Joint source channel coding using complex number DFT block codes
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The rapid growth in communication systems brought an increasing requirement for efficient and robust error control coding. The main aim of this thesis is to first review some of the available coding and decoding procedures for complex number DFT block codes and then, in a second step, make necessary modifications to improve the efficiency and error correction capability. A new technique that is designed to achieve better bandwidth efficiency by reducing redundancy along with maintaining the error correction capability is also proposed and investigated in this thesis. The error control coding on complex numbers is investigated, which can effectively represent most signals and lend themselves to better implementation of joint source channel coding when compared to error correction codes using finite fields. The coding and decoding procedures proposed by Redinbo are studied and implemented. The design of error control codes is studied by considering a complex valued channel model called the Gaussian – Bernoulli Gaussian (GBG) channel model. Various decoding algorithms such as Peterson–Gorenstein–Zierler (PGZ) decoder for detecting error locations and values, Bayes hypothesis tester for locating error positions and a Wiener estimator for estimating error values are studied. These methods are compared for their error correction capability (symbol error rates) with extensive simulations and analysis, and a suitable modification to the decoder is proposed, analyzed, and verified for its superior performance when compared to the other studied decoding algorithms. A new bandwidth efficient technique called “Masking technique” is developed and compared with the existing algorithms for its performance.