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Master Thesis Title: Improved Signal Coding Techniques for Broadband Power Line Communications
Abstract: This dissertation studies digital signal processing techniques for communications over power lines. In spite of the availability of power line communication (PLC) equipment, this technology is far from utilizing the full potential of power line networks which are more pervasive than any other wired communication alternative and should not be neglected by the engineering community. In this work, we have endeavored to fill the gap between the existing PLC technology and the ideal one which in theory is capable of exploiting the full potential of the accessible power grid for communication purposes.
Due to the presence of severe impulsive noise in power line channels, conventional signal coding techniques which are designed based on the oversimplified Gaussian noise assumption cannot be exploited in PLC systems without major modifications. Since the existing impulsive noise mitigation techniques are not capable of providing the optimal solution, there is an urgent need for novel signal processing techniques which can mitigate impulsive noise.
In this thesis, a PLC transceiver that uses multicarrier modulation in the form of orthogonal frequency-division multiplexing (OFDM) in conjunction with turbo codes is proposed. In this system, an oversampled OFDM modulator oversamples the transmit data in order to reconstruct it in the demodulator using an iterative method derived from the nonuniform sampling theorem. Simulation results confirm the robustness of the proposed system against impulsive noise.
The problem of decoding of turbo codes in impulsive symmetric α-stable (SαS) noise is also investigated in this dissertation. It is shown that the non-existence of a closed form expression for the probability density function of α-stable processes can be surmounted via numerical computation. Hence, a generalized turbo decoding algorithm is derived and it is applied to both parallel and serial iterative decoders. The results are promising in both Gaussian and impulsive SαS noise.
The Thesis is provided below:
The presentation slides at the Viva is given below:
My two other related work with their corresponding Matlab files are as follows:
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