Imperial College London
Portrait Picture

ProfessorJulieMcCann

Faculty of Engineering, Department of Computing

Vice-Dean (Research) for the Faculty of Engineering
 
 
 
//

Contact

 

+44 (0)20 7594 8375j.mccann Website

 
 
//

Assistant

 

Miss Teresa Ng +44 (0)20 7594 8300

 
//

Location

 

260ACE ExtensionSouth Kensington Campus

//

Summary

 

Publications

Citation

BibTex format

@article{Qin:2019:10.1109/TVT.2019.2920731,
author = {Qin, Z and Liu, Y and Li, GY and McCann, JA},
doi = {10.1109/TVT.2019.2920731},
journal = {IEEE Transactions on Vehicular Technology},
pages = {7616--7629},
title = {Performance analysis of clustered LoRa networks},
url = {http://dx.doi.org/10.1109/TVT.2019.2920731},
volume = {68},
year = {2019}
}
Download

RIS format (EndNote, RefMan)

TY  - JOUR
AB  - 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.
AU  - Qin,Z
AU  - Liu,Y
AU  - Li,GY
AU  - McCann,JA
DO  - 10.1109/TVT.2019.2920731
EP  - 7629
PY  - 2019///
SN  - 0018-9545
SP  - 7616
TI  - Performance analysis of clustered LoRa networks
T2  - IEEE Transactions on Vehicular Technology
UR  - http://dx.doi.org/10.1109/TVT.2019.2920731
UR  - http://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcApp=PARTNER_APP&SrcAuth=LinksAMR&KeyUT=WOS:000481944300032&DestLinkType=FullRecord&DestApp=ALL_WOS&UsrCustomerID=1ba7043ffcc86c417c072aa74d649202
UR  - http://hdl.handle.net/10044/1/74478
VL  - 68
ER  -
Download