Surface-level path loss modeling for sensor networks in flat and irregular terrain

Chong, Poh Kit; Kim, Dae-Young

doi:10.1145/2422966.2422972

Cited by 32 publications

(27 citation statements)

References 35 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Distance between the relay and source is 1 and the distance between the relay and destination is 2 as shown in Figure 2. The information received at and from source in phase 1 can be written as [14] = √ 1 ℎ + ( ) ,…”

Section: Cooperation Phasementioning

confidence: 99%

“…and are the noise components introduced in the links from to and from to , respectively [14], and have the value in terms of the components as given in (3).…”

Section: Cooperation Phasementioning

confidence: 99%

“…The gain provides amplification at to counter the effect of the channel fading and prevents the relay gain from saturating when the -link undergoes deep fading. As power is defined as energy per unit time, hence expressing the transmission powers of and in terms of energy, (14) can be expressed as…”

Section: Relay Selection and Routing Phasementioning

confidence: 99%

See 2 more Smart Citations

Co-UWSN: Cooperative Energy-Efficient Protocol for Underwater WSNs

Ahmed

Javaid

Khan

et al. 2015

International Journal of Distributed Sensor Networks

View full text Add to dashboard Cite

Sensor networks feature low-cost sensor devices with wireless network capability, limited transmit power, resource constraints, and limited battery energy. Cooperative routing exploits the broadcast nature of wireless medium and transmits cooperatively using nearby sensor nodes as relays. It is a promising technique that utilizes cooperative communication to improve the communication quality of single-antenna sensor nodes. In this paper, we propose a cooperative transmission scheme for underwater sensor networks (UWSNs) to enhance the network performance. Cooperative diversity has been introduced to combat fading. Cooperative UWSN (Co-UWSN) is proposed, which is a reliable, energy-efficient, and high throughput routing protocol for UWSN. Destination and potential relays are selected that utilize distance and signal-to-noise ratio computation of the channel conditions as cost functions. This contributes to sufficient decrease in path losses occurring in the links and transferring of data with much reduced path loss. Simulation results show that Co-UWSN protocol performs better in terms of end-to-end delay, energy consumption, and network lifetime. Selected protocols for comparison are energy-efficient depth-based routing (EEDBR), improved adaptive mobility of courier nodes in threshold-optimized depth-based routing (iAMCTD), cooperative routing protocol for UWSN, and cooperative partner node selection criteria for cooperative routing Coop (Re and dth).

show abstract

Section: Cooperation Phasementioning

confidence: 99%

“…and are the noise components introduced in the links from to and from to , respectively [14], and have the value in terms of the components as given in (3).…”

Section: Cooperation Phasementioning

confidence: 99%

See 1 more Smart Citation

Co-UWSN: Cooperative Energy-Efficient Protocol for Underwater WSNs

Ahmed

Javaid

Khan

et al. 2015

International Journal of Distributed Sensor Networks

View full text Add to dashboard Cite

show abstract

“…ADIO wave propagation in grassy environments has not been studied extensively as compared to studies in forest environments [1], [2], [3], [4], [5], [6]. In some cases, studies of radio propagation have been intended to support animal grazing in large-scale farming [1].…”

Section: Introductionmentioning

confidence: 99%

“…Other studies are focused on anticipated applications of wireless sensor networks (WSNs) in rural areas [2]. Some researchers limit their interest to specific phenomena such as the impact of surface components on signal propagation in different environments [3]. A sample of the studies use both free space path loss (FSPL) and two-ray models which are inaccurate for WSN deployments [7], [8].…”

Section: Introductionmentioning

confidence: 99%

Empirical Path Loss Models for Wireless Sensor Network Deployments in Short and Tall Natural Grass Environments

Olasupo

Otero

Olasupo

et al. 2016

IEEE Trans. Antennas Propagat.

View full text Add to dashboard Cite

Extensive research has not been done on propagation modeling for natural short-and tall-grass environments for the purpose of wireless sensor deployment. This study is essential for efficiently deploying wireless sensors in different applications such as tracking the grazing habits of cows on the grass or monitoring sporting activities. This study proposes empirical path loss models for wireless sensor deployments in grass environments. The proposed models are compared with theoretical models to demonstrate their inaccuracy in predicting path loss between sensor nodes deployed in natural grass environments. Results show that theoretical models deviate from the proposed models by 12 to 42%. Also, results of the proposed models are compared with experimental results obtained from similar natural grassy terrains at different locations resulting in similar outcomes. Finally, the results of the proposed models are compared with previous studies and other terrain models such as those in dense tree environments. These comparisons show that there is significant difference in path loss and empirical models' parameters. The proposed models, as well as the measured data, can be used for efficient planning and future deployments of wireless sensor networks in similar grass terrains.Index Terms-path loss model, RF propagation, short and tall natural grass, terrain, terrain factor, wireless sensor network, XBee radio.

show abstract