- Open Access
On the use of electromagnetic waves as means of power supply in wireless sensor networks
© Cortés-Sánchez et al.; licensee Springer. 2014
- Received: 2 August 2013
- Accepted: 11 February 2014
- Published: 7 March 2014
Wireless sensor networks (WSNs) can be typically used to achieve continuous monitoring (CM) or event detection inside the supervised area. In CM applications, each sensor node transmits periodically its sensed data to the sink node, while in event-detection driven (EDD) applications, once an event occurs, it is reported to the sink node. Hence, CM applications entail much higher energy consumption since all nodes are actively transmitting information much longer than typical EDD applications. Furthermore, in highly dense WSNs, the energy consumption is even higher. As such, the use of autonomous devices that provide a constant energy supply is becoming relevant for these environments. In this work, we propose to take advantage of the electromagnetic waves found in the radio-electric spectrum in order to supply the energy to each node in the network. To this end, the antenna and the storage and amplifications system for such device are designed. Additionally, the performance of dense CM WSN is studied using a Markov chain in order to calculate the lifetime of the system.
- Antenna design
- Markov analysis
- Voltage multiplier
- Wireless sensor networks
Wireless sensor networks (WSNs) are typically designed for either continuous monitoring (CM) or event-detection driven (EDD) applications. EDD WSNs are deployed over a target area to supervise certain phenomena of interest. Once an event occurs, it is reported to the sink node by the sensors within the event area. Each node takes readings from the local environment and processes and transmits the sensed data to the sink node. In this type of WSNs, communications are only triggered by the occurrence of a pre-specified type of events. As opposed to EDD applications, CM WSNs are deployed in order to examine the evolution of certain parameters, which are refreshed periodically at the sink node. As such, CM applications have typically much higher energy. Energy consumption is a major issue in WSNs (for both EDD and CM applications) since in many cases it is very complicated to replace the node's batteries or even impossible. Consider for example, the case of a WSN deployed in the forest for animal protection purposes  or inside the concrete in buildings or steel beams in bridges in order to monitor the structural health .
In the literature, it is common to assume that nodes are equipped with batteries, which power the nodes for a limited amount of time . Hence, the communication protocol is designed in order to limit the power consumption in the system. For instance, clustering protocols like the one proposed in  aim at reducing and evenly distributing the energy consumption in order to extend the network's lifetime.
Building on this, it is natural to search for alternatives to constantly supply power to the nodes in order to extend the network lifetime or even avoid complete energy depletion. Emerging technologies such as solar cells can be used for such effect with the main drawback that it cannot work efficiently indoors or at night. Another alternative would be the use of devices that take the energy from the electromagnetic waves in the radio-electric frequency spectrum, such as TV and radio signals. This alternative has the big advantage that, in these frequencies, there are almost always data transmissions for where to extract energy. In this case, the proposed device is not designed to decode these signals, just to take advantage of the ever-present signal transmission in this frequency range.
As an additional feature of our work, we develop a mathematical analysis to determine the performance of a CM WSN when such device is used, i.e., when nodes use a constant power supply. We focus our attention in CM WSNs since these applications are more energy consuming than their EDD WSNs counterpart.
From the numerical results obtained in this work, it is clear that the use of a constant power supply, such as the device proposed in this paper, can radically change the analysis and design of WSNs. Indeed, the design of WSNs is mainly focused on the lifetime of the system when a limited-energy battery is used as means of power supply. Specifically, communication protocols (including random access strategies and routing schemes) are mainly designed in order to limit the amount of transmissions. This leads to a very restrictive environment where only the most relevant data is to be transmitted. Conversely, when each node has a constant power supply, the design can now be focused on other parameters such as delay guarantees in multimedia data transmission, such as video surveillance or video transmission and VoIP-enabled sensors for noise detection.
A similar RF energy-harvesting device was presented in . However, in  only a 2.4-GHz frequency was considered. In this work a range of frequencies (from some megahertz to a few gigahertz) are contemplated in order to harvest the maximum amount of energy from different radio sources. Also, the work in  does not present a performance evaluation of a WSN with a constant energy source since its focus is mainly on the electronic device for general purpose. In this line, in [6, 7] an alternating current/direct current (AC/DC) converter from an AC voltage of a few hundred millivolts is developed. In the work presented in , authors consider the use of a low-voltage AC/DC converter system for the particular case of a WSN. From the developed systems in [6, 7], it is clear that their proposed devices can indeed offer a constant power supply to the nodes in the system. However, both [6, 7] focuses mainly on the AC/DC conversion. Hence, neither antenna design is proposed nor the performance analysis of the WSN is considered.
In the rest of the paper, we develop the antenna design in order to harvest energy in a wide range of frequencies. Then the electronic device that converts the very low AC signal to a 3.5-V DC signal is presented along with the storage system. Finally, the performance analysis of a continuous monitoring WSN when nodes have a constant power supply is shown. We conclude the paper with some remarks and future work ideas.
In this section, the antenna design and the voltage multiplier are presented. As a case of study, it is considered that the WSN is deployed at a distance of 15 km from the radio and TV broadcast emissions. Also, a performance analysis of the proposed device in a WSN for continuous monitoring applications is presented.
2.1 Antenna selection
The geometrical data for the antenna is as follows:
‘Antenna diameter, 0.56 m
‘Wire radius, 0.00875 m
‘Separation between spires, 0.0175 m
The spiral antenna can be used over a wide range of RF incident power densities, where the goal for the power management is to optimally load the rectenna at the DC output to achieve maximum harvested power . The spiral antenna can be connected to switch with reconfigurable rectenna circuit. The characteristic of the antenna was simulated with FEKO software.
The RF input energy is rectified using a rectenna circuit. The circuit is optimized for a given input RF power. The principal limitation of the rectenna circuit is that it is designed for an operating point. Good efficiency is obtained when different parameters are considered: power level, central frequency, and load impedance .
A rectenna is a microwave rectifier which converts RF energy directly into DC current. When only one frequency is considered, it is possible to use a high-gain receiving antenna.
2.2 Storage and amplification
2.3 Analysis of the CM WSN
In this section, the advantages of using a device that delivers a constant power supply to each sensor node are studied.
It has been proven in  that the use of a clustered-based architecture greatly reduces the energy consumption in CM WSNs since the main sources of energy wastage are addressed: collisions, overhearing (when a node receives an unintended packet), idle listening (lost energy while listening to the medium to receive possible traffic that is not sent), and overhead (due to exchange of signaling messages required for the protocol execution). Hence, we assume such architecture in this analysis.
The following parameters are used for the analysis: The WSN is considered to be placed at 15 km from the emitting antenna. In such conditions, the constant power supply is 3.5 V. The control packets used for the CF phase is lCF = 80 b, while the data packets used in the steady phase is ld = 2,048 b. Based on commercial transceivers (Microchip MRF24J40, Microchip Technology Inc, Chandler, AZ, USA), the transmission energy per bit is ETx = 0.395 J while the reception energy per bit is ERx = 82.5 mJ. Also the energy of a conventional lithium battery is 7.59 J.
For a WSN with N nodes and C clusters in average, there are ENC = N/C nodes per cluster.
2.3.1 Steady-state analysis
where ld is the data packet length used for the transmission of the recollected data by each node, and R is the number of TDMA frames per round. Note that from the N/C nodes in average that form the cluster, only the cluster members transmit to the CH (this comprises the first two elements of (1)). Also, the CH transmits all the recollected packets to the sink node, including its own data packet. As such, neither data compression nor aggregation is assumed in this analysis. Also, it is considered that the same transmission energy is used to reach the CH and the sink node. The rationale behind this is that the analysis presented in this work is a first attempt at analyzing the performance of a WSN with a constant power supply. To this end, we consider the worst conditions. The effect of data compression and/or aggregation would render less energy consumption.
2.3.2 Cluster formation analysis
The system begins in state (N,0) and state (0,0) is an absorbing state (in this state all the nodes in the system have successfully transmitted their control packet and the clusters are formed).
where τ is the transmission probability given by the geometric backoff assumed in this work. When the chain enters state (n,1) (one node form the n contending nodes), it goes to state (n-1,l) with probability 1/(n-1).As such, this two-dimensional Markov chain can be considered to be composed of N different phases denoted by the number of nodes attempting a packet transmission. Hence, the energy cxonsumption at phase n can be calculated noting that whenever a successful transmission occurs, there is one node that consumes units of energy, while there are n-1 nodes that receive the packet, each consuming units of energy. Hence, the energy consumption in the case of a successful transmission is . On the other hand, whenever a collision occurs or if there are no transmissions, there are S n nodes that transmit, each one consuming units of energy, while n-S n nodes listen to the channel consuming units of energy each one.
Hence, the average energy consumption at the cluster formation phase is ECN 0.
In this paper an electronic device to use the energy from the electromagnetic waves was designed. First, the main radio emissions in the particular case of Mexico City were studied in terms of frequency and RF power reception. Then, a suitable antenna was designed such that it is capable of absorbing most of the available radio emissions ranging from dozens of megahertz to a few gigahertz. Given this wide range of frequencies of interest, it can be connected to switch with reconfigurable rectenna circuit. As such, a spiral antenna was selected given its good coupling characteristics in practical all the frequency range. Then, the electronic system was designed. This circuit is composed of the AC/DC converter, rectifier, amplification, and a storage system that directly powers each sensor node.
Building on this, a mathematical analysis to calculate the energy consumption in a CM WSN was performed. First, the analysis considered that a limited energy battery powered the nodes in the system. This is the conventional case in the WSN environment. Then, the analysis was performed considering a constant power supply of 3.5 V. Hence, whenever the energy consumption for the continuous monitoring application entails an energy consumption of less than 3.5 V per node, the system can operate without suffering any depletion from the nodes. Conversely, when the energy consumption is higher than this value, some nodes stop operating, causing information losses. This simple analysis proves the benefits of the proposed device in the context of WSNs increasing by 10 the number of nodes supported in the system without a node depleting its energy in the first round. The analysis can be further improved by considering multiple TDMA frames per round as well as compression and aggregation techniques. Also, different transmission ranges can be considered in order to further reduce the energy consumption.
This work was partially supported by the National Polytechnique Institute (UPIITA-IPN) under multidisciplinary project SIP 20130440 and CONACyT-SEP project 183370.
- Arampatzis T, Lygeros J, Manesis S: A survey of applications of wireless sensors and wireless sensor networks. In Proceedings of the 2005 IEEE International Symposium on Intelligent Control, 2005, Mediterranean Conference on Control and Automation. Limassol; June 2005:27-29.Google Scholar
- Hu X, Wang B, Ji H: A wireless sensor network‒based structural health monitoring system for highway bridges. Computer‒Aided Civil and Infrastructure. Engineering 2012, 28(3):193-209.Google Scholar
- Rivero-Angeles ME, Nizar B: Event reporting on continuous monitoring wireless sensor networks. In IEEE GlobeCom 2009. Honolulu; 2009. 30 November to 4 DecemberGoogle Scholar
- Heinzelman WR, Chandrakasan A, Balakrishnan H: Energy-efficient communication protocol for wireless microsensor networks. In Proceedings of the 33rd Annual Hawaii International Conference on System Sciences. Wailea Maui; 2000:4-7. January 2000Google Scholar
- Paing TS, Zane R: Resistor emulation approach to low-power energy harvesting. In 37th IEEE Power Electronics Specialists Conference. PESC'06, Jeju; 2006:18-22. June 2006Google Scholar
- Dwari S, Parsa L: Efficient low voltage direct AC/DC converters for self-powered wireless sensor nodes and mobile electronics. In IEEE 30th International Telecommunications Energy Conference, 2008. INTELEC 2008, San Diego; 2008:14-18. September 2008Google Scholar
- Dayal R, Parsa L: A new single stage AC-DC converter for low voltage electromagnetic energy harvesting. In 2010 IEEE Energy Conversion Congress and Exposition (ECCE). Atlanta; 2010:12-16. SeptemberGoogle Scholar
- Stutzman WL, Thiele GA: Chapter 6: wire antennas. In Antenna Theory and Design. Wiley, New York; 1998.Google Scholar
- Marian V, Allard B, Vollaire C, Verdier J: Strategy for microwave energy harvesting from ambient field or a feeding source. IEEE Trans On Power Electronics 2012, 27(11):4481-4491.View ArticleGoogle Scholar
- Bouabdallah N, Rivero-Angeles ME, Sericola B: Continuous monitoring using event-driven reporting for cluster-based wireless sensor networks. IEEE Trans on Vehic. Tech. 2009, 58(7):3460-3479.View ArticleGoogle Scholar
- Rom R, Sidi M: Multiple Access Protocols. Performance and Analysis (Springer, Berlin; 1990. pp. 47–103View ArticleGoogle Scholar
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