Impact of the Physical Layer Modeling on the Accuracy and Scalability of Wireless Network Simulation

  • Authors:

  • Elyes Ben Hamida;Guillaume Chelius;Jean Marie Gorce

  • Affiliations:

  • University of Lyon, INSA de Lyon, INRIA, Domaine Scientifiquede la Doua - INSA Lyon, Batiment Claude Chappe, 6 avenue des Arts, 69621 VilleurbanneCedex, France;University of Lyon, INRIA, ENS Lyon, Ecole Normale Supérieurede Lyon, 46, allée d'Italie, 69364 Lyon Cedex 07, France;University of Lyon, INSA de Lyon, INRIA, Domaine Scientifiquede la Doua - INSA Lyon, Batiment Claude Chappe, 6 avenue des Arts, 69621 VilleurbanneCedex, France

  • Venue:
  • Simulation
  • Year:
  • 2009

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Abstract

Recent years have witnessed a tremendous growth of research in the field of wireless systems and networking protocols. Consequently, simulation has appeared as the most convenient approach for the performance evaluation of such systems and several wireless network simulators have been proposed in recent years. However, the complexity of the wireless physical layer (PHY) induces a clear tradeoff between the accuracy and the scalability of simulators. Thereby, the accuracy of the simulation results varies drastically from one simulator to another. In this paper, we focus on this tradeoff and we investigate the impact of the physical layer modeling accuracy on both the computational cost and the confidence in simulations. We first provide a detailed discussion on physical layer issues, including the radio range, link and interference modeling, and we investigate how they have been handled in existing popular simulators. We then introduce a flexible and modular new wireless network simulator, called WSNet. Using this simulator, we analyze the influence of the PHY modeling on the performance and the accuracy of simulations. The results show that the PHY modeling, and in particular interference modeling, can have a significant impact on the behavior of the evaluated protocols at the expense of an increased computational overhead. Moreover, we show that the use of realistic propagation models can improve the simulation accuracy without inducing a severe degradation of scalability.