International audienceMany research on VANETs present new propagation models. This paper focus on the last optimisation of the UM-CRT model proposed by the XLIM-SIC Laboratory. The model is simplified in order to obtain a faster computation time without reducing the realism of the UM-CRT model and new criteria computed from the impulse response are also shown

Bouhadi, Slimane

Ledy, Jonathan

Poussard, Anne-Marie

HAL-UNILIM

UM-CRT model optimisationSlimane Bouhadi, Jonathan Ledy, Anne-Marie PoussardTo cite this version:Slimane Bouhadi, Jonathan Ledy, Anne-Marie Poussard. UM-CRT model optimisation.Journe´es Nationales des Communications dans les Transports Terrestres, Nov 2011, Colmar,France. <hal-00658998>HAL Id: hal-00658998https://hal.archives-ouvertes.fr/hal-00658998Submitted on 13 Jan 2012HAL is a multi-disciplinary open accessarchive for the deposit and dissemination of sci-entific research documents, whether they are pub-lished or not. The documents may come fromteaching and research institutions in France orabroad, or from public or private research centers.L’archive ouverte pluridisciplinaire HAL, estdestine´e au de´poˆt et a` la diffusion de documentsscientifiques de niveau recherche, publie´s ou non,e´manant des e´tablissements d’enseignement et derecherche franc¸ais ou e´trangers, des laboratoirespublics ou prive´s.CopyrightJournées Nationales des Communications dans les Transports Terrestres3-4 Nov. 2011, IUT, ColmarUM-CRT model optimisationSlimane Bouhadi#, Jonathan Ledy#*, Anne-Marie Poussard## Laboratoire XLIM-SIC, UMR CNRS 6172, Université de Poitiers, France* Laboratoire MIPS-GRTC, Université de Haute-Alsace, Francejonathan.ledy@univ-poitiers.frAbstract— Many research on VANETs present new propagation models. This paper focus on the last optimisation of the UM-CRT model  proposed  by  the  XLIM-SIC  Laboratory.  The  model  is simplified in order to obtain a faster computation time without reducing the  realism of  the  UM-CRT model  and new criteria computed from the impulse response are also shown.I. INTRODUCTIONVehicles  wireless  networks  are  called  Vehicular  Ad-hoc NETworks (VANETs). Finding an accurate channel model for VANETs simulations is an important research issue [1].This short paper is organised as follows. Section II give a brief  overview  of  the  UM-CRT  semi-deterministic  model. Section III present the optimisation of the model and  shows some results. Finally section IV conclude the paper.II. UM-CRT MODELIn [2], Ledy et al. proposed a semi-deterministic solution which  benefits  from  both  advantages  of  statistical  and deterministic channel models. This new model is called UM-CRT because  it  is  based  on  the  statistical  Spacial  Channel Model  Extended  in  it's  Urban  Micro  (SCME-UM) environment  [3],  and  deterministic  Communication  Ray Tracer (CRT) simulator [4].Figure 1. Principle of the UM-CRT modelFigure 1 shows the relationship between UM-CRT and both CRT and  SCME-UM.  For  all  radio  links  existing  between nodes,  CRT  computes  Impulse  Responses  (IRs)  of  all  the received multi-paths according to a 3D environment. On the other  hand,  SCME-UM provides  statistically generated  IRs. Ledy et al. proposed to limit the search path by ray-tracing only to the direct path because it is well known that this path has the main impact on the received signal.III. MODEL OPTIMISATION AND NEW CRITERIAIn the previous UM-CRT build, the Line Of Sight (LOS) criteria was determined using the computed delay of the first IR for each links. We modified it to create an IR only in LOS cases, so the Non LOS cases do not need to be computed.Using  this  new  build,  two  simulations  with  20  nodes moving at 15m/s with 3 simultaneous communications takes less than 1 minutes while it  took 3 minutes with the oldest build.  Preliminary  test  shows  that  optimised  UM-CRT and original UM-CRT give the same results in term of behaviour.In addition to this optimisation, we also compute from the IRs two new metrics that are the Capacity and Probability of Outage. They are both good indicators of the quality of radio links and could be combined with LOS/NLOS criteria.Figure 2. Capacity and Probability of Outage versus Signal to Noise RatioFigure 2 shows the two metrics depending on the SNR. The Capacity  of  Outage  is  computed  for  MIMO  and  SISO technologies, as the Probability of Outage is computed for 16 and  64  QAM modulation.  We can  therefore  see  that  these indicators  accurately  reflects  the  properties/quality  of  the channel.IV. CONCLUSIONSIn this paper,  we presented an optimisation for the UM-CRT model. We showed that the results of this optimisation are very similar to the standard one, and that the simulation time had been improved.  New criteria  that  may be used in combination with the LOS-NLOS criteria are also presented.REFERENCES[1] F.  J.  Martinez,  C.-K.  Toh,  J.-C.  Cano,  C.  T.  Calafate  and  P. Manzoni,   "Realistic   Radio   Propagation   Models   (RPMs)   for  VANET   Simulations",   IEEE   Wireless   Communications   and Networking Conference 2009, Mar. 2009. [2] J. Ledy, H. Boeglen, A-M. Poussard, B. Hilt, R. Vauzelle, “A Semi-Deterministic Channel Model for VANETs Simulations”, International Journal of Vehicular Technology, Volume 2012[3] D.  S.  Baum,  J.  Hansen,  J.  Salo,  "An  interim  channel  model   for beyond-3G  systems:  extending  the  3GPP  spatial  channel model  (SCM)",  2005  IEEE  61st  Vehicular  Technology  Conference, VTC 2005-Spring, volume 5, pp. 3132-3136, 2005. [4] F.  Escarieu,  V.  Degardin,  L.  Aveneau, R.  Vauzelle,  Y. Pousset,  M. Lienard, P. Degauque, "3D modelling of the propagation in an indoor environment : a  theoretical  and  experimental  approach",  pp 217-220, ECWT’2001, London, UK, Sept. 2001. --- 64-QAM--- 16-QAM--- MIMO--- SISO

UM-CRT model optimisation

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