| Περίληψη: | Being the key factor for development as a society, electronic communications have increasingly became more and more the center of our day to day life. Consequently,methods and techniques that ensure reliable, safe and fast transmission of information are becoming more and more essential. Digital Signal Processing, In formation Theory and Error Correction Codes are the research areas that study how to achieve such a goal. Many error correction codes have been presented in the past but in recent years a class of codes has imposed itself as the best candidate to solve the problem, Low Density Parity Check (LDPC) Codes. LDPC codes are a class of codes that can achieve reliable communication while keeping the complexity of the encoder and decoder implementation controllable. The performances of LDPC codes have been shown to be very close to the theoretical limit that a code can reach in a given channel, the channel capacity. However, implementation of LDPC codes of very good performance and at the same time, very low complexity, remains a challenge.There is always a need for smaller and faster communication devices with low power consumption and low cost, as a consequence, error correction modules must be improved to meet these specifications covering at the same time all required functionalities.This thesis investigates various aspects of LDPC code construction/implementation that can improve their performance and decrease their hardware implementation requirements.The main focus of the thesis is on code construction and encoder hardware implementation where either by adopting known code construction methods or by modifying them, known encoding algorithms or by modifying them, and by proposing new construction techniques, we always jointly consider the error-corrective capability of the constructed code and their complexity; since when real systems are designed,the choice of the code used cannot be based exclusively on the coding performances but also hardware requirements must be considered. Hence, it is important to develop codes that are capable of good performances without making the encoding and decoding processes intractable from an implementation point of view.
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