 
carry out the usage of rechargeable batteries. Power 
scavenging is ultimate for applications that must persist 
for longer time periods, i.e., those that are used once 
and then always accessible, such as environmental 
monitoring systems [7]. Other applications that may 
benefit from power scavenging are those that necessi-
tate the carrying of large amounts of information to the 
base station, as is the case in multimedia applications 
in wireless sensor networks [8], operational monitoring 
data system [9], etc.  
 
Fig.2. Architecture of energy harvesting wireless sen-
sor node[6]. 
Basically, all types of wireless sensor networks uses 
can benefit from power scavenging techniques to elon-
gate the lifespan of the WSNs. 
Classification of energy harvesting techniques in 
WSNs 
 For Power scavenging several power sources have 
been deliberated. To select a power harvesting source, 
one of the leading standards is to define whether or not 
it can deliver the required energy level for the SN. 
Generally, power dissipates through voltage conversion 
and the dissipation growths as the input/output ratio of 
the voltage growths. Consequently, it is imperative to 
guarantee that the engendered power is at an appropri-
ate voltage and current level. In order to attain the 
anticipated power level, whether the source of the en-
ergy is improved or the power scavenging device is 
surmounted accordingly. For example, in the case of 
Radio Frequency, raising the power of the source will 
satisfy the required demand. Also, growing the Photo-
voltaic (PV) cell region will assemble extra light, ensu-
ing in the generation of extra power. Though, in certain 
environments, the sources/converters cannot be scaled 
so simply. For example, power resulting from industri-
al vibrations in general cannot be scaled up without 
growing the vibration effect on the machine, which 
may be undesirable. Therefore, while it may be promis-
ing to scale up the scavenging device, several wireless 
sensors network applications oblige sensors to be small 
sized and lightweight. Therefore, the power density 
parameter is used commonly by the scientist research-
ers to compare diverse power scavenging mechanisms 
[10].  
 
Fig.3. Taxonomy of energy harvesting sources in 
WSN 
For that reason, developers need to keep this tradeoff in 
mind when choosing an appropriate power scavenging 
system for a specific use. We organize the power scav-
enging sources into two general classes: ambient 
sources and external sources. Ambient sources are 
readily offered in the environment at almost free. On 
the other hand, external sources are positioned openly 
in the environments for power harvesting purposes. 
These classes are auxiliary partitioned as presented in 
Fig. 3. 
RF Energy Harvesting  
Ambient Radio frequency energy is a 4
th
 source for 
energy scavenging fig.4. By ambient RF energy, we 
mean RF energy obtainable over public telecommuni-
cation services (e.g., GSM and WLAN frequencies). 
When harvesting power energy in the GSM or WLAN 
band, one has to deal with very low power density 
levels. For ranges of 25–100 m from a GSM sink, 
power density levels of 0.1–1.0 mW/m2 can be pre-
dictable for single frequencies [11]. For the entire GSM 
downlink frequency bands, these levels can be raised 
by a factor of between 1 and 3, contingent on traffic 
capacity. First measurements in a WLAN environment 
specify power density levels that are at least one order 
of magnitude lower [12]. Then, neither GSM nor 
WLAN is expected to harvest enough ambient RF 
energy for wirelessly powering tiny sensors, unless a 
big area is employed for harvesting. This was evidently 
proved by Intel [6] Energy diffused by an adjacent TV 
station (distance: four km) was used to power a tem-
perature sensor (Fig.5.). 
 
Fig.4. Generalized RF energy harvesting system for 
WSNs 
 With an antenna of around 30 cm by 20 cm, 60 µW of 
energy was harvested, which amounts to an energy 
density of 0.1 µW/cm2. Alternatively, one can use a 
dedicated RF source positioned close (a few meters) to 
the sensor node, thereby limiting the transmission 
power to levels accepted by international regulations. 
Consider an RF device with power PT transmitting and 
receiving at wavelength l at a distance R from the node. 
The received power PR is then described by the Friis 
equation [13] as PR 5 PTGTGRl2 14p22R2 , where 
GR and GT are the receiving and transmitting antenna 
gains, respectively. Such a commercial system, pro-
duced by the company Powercast, is currently on the 
market [14]. The system charges the internal battery of 
a device using the received RF energy. In ideal condi-
tions, with no reflections and aligned polarization, 15 
mW of power can be received at a distance of 30 cm, 
with a transmitted power of 2–3 W at a frequency of 
906 MHz. There is still a lot of room for improvement 
in transmission (e.g., via beam steering), receiving 
(with improved antenna design), and conversion effi-
ciency. As an example, at a transmission power of 100 
mW, values of 1.5 mW at 20 cm and 200 μW at 2 m 
have been reported [15]. 
 
Fig.5. The DC/DC converter architecture[16] 
 
CONCLUSION 
1. Conclusion  
This paper presented energy harvesting routing based 
and battery power based routing approaches in WSN. 
The state-of-the-art energy harvesting mechanism for 
WSN is discussed in details and the most recent ener-
gy-efficient data packet routing approaches are re-
viewed. Then comparisons of the studied methods 
based on the main features are made. According to the 
literature, balancing of the energy among the nodes is 
usually obtained in two ways, single-path, and multi-
path methods. In single-path methods, the best path 
that can satisfy the required energy consumption. The 
load is divided amongst the paths, to ensure energy 
balancing among nodes in multi-paths methods 
 
Bibliographie 
[1] N. Li, N. Zhang, S. K. Das, et B. Thuraisingham, 
« Privacy preservation in wireless sensor networks: A state-
of-the-art survey », Ad Hoc Networks, vol. 7, no 8, p. 
1501‑1514, nov. 2009. 
[2] P. Marappan et P. Rodrigues, « An energy efficient 
routing protocol for correlated data using CL-LEACH in 
WSN », Wireless Netw, vol. 22, no 4, p. 1415‑1423, mai 
2016. 
[3] M. Prauzek, J. Konecny, M. Borova, K. Janosova, J. 
Hlavica, et P. Musilek, « Energy Harvesting Sources, Storage 
Devices and System Topologies for Environmental Wireless 
Sensor Networks: A Review », Sensors, vol. 18, no 8, p. 
2446, juill. 2018. 
[4] S. Chaudhary, « Energy Efficient Techniques for 
Data aggregation and collection in WSN », IJCSEA, vol. 2, no 
4, p. 37‑47, août 2012. 
[5] S. Kumar, A. Arora, et T. H. Lai, « On the lifetime 
analysis of always-on wireless sensor network applications », 
in IEEE International Conference on Mobile Adhoc and 
Sensor Systems Conference, 2005., N/A, 2005, p. 186‑188. 
[6] F. K. Shaikh et S. Zeadally, « Energy harvesting in 
wireless sensor networks: A comprehensive review », Re-
newable and Sustainable Energy Reviews, vol. 55, p. 
1041‑1054, mars 2016. 
[7] S. Ferdoush et X. Li, « Wireless Sensor Network 
System Design Using Raspberry Pi and Arduino for Envi-
ronmental Monitoring Applications », Procedia Computer 
Science, vol. 34, p. 103‑110, 2014. 
[8] S. Misra, M. Reisslein, et G. Xue, « A survey of 
multimedia streaming in wireless sensor networks », IEEE 
Commun. Surv. Tutorials, vol. 10, no 4, p. 18‑39, 2008. 
[9] N. Xu et al., « A wireless sensor network For struc-
tural monitoring », in Proceedings of the 2nd international 
conference on Embedded networked sensor systems  - SenSys 
’04, Baltimore, MD, USA, 2004, p. 13. 
[10] K. Najafi, T. Galchev, E. E. Aktakka, R. L. Peterson, 
et J. McCullagh, « Microsystems for energy harvesting », in 
2011 16th International Solid-State Sensors, Actuators and 
Microsystems Conference, Beijing, China, 2011, p. 
1845‑1850. 
[11] C. Song, Y. Huang, J. Zhou, J. Zhang, S. Yuan, et P. 
Carter, « A High-Efficiency Broadband Rectenna for Ambi-
ent Wireless Energy Harvesting », IEEE Trans. Antennas 
Propagat., vol. 63, no 8, p. 3486‑3495, août 2015. 
[12] L. Zou, A. Javed, et G.-M. Muntean, « Smart mobile 
device power consumption measurement for video streaming 
in wireless environments: WiFi vs. LTE », in 2017 IEEE 
International Symposium on Broadband Multimedia Systems 
and Broadcasting (BMSB), Cagliari, Italy, 2017, p. 1‑6. 
[13] O. Franek, « Phasor Alternatives to Friis’ Transmis-
sion Equation », Antennas Wirel. Propag. Lett., vol. 17, no 1, 
p. 90‑93, janv. 2018. 
[14] F. Sangare, A. Arab, Miao Pan, Lijun Qian, S. K. 
Khator, et Zhu Han, « RF energy harvesting for WSNs via 
dynamic control of unmanned vehicle charging », in 2015 
IEEE Wireless Communications and Networking Conference 
(WCNC), New Orleans, LA, 2015, p. 1291‑1296. 
[15] C. Merz, G. Kupris, et M.  Niedernhuber, « 1.1 - 
Wireless and Battery-less Sensor Using RF Energy Harvest-
ing », p. 6 Pages, 336 KB, 2014. 
[16] B. J. Patella, A. Prodic, A. Zirger, et D. Maksimovic, 
« High-frequency digital controller IC for DC/DC convert-
ers », in APEC. Seventeenth Annual IEEE Applied Power 
Electronics Conference and Exposition (Cat. 
No.02CH37335), Dallas, TX, USA, 2002, p. 374‑380. 
 
 


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