Energy-balanced cooperative transmission based on relay selection and power control in energy harvesting wireless sensor network
Introduction
Wireless Sensor Network (WSN) is a salient technique for information gathering with a wide range of applications including habitat monitoring, battlefield surveillance, intelligent building, etc [1]. In general, the small-sized and battery-powered sensors are deployed and intended to operate unattended for a long operation time. Due to the limitation of battery capacity, the depletion of sensors’ energy may lead to coverage hole and network partition [2]. Recently, the energy harvesting (EH) technology proposes a promising solution to prolong sensors’ lifetime by enabling the sensors to harvest energy from the ambient energy sources, such as thermal, wind and Radio Frequency (RF) [3], [4]. The typical application of the Energy Harvesting Wireless Sensor Network (EHWSN) is reported in [5], where Dutta et al. deploy a solar-powered sensor network to monitor the outdoor environment for more than four months. Although, the ambient energy can be harvested and stored for later use, the availability of ambient energy sources is temporally and spatially changing [6], [7]. Therefore, the energy harvested and consumed by sensors should be well balanced to promise the sensors’ sustainability and functioning [8].
With the emerging of virtual Multiple-Input-Multiple-Output (MIMO), i.e., the cooperative transmission technique, the small wireless devices can distributively coordinate their antennas to emulate the functionality of multi-antenna systems for data transmission [9]. The signals from the small wireless devices are constructively combined at the destination [10]. By exploiting the cooperative transmission in EHWSN, the sensors with low EH capability are able to leverage the energy of other sensors to transmit data, such that sensors’ energy consumption and harvesting can be balanced according to their EH capabilities.
Utilizing cooperative transmission in EHWSN, sensors play two energy consuming roles, where one role is to serve as the source with a data packet destined to the sink, and the other role is to serve as the relay to cooperate with the source. Since the energy consumption of cooperative transmission may impact the relay’s operation, the relay selection, i.e., which relay is selected to cooperate with the source, and the power control, i.e., how do the relay and source adjust their transmission power, are both the key issues to make a balanced use of sensors’ energy. Furthermore, due to the decentralized nature of EHWSN, the relay selection and power control should be realized in a distributed manner.
In this paper, we investigate the distributed single relay selection and power control for an EHWSN to balance the residual energy of sensors. In the EHWSN, the sink locates in the maximal transmission range of all sensors. In each data transmission, the sensor with the data packet is referred to as the source, while other sensors are referred to as the relays. Each relay resolves the power control problem to maximize the minimum residual energy of sensors. Then the relay sends a JOIN message to the source for cooperative transmission after a backoff time. The value of the backoff time is inversely correlated with the maximized minimum residual energy, such that the relay selection can be realized in a distributed manner. Specifically, the contributions are summarized as follows:
- 1.
Considering the EH capability and instantaneous channel gain, we design a relay selection and power control scheme that can be unified into the signaling procedure of the MAC layer for EHWSN, called Distributed Energy Balancing Scheme (DEBS), to maximize the residual energy of sensors using cooperative transmission.
- 2.
In DEBS, we formulate a maximization of minimum value problem to maximize the minimum residual energy of sensors in each data transmission, and efficiently solve the problem by exploiting its linear structure. The extensive simulation results are conducted to confirm that DEBS can remarkably optimize the residual energy of sensors comparing to other two classic relay selection schemes.
The remainder of this paper is organized as follows. The related works are reviewed in Section 2. Section 3 describes the system model. Then we propose DEBS in Section 4. Section 5 provides the performance evaluation. Finally, Section 6 concludes this paper and outlines the future work.
Section snippets
Related works
Virtual MIMO-based cooperative transmission has been widely investigated for the sake of energy efficiency in the literature [11], [12], [13], [14], [15]. Cui et al. analyze the best modulation and transmission strategy for a single-hop sensor network to minimize the energy consumption that is required to send a given number of bits [11]. It is revealed that much transmission energy can be saved through sensors’ cooperation, especially for long-distance transmission. In [12], Jayaweera extends
System model
We consider an EHWSN consisting of one sink, and N sensors equipped with EH modules and a rechargeable battery with capacity Bmax. The sensors can communicate with the sink directly with the maximal transmission power. The sensors collect data from the area of interest, and transmit the data packet to the sink. Furthermore, the following assumptions stand through the paper:
- 1.
The sensors are equipped with omni-directional antennas. Therefore, we assume the wireless channels between all sensors
Distributed energy balancing scheme: DEBS
Considering the channel gain and EH capabilities of the relays, the design of distributed relay selection and power control becomes challenging. In this section, we propose the DEBS for each relay to decide whether it should cooperate with the source, and the setting of backoff time tR. By assigning a shorter backoff time to the relay which can achieve higher minimum residual energy, the relay selection can be distributively realized.
Performance evaluation
This section evaluates the performance of the proposed scheme. The transmission of control messages and data packets is built in the widely-used Omnet++ discrete event simulator [36]. The considered EHWSN consists of sensors and one sink. The sensors randomly distribute around a circular area with radius 120 m. In each data transmission, the sensor with a data packet to transmit acts as the source, while other sensors act as relays. The relay sends the JOIN message to the source for
Conclusion
In this paper, we have proposed a cooperative transmission scheme for EHWSN, where the relay selection and power control are jointly designed to balance the residual energy of sensors. The proposed scheme operates in a distributed manner in which the optimal relay, i.e., the relay that can maximize the sensors’ residual energy, is selected to cooperate with the source for data transmission. The outcomes of this paper can provide some insights for residual energy balancing design in EHWSN, by
Acknowledgment
This work was supported by the Fundamental Research Funds for the Central Universities of the Central South University (No. 2013zzts043). This work was also supported by National Natural Science Foundation of China (61379057, 61272149) and NSERC, Canada.
Deyu Zhang recevied the B.Sc. degree in communication engineering from PLA Information Engineering University in 2005; and M.Sc. degree from Central South University in 2012, China, all in communication engineering. He is pursuing his Ph.D degree in Central South University in computer science. He is currently a visiting scholar with the Department of Electrical and Computer Engineering, University of Waterloo, ON, Canada. His research interests include wireless sensors network, stochastic
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Deyu Zhang recevied the B.Sc. degree in communication engineering from PLA Information Engineering University in 2005; and M.Sc. degree from Central South University in 2012, China, all in communication engineering. He is pursuing his Ph.D degree in Central South University in computer science. He is currently a visiting scholar with the Department of Electrical and Computer Engineering, University of Waterloo, ON, Canada. His research interests include wireless sensors network, stochastic optimization and resource allocation.
Zhigang Chen received B.Sc., M.Sc. and Ph.D degrees from Central South University, China, in 1984, 1987 and 1998, all in computer science, respectively. He is a professor and Ph.D. Supervisor with CSU. His research interests are in network computing and distributed processing.
Haibo Zhou received the Ph.D. degree in information and communication engineering from Shanghai Jiao Tong University, Shanghai, China, in 2014. He is currently a postdoctoral fellow with the Broadband Communications Research (BBCR) Group, Department of Electrical and Computer Engineering, Faculty of Engineering, University of Waterloo, Waterloo, ON, Canada. His current research interests include resource management and protocol design in cognitive radio networks and vehicular networks.
Long Chen received the B.S. degree in software engineering from Central South University in 2013. He is currently persuing his M.Sc. degree in CSU in software engineering. His research interests are wireless sensors network.
Xuemin (Sherman) Shen received the B.Sc. degree from Dalian Maritime University, Dalian, China, in 1982 and the M.Sc. and Ph.D. degrees from Rutgers University, New Brunswick, NJ, USA, in 1987 and 1990, respectively, all in electrical engineering. He is a Professor and a University Research Chair with the Department of Electrical and Computer Engineering, Faculty of Engineering, University of Waterloo, Waterloo, ON, Canada, where he was the Associate Chair for Graduate Studies from 2004 to 2008. He is a coauthor or editor of six books, and he is the author or coauthor of more than 600 papers and book chapters in wireless communications and networks, control, and filtering. His research focuses on resource management in interconnected wireless/wired networks, wireless network security, social networks, smart grids, and vehicular ad hoc and sensor networks. Dr. Shen is an IEEE Fellow, an Engineering Institute of Canada Fellow, a Canadian Academy of Engineering Fellow, and a Distinguished Lecturer of the IEEE Vehicular Technology Society and the IEEE Communications Society. He served as the Technical Program Committee Chair or Cochair for IEEE Infocom’14 and IEEE VTC’10 Fall, as the Symposia Chair for the IEEE ICC’10, as the Tutorial Chair for the IEEE VTC’11 Spring and the IEEE ICC’08, as the Technical Program Committee Chair for the IEEE Globecom’07, as the General Cochair for Chinacom’07 and QShine’06, and as the Chair for the IEEE Communications Society Technical Committee on Wireless Communications, and P2P Communications and Networking. He also serves or served as the Editor-in-Chief for IEEE Network, Peer-to-Peer Networking and Application, and IET Communications; as a Founding Area Editor for the IEEE Transactions on Wireless Communications; as an Associate Editor for the IEEE Transactions on Vehicular Technology, Computer Networks, ACM/Wireless Networks, etc.; and as a Guest Editor for the IEEE Journal on Selected Areas in Communication, the IEEE Wireless Communications, the IEEE Communications Magazine, ACM Mobile Networks and Applications, etc. He was the recipient of the Excellent Graduate Supervision Award in 2006; the Outstanding Performance Award in 2004, 2007, and 2010 from the University of Waterloo; the Premier’s Research Excellence Award from the Province of Ontario, Canada, in 2003; and the Distinguished Performance Award from the Faculty of Engineering, University of Waterloo in 2002 and 2007. He is a Registered Professional Engineer in Ontario, Canada.