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Access Time Analysis of MCPTT Off-Network Mode over LTE
- Source :
- Wireless Communications and Mobile Computing, Vol 2019 (2019)
- Publication Year :
- 2019
- Publisher :
- Hindawi-Wiley, 2019.
-
Abstract
- Public safety organizations around the world started migrating toward Long-Term Evolution (LTE) networks to support the increasing needs for video and data. To address the unique voice communication requirements of first responders, the 3rd Generation Partnership Project (3GPP) introduced new capabilities that aim at providing similar functionalities as the traditional Land Mobile Radio (LMR) systems, namely, Direct Mode communication and mission critical push-to-talk (MCPTT). Direct Mode communication, also called Proximity Services (ProSe), allows public safety users to communicate directly with each other regardless of the network status. MCPTT was the first mission critical service, and first application, standardized by 3GPP to provide both on- and off-network voice capability. Assessing the performance of those capabilities is critical to accelerate their deployment and adoption by first responders. In this study, we evaluate the performance of an off-network mode MCPTT device over ProSe by focusing on the access time, a measure of the delay incurred before a user can talk. We develop analytical models for various types of calls and verify the accuracy of the predicted access time using ns-3 simulations. We perform sensitivity analysis to show the validity of the models for various scenarios. Finally, we show how the models can be used to guide parameter configuration for both MCPTT and ProSe to optimize the performance.
- Subjects :
- Mobile radio
Service (systems architecture)
Measure (data warehouse)
Article Subject
Computer Networks and Communications
Computer science
business.industry
lcsh:T
020206 networking & telecommunications
02 engineering and technology
lcsh:Technology
lcsh:Telecommunication
Mode (computer interface)
lcsh:TK5101-6720
0202 electrical engineering, electronic engineering, information engineering
020201 artificial intelligence & image processing
Electrical and Electronic Engineering
business
Access time
Information Systems
Computer network
Subjects
Details
- Language :
- English
- ISSN :
- 15308677 and 15308669
- Volume :
- 2019
- Database :
- OpenAIRE
- Journal :
- Wireless Communications and Mobile Computing
- Accession number :
- edsair.doi.dedup.....3ca1f04b311a7bd3e0aea65b867005e2