A STUDY OF LOW DENSITY PARITY CHECK CODES

Abstract

Digital Communication systems and digital storage systems are similar from the perspective of extracting the original information bits from the received signal. In case of any communication system, the main goal is to retrieve the original information as accurately as possible in the presence of impairments such as noise and intersymbol interference (ISI). One method to improve the accuracy of the retrieved digital information is to use error correcting codes. Coding for error correction is one of the many tools available for achieving reliable data transmission in communication systems. Recently, significant progress has been made in designing error control codes and iterative decoding to closely approach the Shannon limit. Low density parity check (LDPC) codes are one of the many error correcting codes available for error correction. Iterative decoding of LDPC will approach the Shannon limit to within 0.0045 dB. The Sum-Product Algorithm (SPA) is an iterative decoding algorithm based on belief propagation that is extremely efficient for decoding of LDPC codes. In this dissertation the Sum-product algorithm is implemented for the LDPC coded system. The LDPC code is generated by using two methods ' namely Gallger's general method and another based on RS code with two information symbols over the Galois field GF (q), where q = 2"' . The performance of the sum-product algorithm is simulated for different information sequence lengths of LDPC code and for different number of decoding iterations.