Loading…

Closed-Form Path-Loss Predictor for Gaussianly Distributed Nodes

The emulation of wireless nodes spatial position is a practice used by deployment engineers and network planners to analyze the characteristics of a network. In particular, nodes geolocation will directly impact factors such as connectivity, signals fidelity, and service quality. In literature, in a...

Full description

Saved in:
Bibliographic Details
Main Authors: Abdulla, M, Shayan, Y R
Format: Conference Proceeding
Language:English
Subjects:
Online Access:Request full text
Tags: Add Tag
No Tags, Be the first to tag this record!
cited_by
cites
container_end_page 6
container_issue
container_start_page 1
container_title
container_volume
creator Abdulla, M
Shayan, Y R
description The emulation of wireless nodes spatial position is a practice used by deployment engineers and network planners to analyze the characteristics of a network. In particular, nodes geolocation will directly impact factors such as connectivity, signals fidelity, and service quality. In literature, in addition to typical homogenous scattering, normal distribution is frequently used to model mobiles concentration in a cellular system. Moreover, Gaussian dropping is often considered as an effective placement method for airborne sensor deployment. Despite the practicality of this model, getting the network channel loss distribution still relies on exhaustive Monte Carlo simulation. In this paper, we argue the need for this inefficient approach and hence derived a generic and exact closed-form expression for the path-loss distribution density between a base-station and a network of nodes. Simulation was used to reaffirm the validity of the theoretical analysis using values from the new IEEE 802.20 standard.
doi_str_mv 10.1109/ICC.2010.5502200
format conference_proceeding
fullrecord <record><control><sourceid>ieee_6IE</sourceid><recordid>TN_cdi_ieee_primary_5502200</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><ieee_id>5502200</ieee_id><sourcerecordid>5502200</sourcerecordid><originalsourceid>FETCH-LOGICAL-i175t-b596c0d482e1cf85faed7e1d5fa385127016205ce47f6aed516ef7f3b73072b3</originalsourceid><addsrcrecordid>eNpFkDtPw0AQhI9HJJxAj0TjP3Bh997uQA4JkSxIkYIusn174lCCkc8p8u-xRCSK0ezo02wxjN0jzBGheFyX5VzAmLQGIQAu2BSVUMookB-XLMNCOo7Oyat_IPB6BGOBSwN2wjKH3KhCK3vDpil9AWhRSMzYU7nvEnm-7PpDvqmHT151KeWbnnxsh67Pw6hVfUwp1t_7U76IaehjcxzI52-dp3TLJqHeJ7o7-4xtly_b8pVX76t1-VzxiFYPvNGFacErJwjb4HSoyVtCPx7SaRQW0AjQLSkbzMg0Ggo2yMZKsKKRM_bw9zYS0e6nj4e6P-3Oi8hf9hhN8w</addsrcrecordid><sourcetype>Publisher</sourcetype><iscdi>true</iscdi><recordtype>conference_proceeding</recordtype></control><display><type>conference_proceeding</type><title>Closed-Form Path-Loss Predictor for Gaussianly Distributed Nodes</title><source>IEEE Electronic Library (IEL) Conference Proceedings</source><creator>Abdulla, M ; Shayan, Y R</creator><creatorcontrib>Abdulla, M ; Shayan, Y R</creatorcontrib><description>The emulation of wireless nodes spatial position is a practice used by deployment engineers and network planners to analyze the characteristics of a network. In particular, nodes geolocation will directly impact factors such as connectivity, signals fidelity, and service quality. In literature, in addition to typical homogenous scattering, normal distribution is frequently used to model mobiles concentration in a cellular system. Moreover, Gaussian dropping is often considered as an effective placement method for airborne sensor deployment. Despite the practicality of this model, getting the network channel loss distribution still relies on exhaustive Monte Carlo simulation. In this paper, we argue the need for this inefficient approach and hence derived a generic and exact closed-form expression for the path-loss distribution density between a base-station and a network of nodes. Simulation was used to reaffirm the validity of the theoretical analysis using values from the new IEEE 802.20 standard.</description><identifier>ISSN: 1550-3607</identifier><identifier>ISBN: 1424464021</identifier><identifier>ISBN: 9781424464029</identifier><identifier>EISSN: 1938-1883</identifier><identifier>EISBN: 142446403X</identifier><identifier>EISBN: 9781424464043</identifier><identifier>EISBN: 1424464048</identifier><identifier>EISBN: 9781424464036</identifier><identifier>DOI: 10.1109/ICC.2010.5502200</identifier><identifier>LCCN: 81-649547</identifier><language>eng</language><publisher>IEEE</publisher><subject>Communications Society ; Emulation ; Gaussian distribution ; Global Positioning System ; Humans ; Peer to peer computing ; Scattering ; Stochastic processes ; Surface topography ; Wireless sensor networks</subject><ispartof>2010 IEEE International Conference on Communications, 2010, p.1-6</ispartof><woscitedreferencessubscribed>false</woscitedreferencessubscribed></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://ieeexplore.ieee.org/document/5502200$$EHTML$$P50$$Gieee$$H</linktohtml><link.rule.ids>309,310,780,784,789,790,2058,27925,54555,54920,54932</link.rule.ids><linktorsrc>$$Uhttps://ieeexplore.ieee.org/document/5502200$$EView_record_in_IEEE$$FView_record_in_$$GIEEE</linktorsrc></links><search><creatorcontrib>Abdulla, M</creatorcontrib><creatorcontrib>Shayan, Y R</creatorcontrib><title>Closed-Form Path-Loss Predictor for Gaussianly Distributed Nodes</title><title>2010 IEEE International Conference on Communications</title><addtitle>ICC</addtitle><description>The emulation of wireless nodes spatial position is a practice used by deployment engineers and network planners to analyze the characteristics of a network. In particular, nodes geolocation will directly impact factors such as connectivity, signals fidelity, and service quality. In literature, in addition to typical homogenous scattering, normal distribution is frequently used to model mobiles concentration in a cellular system. Moreover, Gaussian dropping is often considered as an effective placement method for airborne sensor deployment. Despite the practicality of this model, getting the network channel loss distribution still relies on exhaustive Monte Carlo simulation. In this paper, we argue the need for this inefficient approach and hence derived a generic and exact closed-form expression for the path-loss distribution density between a base-station and a network of nodes. Simulation was used to reaffirm the validity of the theoretical analysis using values from the new IEEE 802.20 standard.</description><subject>Communications Society</subject><subject>Emulation</subject><subject>Gaussian distribution</subject><subject>Global Positioning System</subject><subject>Humans</subject><subject>Peer to peer computing</subject><subject>Scattering</subject><subject>Stochastic processes</subject><subject>Surface topography</subject><subject>Wireless sensor networks</subject><issn>1550-3607</issn><issn>1938-1883</issn><isbn>1424464021</isbn><isbn>9781424464029</isbn><isbn>142446403X</isbn><isbn>9781424464043</isbn><isbn>1424464048</isbn><isbn>9781424464036</isbn><fulltext>true</fulltext><rsrctype>conference_proceeding</rsrctype><creationdate>2010</creationdate><recordtype>conference_proceeding</recordtype><sourceid>6IE</sourceid><recordid>eNpFkDtPw0AQhI9HJJxAj0TjP3Bh997uQA4JkSxIkYIusn174lCCkc8p8u-xRCSK0ezo02wxjN0jzBGheFyX5VzAmLQGIQAu2BSVUMookB-XLMNCOo7Oyat_IPB6BGOBSwN2wjKH3KhCK3vDpil9AWhRSMzYU7nvEnm-7PpDvqmHT151KeWbnnxsh67Pw6hVfUwp1t_7U76IaehjcxzI52-dp3TLJqHeJ7o7-4xtly_b8pVX76t1-VzxiFYPvNGFacErJwjb4HSoyVtCPx7SaRQW0AjQLSkbzMg0Ggo2yMZKsKKRM_bw9zYS0e6nj4e6P-3Oi8hf9hhN8w</recordid><startdate>201005</startdate><enddate>201005</enddate><creator>Abdulla, M</creator><creator>Shayan, Y R</creator><general>IEEE</general><scope>6IE</scope><scope>6IH</scope><scope>CBEJK</scope><scope>RIE</scope><scope>RIO</scope></search><sort><creationdate>201005</creationdate><title>Closed-Form Path-Loss Predictor for Gaussianly Distributed Nodes</title><author>Abdulla, M ; Shayan, Y R</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-i175t-b596c0d482e1cf85faed7e1d5fa385127016205ce47f6aed516ef7f3b73072b3</frbrgroupid><rsrctype>conference_proceedings</rsrctype><prefilter>conference_proceedings</prefilter><language>eng</language><creationdate>2010</creationdate><topic>Communications Society</topic><topic>Emulation</topic><topic>Gaussian distribution</topic><topic>Global Positioning System</topic><topic>Humans</topic><topic>Peer to peer computing</topic><topic>Scattering</topic><topic>Stochastic processes</topic><topic>Surface topography</topic><topic>Wireless sensor networks</topic><toplevel>online_resources</toplevel><creatorcontrib>Abdulla, M</creatorcontrib><creatorcontrib>Shayan, Y R</creatorcontrib><collection>IEEE Electronic Library (IEL) Conference Proceedings</collection><collection>IEEE Proceedings Order Plan (POP) 1998-present by volume</collection><collection>IEEE Xplore All Conference Proceedings</collection><collection>IEEE Xplore</collection><collection>IEEE Proceedings Order Plans (POP) 1998-present</collection></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>Abdulla, M</au><au>Shayan, Y R</au><format>book</format><genre>proceeding</genre><ristype>CONF</ristype><atitle>Closed-Form Path-Loss Predictor for Gaussianly Distributed Nodes</atitle><btitle>2010 IEEE International Conference on Communications</btitle><stitle>ICC</stitle><date>2010-05</date><risdate>2010</risdate><spage>1</spage><epage>6</epage><pages>1-6</pages><issn>1550-3607</issn><eissn>1938-1883</eissn><isbn>1424464021</isbn><isbn>9781424464029</isbn><eisbn>142446403X</eisbn><eisbn>9781424464043</eisbn><eisbn>1424464048</eisbn><eisbn>9781424464036</eisbn><abstract>The emulation of wireless nodes spatial position is a practice used by deployment engineers and network planners to analyze the characteristics of a network. In particular, nodes geolocation will directly impact factors such as connectivity, signals fidelity, and service quality. In literature, in addition to typical homogenous scattering, normal distribution is frequently used to model mobiles concentration in a cellular system. Moreover, Gaussian dropping is often considered as an effective placement method for airborne sensor deployment. Despite the practicality of this model, getting the network channel loss distribution still relies on exhaustive Monte Carlo simulation. In this paper, we argue the need for this inefficient approach and hence derived a generic and exact closed-form expression for the path-loss distribution density between a base-station and a network of nodes. Simulation was used to reaffirm the validity of the theoretical analysis using values from the new IEEE 802.20 standard.</abstract><pub>IEEE</pub><doi>10.1109/ICC.2010.5502200</doi><tpages>6</tpages></addata></record>
fulltext fulltext_linktorsrc
identifier ISSN: 1550-3607
ispartof 2010 IEEE International Conference on Communications, 2010, p.1-6
issn 1550-3607
1938-1883
language eng
recordid cdi_ieee_primary_5502200
source IEEE Electronic Library (IEL) Conference Proceedings
subjects Communications Society
Emulation
Gaussian distribution
Global Positioning System
Humans
Peer to peer computing
Scattering
Stochastic processes
Surface topography
Wireless sensor networks
title Closed-Form Path-Loss Predictor for Gaussianly Distributed Nodes
url http://sfxeu10.hosted.exlibrisgroup.com/loughborough?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-01-03T19%3A22%3A18IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-ieee_6IE&rft_val_fmt=info:ofi/fmt:kev:mtx:book&rft.genre=proceeding&rft.atitle=Closed-Form%20Path-Loss%20Predictor%20for%20Gaussianly%20Distributed%20Nodes&rft.btitle=2010%20IEEE%20International%20Conference%20on%20Communications&rft.au=Abdulla,%20M&rft.date=2010-05&rft.spage=1&rft.epage=6&rft.pages=1-6&rft.issn=1550-3607&rft.eissn=1938-1883&rft.isbn=1424464021&rft.isbn_list=9781424464029&rft_id=info:doi/10.1109/ICC.2010.5502200&rft.eisbn=142446403X&rft.eisbn_list=9781424464043&rft.eisbn_list=1424464048&rft.eisbn_list=9781424464036&rft_dat=%3Cieee_6IE%3E5502200%3C/ieee_6IE%3E%3Cgrp_id%3Ecdi_FETCH-LOGICAL-i175t-b596c0d482e1cf85faed7e1d5fa385127016205ce47f6aed516ef7f3b73072b3%3C/grp_id%3E%3Coa%3E%3C/oa%3E%3Curl%3E%3C/url%3E&rft_id=info:oai/&rft_id=info:pmid/&rft_ieee_id=5502200&rfr_iscdi=true