Document
type: Class

Distributed Combining Techniques for Distributed Detection in Fading Wireless Sensor Networks
type: Conference Paper
origen: scopus
related by: authorship_49713
estado: published
type: Article
crisid: 7793
doi: 10.1109/MENACOMM46666.2019.8988544
abstract: We investigate distributed combining techniques for distributed detection in wireless sensor networks (WSNs) over Rayleigh fading multiple access channel (MAC). The MAC also suffers from with path loss and additive noise. The WSN is modelled as a Poisson point process (PPP). Two distributed transmit combining techniques are proposed to mitigate fading; distributed equal gain transmit combining (ddEGTC) and distributed maximum ratio transmit combining (dMRTC). The performance of the previous methods is analysed using stochastic geometry tools, where the mean and variance of the detector%27s test statistic are found thus enabling the fitting of the received signal distribution by a log-normal distribution. Surprisingly, simulation results show a that ddEGTC outperforms dMRTC. © 2019 IEEE.
accesstype: All Open Access, Green
related by: authorship_49715
abstract: We investigate distributed combining techniques for distributed detection in wireless sensor networks (WSNs) over Rayleigh fading multiple access channel (MAC). The MAC also suffers from with path loss and additive noise. The WSN is modelled as a Poisson point process (PPP). Two distributed transmit combining techniques are proposed to mitigate fading; distributed equal gain transmit combining (ddEGTC) and distributed maximum ratio transmit combining (dMRTC). The performance of the previous methods is analysed using stochastic geometry tools, where the mean and variance of the detector's test statistic are found thus enabling the fitting of the received signal distribution by a log-normal distribution. Surprisingly, simulation results show a that ddEGTC outperforms dMRTC. © 2019 IEEE.
artnum: 8988544
type: Entity
related by: authorship_49714
has publication venue: 2019 2nd IEEE Middle East and North Africa COMMunications Conference, MENACOMM 2019
type: Generically Dependent Continuant
type: Thing
freetext keyword: distributed detection; distributed transmit combining; multiple access channel; stochastic geometry; Wireless sensor networks Additive noise; Geometry; Normal distribution; Rayleigh fading; Statistical tests; Stochastic systems; Combining techniques; Distributed detection; distributed transmit combining; Log-normal distribution; Multiple access channels; Poisson point process; Stochastic geometry; Wireless sensor network (WSNs); Wireless sensor networks
type: Document
most specific type: Conference Paper
date time value: conference paper date 7793
type: Continuant
EI dscopus: 2-s2.0-85081100223
related by: authorship_49716
type: Information Content Entity
most specific type: Document
related by: authorship_49712

2019 2nd IEEE Middle East and North Africa COMMunications Conference, MENACOMM 2019
publication venue for: Distributed Combining Techniques for Distributed Detection in Fading Wireless Sensor Networks
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type: Document
type: Thing
type: Generically Dependent Continuant
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type: Continuant
type: Proceedings

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RDF description of Distributed Combining Techniques for Distributed Detection in Fading Wireless Sensor Networks - http://orbis.uaslp.mx/vivo/individual/scopus7792
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date: 2026-08-27T20:05:35
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Conference Paper
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