Research Of Blind Channel Estimation And Equalization Based On Correlations In Vehicular Ad-hoc Networks

Inter-Symbol Interference (ISI) is always one of the main factors affecting the quality of high speed data transmission in wireless communication field. In order to reduce the signal distortion aroused by ISI, channel equalization is always used in the communication systems. In order to overcome the influence of ISI, traditional equalization algorithm needs to send a training sequence, which is not necessary in blind equalization. This thesis studies the algorithm of blind channel estimation and equalization based on correlations in vehicular Ad-hoc networks.This thesis consists of five chapters. An overview of the significance and the development of blind channel estimation and equalization, and the major works of this thesis are introduced in Chapter 1. In Chapter 2, we introduce the basic concept and structure of blind equalizer, the performance analysis of blind equalization algorithm. In chapter 3, the basic knowledge based on correlations in vehicular Ad-hoc networks is introduced. Then the model of signal and system based on cross-correlations are described. Meantime, we also demonstrate that signals of adjacent vehicles can be highly cross-correlated in densely vehicular Ad-hoc networks. In chapter 4, in V2V networks, this thesis utilizes such a property to develop efficient blind channel identification and equalization algorithms. And to propose an adaptive algorithm with a low complexity, a low complexity adaptive algorithm is also introduced on the basis of this. In chapter 5, in V2V networks, to enhance the robustness of the system, it also utilize such a property to propose a minimum-output-energy optimization algorithm with the equality and inequality constraints. The simulation results show that the robust algorithm can not only improve the convergence speed, but also reduce steady residual error and bit error rate.