Análise de desempenho de códigos LDPC em sistemas de comunicações ópticas coerentes

• Autor(a) principal: Gonçalves, Jéssica Oliveira
• Data de Publicação: 2021
• Tipo de documento: Trabalho de conclusão de curso
• Idioma: por
• Título da fonte: Repositório Institucional da UNESP
• Texto Completo: http://hdl.handle.net/11449/214055
• topic: Códigos corretores de erros (Teoria da informação); Comunicações ópticas; Telecomunicações; Teoria da codificação

Channel encoding consists of the insertion of redundant bits in the information to be sent, in order to protect the information, allowing the receiver to recover it without the need for retransmission. This technique was introduced by Shannon in 1948 and since then it has been widely studied and several channel coding strategies have been presented. In the last decades, the technique known as foward error correction (FEC) based on low density verification codes (LDPC) has been widely used in several areas, but has shown to be very promising in applications related to coherent optical communications systems, due to their efficiency in long-range transmissions, as well as in transmissions with a high information rate. This work has as main objective to explore the theory and techniques for obtaining efficient LDPC codes, applying a coding technique from its parity control matrix obtained through a method known as balanced incomplete block design (BIBD) and an iterative decoding using a soft-decision algorithm called the sum-product algorithm (SPA). Computational simulations will be performed using the Python programming language in order to verify the performance of LDPC codes in an optical communication channel. This channel was modeled from a Gaussian channel, where using certain criteria it could be approximated to a channel with additive noise gaussian and white (AWGN). The results show the possibility of using a method of obtaining the parity check matrix different from the traditional one proposed by Gallager, in addition to demonstrating the direct link between the increase in performance and the number of iterations in the SPA decoding algorithm and allowing to measure the coding gain in relation to SNR, which in the best simulated scenario was 4.91 dB.