| Popis: |
As the mobility of people increases, so does the density of vehicles on road networks. This comes at a cost, causing traffic congestions and raising the number of casualties. Wire- less communications between vehicles will enable the development of Intelligent Transport Systems (ITS), which are expected to assist and manage road transportation. The aim of ITS is to enhance safety, road network management, but also personal comfort for drivers and passengers. IEEE 802.11p has been chosen as the standard for the Physi- cal Layer (PHY) design for wireless vehicular communications. Unfortunately, vehicular channels are challenging for communications. While the dispersive nature of the channel has advantages, such as the possibility to communicate in the absence of line-of-sight, time variations present in high mobility scenarios lead to doubly selective channels. The systems are expected to allow reliable communications despite those conditions. In this thesis we focus on PHY design for the receiver. We aim at implementing receivers able to perform channel estimation in the case of doubly selective channels, with minimal information from training sequences. The solutions considered all involve joint channel estimation and decoding, characterized by the use of an iterative structure. As limited knowledge of the channel is available at the receiver, only a coarse estimate can be performed in the first place. Iterative structures allow the channel estimator to benefit from feedback produced by the decoder, used to refine the channel estimation and ultimately resulting in a smaller error rate. Different algorithms are considered, either based on Minimum Mean Square Estimation (MMSE), or Maximum A Posteriori (MAP) estimation. The latter requires a recursive description of the channel introduced as a Markov chain. Using these powerful methods to perform channel estimation, we decrease the error rate, despite the varying nature of the channel. However, improving the channel estimation comes at the cost of a higher complexity. An analysis on the trade-off between performance and complexity is also provided. |
