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PUBLICATIONS

Access Time Analysis of MCPTT Off-Network Mode over LTE

Published

Author(s)

Yishen Sun, Wesley D. Garey, Richard A. Rouil, Priam C. Varin

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 requirements of first responders, the Third 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 that 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 based 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 in order to optimize the performance.
Citation
Wireless Communications and Mobile Computing
Volume
2019
Pub Type
Journals

Download Paper

https://doi.org/10.1155/2019/2729370

Keywords

Mission Critical Push to Talk (MCPTT), Access Time, Proximity Services, Off-Network Mode, Direct Mode
Public safety communications research

Citation

Sun, Y. , Garey, W. , Rouil, R. and Varin, P. (2019), Access Time Analysis of MCPTT Off-Network Mode over LTE, Wireless Communications and Mobile Computing, [online], https://doi.org/10.1155/2019/2729370 (Accessed April 25, 2024)

Created April 2, 2019, Updated April 12, 2019