60 research outputs found

    A channel model and coding for vehicle to vehicle communication based on a developed V-SCME

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    Over the recent years, VANET communication has attracted a lot of attention due to its potential in facilitating the implementation of 'Intelligent Transport System'. Vehicular applications need to be completely tested before deploying them in the real world. In this context, VANET simulations would be preferred in order to evaluate and validate the proposed model, these simulations are considered inexpensive compared to the real world (hardware) tests. The development of a more realistic simulation environment for VANET is critical in ensuring high performance. Any environment required for simulating VANET, needs to be more realistic and include a precise representation of vehicle movements, as well as passing signals among different vehicles. In order to achieve efficient results that reflect the reality, a high computational power during the simulation is needed which consumes a lot of time. The existing simulation tools could not simulate the exact physical conditions of the real world, so results can be viewed as unsatisfactory when compared with real world experiments. This thesis describes two approaches to improve such vehicle to vehicle communication. The first one is based on the development of an already existing approach, the Spatial Channel Model Extended (SCME) for cellular communication which is a verified, validated and well-established communication channel model. The new developed model, is called Vehicular - Spatial Channel Model Extended (V-SCME) and can be utilised for Vehicle to Vehicle communication. V-SCME is a statistical channel model which was specifically developed and configured to satisfy the requirements of the highly dynamic network topology such as vehicle to vehicle communication. V-SCME provides a precise channel coefficients library for vehicle to vehicle communication for use by the research community, so as to reduce the overall simulation time. The second approach is to apply V-BLAST (MIMO) coding which can be implemented with vehicle to vehicle communication and improve its performance over the V-SCME. The V- SCME channel model with V-BLAST coding system was used to improve vehicle to vehicle physical layer performance, which is a novel contribution. Based on analysis and simulations, it was found that the developed channel model V-SCME is a good solution to satisfy the requirements of vehicle to vehicle communication, where it has considered a lot of parameters in order to obtain more realistic results compared with the real world tests. In addition, V-BLAST (MIMO) coding with the V-SCME has shown an improvement in the bit error rate. The obtained results were intensively compared with other types of MIMO coding

    Wideband channel characterization : simulation and measurements analysis

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    The development of wireless telecommunication requires higher speed data rates. Wideband MIMO systems are a possible answer to that need. Both wideband and MIMO characteristics enhance multipath propagation, and require a precise knowledge of the channel to properly exploit their capabilities. The extraction of the channel parameters can be done from the measurements, but also from simulations. In the frame of this thesis, the possibility to use ray tracing to derive capacity coverage prediction is studied, based on the comparison with measurements. First the radio channel models are discussed, from the MIMO channel model to the ray tracing methods. Then the measurements methods and the algorithms extracting the channel parameters are presented, before focusing on a measurement campaign to compare prediction from ray tracing and measurements-based SAGE algorithm. Key parameters for capacity –delay spread and angular spread– were first compared, then capacity itself is introduced and a capacity comparison is conducted. Polarization influence on capacity is also studied, and different methods of emulating polarization on ray tracing are studied. Last but not least, the desired capacity coverage prediction is achieved on a wide area around the measurement streets. The simulation results with the ray tracing software are promising. The multipath components were predicted well enough by ray tracing to compute capacity. Then the polarization emulating methods gave interesting results: polarization influences capacity, and the derived capacity values were close enough to those computed from measurement to launch a capacity coverage calculation, first step toward a cellular planning based on MIMO capacity. However, some uncertainties are still left, due to computation time and models approximations
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