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- Publisher Website: 10.1109/TVT.2019.2920731
- Scopus: eid_2-s2.0-85074979109
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Article: Performance analysis of clustered LoRa networks
Title | Performance analysis of clustered LoRa networks |
---|---|
Authors | |
Keywords | LoRa Low-power wide-area networks Poisson cluster process Stochastic geometry |
Issue Date | 2019 |
Citation | IEEE Transactions on Vehicular Technology, 2019, v. 68, n. 8, p. 7616-7629 How to Cite? |
Abstract | In this paper, we investigate the uplink transmission performance of low-power wide-area (LPWA) networks with regards to coexisting radio modules. We adopt the long-range (LoRa) radio technique as an example of the network of focus, even though our analysis can be easily extended to other situations. We exploit a new topology to model the network, where the node locations of LoRa follow a Poisson cluster process while other coexisting radio modules follow a Poisson point process. Unlike most of the performance analysis based on stochastic geometry, we take noise into consideration. More specifically, two models, with a fixed and a random number of active LoRa nodes in each cluster, respectively, are considered. To obtain insights, both the exact and simple approximated expressions for coverage probability are derived. Based on them, area spectral efficiency and energy efficiency are obtained. From our analysis, we show how the performance of LPWA networks can be enhanced by adjusting the density of LoRa nodes around each LoRa receiver. Moreover, the simulation results unveil that the optimal number of active LoRa nodes in each cluster exists to maximize the area spectral efficiency. |
Persistent Identifier | http://hdl.handle.net/10722/349366 |
ISSN | 2023 Impact Factor: 6.1 2023 SCImago Journal Rankings: 2.714 |
DC Field | Value | Language |
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dc.contributor.author | Qin, Zhijin | - |
dc.contributor.author | Liu, Yuanwei | - |
dc.contributor.author | Li, Geoffrey Ye | - |
dc.contributor.author | McCann, Julie A. | - |
dc.date.accessioned | 2024-10-17T06:58:03Z | - |
dc.date.available | 2024-10-17T06:58:03Z | - |
dc.date.issued | 2019 | - |
dc.identifier.citation | IEEE Transactions on Vehicular Technology, 2019, v. 68, n. 8, p. 7616-7629 | - |
dc.identifier.issn | 0018-9545 | - |
dc.identifier.uri | http://hdl.handle.net/10722/349366 | - |
dc.description.abstract | In this paper, we investigate the uplink transmission performance of low-power wide-area (LPWA) networks with regards to coexisting radio modules. We adopt the long-range (LoRa) radio technique as an example of the network of focus, even though our analysis can be easily extended to other situations. We exploit a new topology to model the network, where the node locations of LoRa follow a Poisson cluster process while other coexisting radio modules follow a Poisson point process. Unlike most of the performance analysis based on stochastic geometry, we take noise into consideration. More specifically, two models, with a fixed and a random number of active LoRa nodes in each cluster, respectively, are considered. To obtain insights, both the exact and simple approximated expressions for coverage probability are derived. Based on them, area spectral efficiency and energy efficiency are obtained. From our analysis, we show how the performance of LPWA networks can be enhanced by adjusting the density of LoRa nodes around each LoRa receiver. Moreover, the simulation results unveil that the optimal number of active LoRa nodes in each cluster exists to maximize the area spectral efficiency. | - |
dc.language | eng | - |
dc.relation.ispartof | IEEE Transactions on Vehicular Technology | - |
dc.subject | LoRa | - |
dc.subject | Low-power wide-area networks | - |
dc.subject | Poisson cluster process | - |
dc.subject | Stochastic geometry | - |
dc.title | Performance analysis of clustered LoRa networks | - |
dc.type | Article | - |
dc.description.nature | link_to_subscribed_fulltext | - |
dc.identifier.doi | 10.1109/TVT.2019.2920731 | - |
dc.identifier.scopus | eid_2-s2.0-85074979109 | - |
dc.identifier.volume | 68 | - |
dc.identifier.issue | 8 | - |
dc.identifier.spage | 7616 | - |
dc.identifier.epage | 7629 | - |
dc.identifier.eissn | 1939-9359 | - |