Modeling Cellular Network Infrastructure in SUMO
Communication networks are becoming an increasingly important part of the mobility system. They allow traffic participants to be connected and to exchange information related to traffic and roads. The information exchange impacts the behavior of traffic participants, such as the selection of travel routes or their mobility dynamics. Considering infrastructure-based networks, the information exchange depends on the availability of the network infrastructure and the quality of the communication links. Specifically in urban areas, today’s 4G and 5G networks deploy small cells of high capacity, which do not provide ubiquitous cellular coverage due to their small range, signal blocking, etc. Therefore, the accurate modeling of the network infrastructure and its integration in simulation scenarios in microscopic traffic simulation software is gaining relevance.
Unlike traffic infrastructure, such as traffic lights, the simulation of a cellular network infrastructure is not natively supported in SUMO. Instead, the protocols, functions and entities of the communication system with the physical wireless transmission are modeled in a dedicated and specialized network simulator that is coupled with SUMO. The disadvantage of this approach is that the simulated SUMO entities, typically vehicles, are not aware which portions of the roads are covered by wireless cells and what quality the wireless communication links have.
In this paper, we propose a method for modeling the cellular infrastructure in SUMO that introduces a cellular coverage layer to SUMO. This layer models cell sites in a regular hexagonal grid, where each site is served by a base station. Following commonly accepted guidelines for the evaluation of cellular communication system, the method facilitates standardized and realistic modeling of the cellular coverage, including cell sites, antenna characteristics, cell association and handover. In order to ease the applicability of the method, we describe the work flow to create cell sites. As a representative case, we have applied the method to InTAS, the SUMO Ingolstadt traffic scenario and applied real data for the cellular infrastructure. We validate the approach by simulating a Cellular V2X system with sidelink connectivity in an urban macro cell environment by coupling SUMO enhanced by the proposed connectivity sublayer with ARTERY-C, a network simulator for Cellular V2X. As a proof-of-concept, we present a signal-to-interference noise ratio (SINR) coverage map and further evaluate the impact of different types of interference. We also demonstrate the effect of advanced features of cellular networks such as inter-cell interference coordination (ICIC) and sidelink communication modes of Cellular V2X with dynamic switching between the in-coverage and out-of-coverage mode.
5G Automotive Association (5GAA). The case for Cellular V2X for safety and cooperative driving, 2016. Whitepaper, https://bit.ly/3fiK7kK.
Anupama Hegde and Andreas Festag. Mode switching strategies in Cellular V2X. IFAC Symposium, 52(8):81–86, September 2019.
Anupama Hegde and Andreas Festag. Artery-C: An OMNeT++ based discrete event simulation framework for Cellular V2X. In ACM MSWiM, November 2020.
Anupama Hegde and Andreas Festag. Mode switching performance in Cellular-V2X. In IEEE VNC, December 2020.
ITU-R. Guidelines for evaluation of radio interface technologies for IMT-2020, 2017. Technical Report M.412-0, https://www.itu.int/pub/R-REP-M.2412-2017.
Sebastian Kühlmorgen, Patrick Schmager, Andreas Festag, and Gerhard Fettweis. Simulation-based evaluation of ETSI ITS-G5 and Cellular-VCS in a real-world road traffic scenario. In IEEE VTC-Fall, August 2018.
Vineet Kumar et al. iTETRIS: Adaptation of ITS technologies for large scale integrated simulation. In IEEE VTC-Spring, 2010.
Pekka Kyösti et al. WINNER II channel models, February 2008. Technical Report IST-4-027756WINNER II D1.1.2 V1.2.
Kwonjong Lee, Joonki Kim, Yosub Park, Hanho Wang, and Daesik Hong. Latency of Cellular-based V2X: Perspectives on TTI-proportional latency and TTI-independent latency. IEEE Access, 5:15800–15809, July 2017.
Silas C. Lobo, Stefan Neumeier, Evelio M. G. Fernandez, and Christian Facchi. InTAS – The Ingolstadt traffic scenario for SUMO. In SUMO Conference 2020, October 2020. https://arxiv.org/abs/2011.11995.
Pablo Alvarez Lopez et al. Microscopic traffic simulation using SUMO. In IEEE ITSC, November 2018.
Brian McCarthy and Aisling O’Driscoll. OpenCV2X Mode 4: A simulation extension for cellular vehicular communication networks. In IEEE CAMAD, October 2019.
Giovanni Nardini, Dario Sabella, Giovanni Stea, Purvi Thakkar, and Antonio Virdis. Simu5G – an OMNeT++ library for end-to-end performance evaluation of 5G networks. IEEE Access, 8:181176–181191, 2020.
Raphael Riebl, Hendrik Günther, Christian Facchi, and Lars Wolf. Artery: Extending Veins for VANET applications. In IEEE MT-ITS, June 2015.
Christoph Sommer, Reinhard German, and Falko Dressler. Bidirectionally coupled network and road traffic simulation for improved IVC analysis. IEEE Transactions on Mobile Computing,10(1):3–15, 2011.
Antonio Virdis, Giovanni Stea, and Giovanni Nardinis. Simulating LTE/LTE-Advanced networks with SimuLTE. In M. S. Obaidat, T. Ören, J. Kacprzyk, and J. Filipe, editors, Simulation and Modeling Methodologies, Technologies and Applications, pages 83–105. Springer, Cham, 2015.
Axel Wegener et al. TraCI: An interface for coupling road traffic and network simulators. In ACM CNS Symposium, 2008.
How to Cite
Copyright (c) 2022 Anupama Hegde, Ringo Stahl, Silas Lobo, Andreas Festag
This work is licensed under a Creative Commons Attribution 3.0 Unported License.