Complexity Efficient Decoder Design for Vehicular Communication

Vehicular communication is currently seen as a key technology for enabling safer and more comfortable driving. In the general effort to reduce the number of casualties and improve the traffic flow despite an increasing number of vehicles, this field has a promising future. IEEE 802.11p has been chosen as the standard for the Physical Layer (PHY) design for wireless vehicular communication. However, the channels encountered in such situations pose several challenges for reliable communications. Time and frequency selectivity caused by dispersive environments and high mobility lead to doubly-selective channels. The systems are expected to conduct proper operation, in spite of these disturbances. In this thesis, we focus on the design of receivers working on the PHY layer, with an emphasis on limited complexity. This poses high constraints on the algorithms, which already have to cope with the limited amount of information provided by the training sequences. The solutions considered all involve joint channel estimation and decoding, characterized by the use of an iterative structure. Such structures allow the channel estimation to benefit from the knowledge brought by the decoder, which ultimately decreases the error rate. Following a previous work, we use algorithms based on Minimum Mean Square Error (MMSE) or Maximum A Posteriori (MAP) estimation. These receivers were modified to operate on full frames instead of individual subcarriers, and various improvements were studied. We provide a detailed analysis of the complexity of the proposed designs, along with an evaluation of their decoding performance. The trade-offs between these two parameters are also discussed. A part of these analyses isused in [10]. Finally, we give an insight into some considerations which may arise when implementing the algorithms on testbeds