Channel equalization in radio-over-fiber transmission links

This project is about the channel equalization in radio over ber transmission links. In particular, we focus on minimizing the effect of additive white Gaussian noise and the dispersion caused by transmission. To solve the problem of channel equalization, filters such as Finite Impulse Response (FIR) or Infinite Impulse Response (IIR), have already been investigated deep enough, thus, our project will be taken from another point of view. The goal of this project is to achieve signal equalzation in the receiver decision module, increasing the performance of the Bit Error Rate curves in digital formats. In order to do that, we will use artificial intelligence algorithms. This document is divided into four chapters. First of all, an introduction to the theoretical background used in this project will be described. Then, we will define the problem, and possible solutions. Once a solution is chosen, we will start discussing the implementation, in order to justify the results obtained in the computer simulations. Our systems under study uses digital modulations theory. In concrete, we will be focusing on Phase-shift keying modulations, since it is going to be the base for our project. The channel is one of the most important bulding blocks on our scheme, because it generates the signal distorsions that we want to mitigate. Thus, ber channels model will be reviewed in order to extract the features that will produce the noise and how it influences the transmitted signal. This noise can be classified as additive white Gaussian noise (AWGN) and the dispersion. Our proposed and studied solution is based on artificial intelligence (AI) algorithms in the decider module of the receiver: Expectation Maximization (EM) and Hidden Markov Models (HMM). These two algortihms learn from the channel behaviour in the system and adapt the decision boundaries to make more correct decisons. We performed computer simulations of our proposed solution, and the results proved an important improvement over the current systems. Our proposed approach is not only capable of signi cantly reducing the BER of the system, but it is also able of correcting other phenomena's such constellation phase rotation or changes in the distribution of the received symbols in the constellation.Ingeniería Técnica en Sistemas de Telecomunicació