Long-Range Low-Power Wireless Networks and Sampling Strategies in Electricity Metering
This paper studies a specific low-power wireless technology capable of reaching a long range, namely long range (LoRa). Such a technology can be used by different applications in cities involving many transmitting devices while requiring loose communication constrains. We focus on electricity grids,...
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Veröffentlicht in: | IEEE transactions on industrial electronics (1982) 2019-02, Vol.66 (2), p.1629-1637 |
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description | This paper studies a specific low-power wireless technology capable of reaching a long range, namely long range (LoRa). Such a technology can be used by different applications in cities involving many transmitting devices while requiring loose communication constrains. We focus on electricity grids, where LoRa end-devices are smart meters that send the average power demanded by their respective households during a given period. The successfully decoded data by the LoRa gateway are used by an aggregator to reconstruct the daily households' profiles. We show how the interference from concurrent transmissions from both LoRa and non-LoRa devices negatively affect the communication outage probability and the link effective bit-rate. Besides, we use actual electricity consumption data to compare time-based and event-based sampling strategies, showing the advantages of the latter. We then employ this analysis to assess the gateway range that achieves an average outage probability that leads to a signal reconstruction with a given requirement. We also discuss that, although the proposed analysis focuses on electricity metering, it can be easily extended to any other smart city application with similar requirements, such as water metering or traffic monitoring. |
doi_str_mv | 10.1109/TIE.2018.2816006 |
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Besides, we use actual electricity consumption data to compare time-based and event-based sampling strategies, showing the advantages of the latter. We then employ this analysis to assess the gateway range that achieves an average outage probability that leads to a signal reconstruction with a given requirement. 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J.</creatorcontrib><creatorcontrib>Alves, Hirley</creatorcontrib><title>Long-Range Low-Power Wireless Networks and Sampling Strategies in Electricity Metering</title><title>IEEE transactions on industrial electronics (1982)</title><addtitle>TIE</addtitle><description>This paper studies a specific low-power wireless technology capable of reaching a long range, namely long range (LoRa). Such a technology can be used by different applications in cities involving many transmitting devices while requiring loose communication constrains. We focus on electricity grids, where LoRa end-devices are smart meters that send the average power demanded by their respective households during a given period. The successfully decoded data by the LoRa gateway are used by an aggregator to reconstruct the daily households' profiles. We show how the interference from concurrent transmissions from both LoRa and non-LoRa devices negatively affect the communication outage probability and the link effective bit-rate. Besides, we use actual electricity consumption data to compare time-based and event-based sampling strategies, showing the advantages of the latter. We then employ this analysis to assess the gateway range that achieves an average outage probability that leads to a signal reconstruction with a given requirement. We also discuss that, although the proposed analysis focuses on electricity metering, it can be easily extended to any other smart city application with similar requirements, such as water metering or traffic monitoring.</description><subject>Aggregates</subject><subject>Electric power grids</subject><subject>Electricity</subject><subject>Electricity consumption</subject><subject>Electricity meters</subject><subject>Electronic devices</subject><subject>Event-based sampling</subject><subject>Geometry</subject><subject>Households</subject><subject>Interference</subject><subject>Logic gates</subject><subject>low-power wide-area (LPWA) wireless networks</subject><subject>Probability</subject><subject>Sampling</subject><subject>Signal reconstruction</subject><subject>stochastic geometry</subject><subject>Stochastic processes</subject><subject>Water meters</subject><subject>Wireless networks</subject><issn>0278-0046</issn><issn>1557-9948</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2019</creationdate><recordtype>article</recordtype><sourceid>RIE</sourceid><recordid>eNo9kEtLAzEUhYMoWKt7wU3A9dRkMnktpVQt1Ae26jLEzJ0hdTpTk5TSf--UFld3cb5zLnwIXVMyopTou8V0MsoJVaNcUUGIOEEDyrnMtC7UKRqQXKqMkEKco4sYl4TQglM-QJ-zrq2zd9vWgGfdNnvrthDwlw_QQIz4BdK2Cz8R27bEc7taN76t8TwFm6D2ELFv8aQBl4J3Pu3wMyQIPXKJzirbRLg63iH6eJgsxk_Z7PVxOr6fZY4xljIndKkqyYUsqbTKOVfaUnDNCsKk4IpX3xUluaqsLrVkxHFQkjoQBenDQrEhuj3srkP3u4GYzLLbhLZ_aXJKuWJMSNFT5EC50MUYoDLr4Fc27AwlZm_P9PbM3p452usrN4eKB4B_XDEqNOfsD-dnao0</recordid><startdate>20190201</startdate><enddate>20190201</enddate><creator>de Castro Tome, Mauricio</creator><creator>Nardelli, Pedro H. 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J. ; Alves, Hirley</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c333t-c69d8f7567d17a8cccdad659340376585fbf1028fa9d9730c5e871ce640585483</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2019</creationdate><topic>Aggregates</topic><topic>Electric power grids</topic><topic>Electricity</topic><topic>Electricity consumption</topic><topic>Electricity meters</topic><topic>Electronic devices</topic><topic>Event-based sampling</topic><topic>Geometry</topic><topic>Households</topic><topic>Interference</topic><topic>Logic gates</topic><topic>low-power wide-area (LPWA) wireless networks</topic><topic>Probability</topic><topic>Sampling</topic><topic>Signal reconstruction</topic><topic>stochastic geometry</topic><topic>Stochastic processes</topic><topic>Water meters</topic><topic>Wireless networks</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>de Castro Tome, Mauricio</creatorcontrib><creatorcontrib>Nardelli, Pedro H. J.</creatorcontrib><creatorcontrib>Alves, Hirley</creatorcontrib><collection>IEEE All-Society Periodicals Package (ASPP) 2005-present</collection><collection>IEEE All-Society Periodicals Package (ASPP) 1998-Present</collection><collection>IEEE Electronic Library (IEL)</collection><collection>CrossRef</collection><collection>Electronics & Communications Abstracts</collection><collection>Technology Research Database</collection><collection>Advanced Technologies Database with Aerospace</collection><jtitle>IEEE transactions on industrial electronics (1982)</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>de Castro Tome, Mauricio</au><au>Nardelli, Pedro H. J.</au><au>Alves, Hirley</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Long-Range Low-Power Wireless Networks and Sampling Strategies in Electricity Metering</atitle><jtitle>IEEE transactions on industrial electronics (1982)</jtitle><stitle>TIE</stitle><date>2019-02-01</date><risdate>2019</risdate><volume>66</volume><issue>2</issue><spage>1629</spage><epage>1637</epage><pages>1629-1637</pages><issn>0278-0046</issn><eissn>1557-9948</eissn><coden>ITIED6</coden><abstract>This paper studies a specific low-power wireless technology capable of reaching a long range, namely long range (LoRa). Such a technology can be used by different applications in cities involving many transmitting devices while requiring loose communication constrains. We focus on electricity grids, where LoRa end-devices are smart meters that send the average power demanded by their respective households during a given period. The successfully decoded data by the LoRa gateway are used by an aggregator to reconstruct the daily households' profiles. We show how the interference from concurrent transmissions from both LoRa and non-LoRa devices negatively affect the communication outage probability and the link effective bit-rate. Besides, we use actual electricity consumption data to compare time-based and event-based sampling strategies, showing the advantages of the latter. We then employ this analysis to assess the gateway range that achieves an average outage probability that leads to a signal reconstruction with a given requirement. 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subjects | Aggregates Electric power grids Electricity Electricity consumption Electricity meters Electronic devices Event-based sampling Geometry Households Interference Logic gates low-power wide-area (LPWA) wireless networks Probability Sampling Signal reconstruction stochastic geometry Stochastic processes Water meters Wireless networks |
title | Long-Range Low-Power Wireless Networks and Sampling Strategies in Electricity Metering |
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