Power allocation and relay selection for energy efficient cooperation in wireless sensor networks with energy harvesting

Yin, Wenjie; Liu, Yanyi; Li, Kaiyu

doi:10.1186/s13638-017-0811-9

Cited by 15 publications

(7 citation statements)

References 22 publications

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“…26,27 However, BER and network lifetime of wireless sensor network are studied previously, but in this paper, performance on BER and network lifetime both are evaluated simultaneously. In the proposed RSFL, path loss and residual energy of node have given equal priority.…”

Section: Defuzzificationmentioning

confidence: 99%

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A fuzzy decision scheme for relay selection in cooperative wireless sensor network

Jain

Yadav

Verma

2019

Int J Communication

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In energy-constrained military wireless sensor networks, minimizing the bit error rate (BER) with little compromise on network lifetime is one of the most challenging issues. This paper presents a new relay selection based on fuzzy logic (RSFL) scheme which provides balance between these parameters. The proposed scheme considers node's residual energy and path loss of the relaydestination link as the input parameters for the selection of the relay node.The relay node selection by fuzzy logic is based on prioritizing higher residual energy and minimum path loss. To evaluate the performance on wireless sensor network, we compare the proposed scheme with the three existing relay selection strategies, ie, random, maximum residual energy based relay selection (MaxRes), and minimum energy consumption based relay selection (MinEnCon). The simulation results of the proposed scheme in terms of network lifetime, BER, Network Survivability Index (NSI), and average energy of network nodes have been presented and compared with different relay selection schemes. The simulation results show that the proposed RSFL scheme has the lowest BER, moderate network lifetime, average energy, and NSI. KEYWORDSbit error rate, cooperative communication, network lifetime, Network Survivability Index, random relay selection, residual energy, wireless sensor networks | INTRODUCTIONWireless sensor network is widely used in many applications and services such as industry, mines, health, military, agriculture, Internet of Things (IoT), and home automation. [1][2][3][4] The wireless channel which is used for communication becomes unreliable due to noise, fading, reflections, distortion, and installation of antennas. In order to minimize the effects of these distortions, various solutions have been proposed such as cooperative communication, energy harvesting, multiple antennas etc. The design of wireless sensor network depends on the specific application.In military battle ground, the communication may be interrupted due to nodes are attacked by enemy troops. If some nodes are destroyed by the enemy, then it is very difficult to send important information to the destination node. 5 Maintaining the reliable communication between the nodes is a key preference for the security point of view. In such situation, cooperative communication emerges as a vital solution where noninterrupted, error free data reception, network survivability, and lifetime are the prime issues. These issues can be address by the selection of an appropriate intermediate node in cooperative wireless sensor networks.

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Section: Defuzzificationmentioning

confidence: 99%

“…In addition, in the proposed strategy for retransmission of the signals, the destination node chooses relay node instead of source node. 26,27 However, BER and network lifetime of wireless sensor network are studied previously, but in this paper, performance on BER and network lifetime both are evaluated simultaneously.…”

Section: Defuzzificationmentioning

confidence: 99%

A fuzzy decision scheme for relay selection in cooperative wireless sensor network

Jain

Yadav

Verma

2019

Int J Communication

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“…Authors in [17] offered Energy Harvesting (EH-WSN) technique having the upside of productive collaboration and transfer choice in view of little power use. The convention is assessed in two stages, in initial step, helpful correspondence is assessed and afterward the energy of every node is figured.…”

Section: Literature Reviewmentioning

confidence: 99%

Dist-Coop: Distributed Cooperative Transmission in UWSNs using Optimization Congestion Control and Opportunistic Routing

Ali¹,

Shahid²,

Ahmed³

et al. 2018

ijacsa

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One of the real issues in UWSN is congestion control. The need is to plan an optimized congestion control scheme which enhances the network life time and in addition limits the usage of energy in data transmission from source to destination. In this paper, we propose a routing protocol called Dist-Coop in UWSN. Dist-Coop is a distributed cooperation based routing scheme which uses mechanism for optimized congestion control in noisy links of underwater environment. It is compact, energy proficient and high throughput opportunistic routing scheme for UWSN. In this proposed protocol architecture, we present congestion control with cooperative transmission of data packets utilizing relay sensors. The final objective is to enhance the network life time and forward information utilizing cooperation procedure, limiting energy consumption amid transmission of information. At destination node, combining strategy utilized is based on Signal-to-Noise Ratio (SNRC). Simulation results of Dist-Coop scheme indicate better outcomes in terms of energy consumption, throughput and network lifetime in contrast with Co-UWSN and EH-UWSN routing protocols. Dist-Coop has expended substantially less energy and better throughput when contrasted with these protocols.

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“…However, their work did not involve an SR in the secondary network, whereas ours takes the SR into consideration for optimal power allocation. The optimal power allocation schemes in [29,30] are in relation to relay selection, unlike ours, which employs a single relay sensor to execute power superposition coding.The jointly optimal power splitting ratio and power sharing coefficient were found using specific analytical or mathematical expressions. In these expressions, the impact of the system parameters (including the two power parameters) on the outage probabilities are evaluated.…”

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Optimal Power Allocation of Relay Sensor Node Capable of Energy Harvesting in Cooperative Cognitive Radio Network

Har

Cho

Kong

2017

Sensors

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A cooperative cognitive radio scheme exploiting primary signals for energy harvesting is proposed. The relay sensor node denoted as the secondary transmitter (ST) harvests energy from the primary signal transmitted from the primary transmitter, and then uses it to transmit power superposed codes of the secrecy signal of the secondary network (SN) and of the primary signal of the primary network (PN). The harvested energy is split into two parts according to a power splitting ratio, one for decoding the primary signal and the other for charging the battery. In power superposition coding, the amount of fractional power allocated to the primary signal is determined by another power allocation parameter (e.g., the power sharing coefficient). Our main concern is to investigate the impact of the two power parameters on the performances of the PN and the SN. Analytical or mathematical expressions of the outage probabilities of the PN and the SN are derived in terms of the power parameters, location of the ST, channel gain, and other system related parameters. A jointly optimal power splitting ratio and power sharing coefficient for achieving target outage probabilities of the PN and the SN, are found using these expressions and validated by simulations.

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Power allocation and relay selection for energy efficient cooperation in wireless sensor networks with energy harvesting

Cited by 15 publications

References 22 publications

A fuzzy decision scheme for relay selection in cooperative wireless sensor network

A fuzzy decision scheme for relay selection in cooperative wireless sensor network

Dist-Coop: Distributed Cooperative Transmission in UWSNs using Optimization Congestion Control and Opportunistic Routing

Optimal Power Allocation of Relay Sensor Node Capable of Energy Harvesting in Cooperative Cognitive Radio Network

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