Please use this identifier to cite or link to this item: http://localhost:8081/xmlui/handle/123456789/9841
Title: "CHANNEL ESTIMATION FOR STREAM ORIENTED TURBO CODES",
Authors: Soni, Manish Kumar
Keywords: ELECTRONICS AND COMPUTER ENGINEERING;CHANNEL ESTIMATION;STREAM ORIENTED TURBO CODES;FORWARD ERROR CORRECTION
Issue Date: 2004
Abstract: "CHANNEL ESTIMATION FOR STREAM ORIENTED TURBO CODES",In order to have reliable communications, channel coding is often employed. Turbo code as a powerful coding technique has been widely studied and used in communication systems. Turbo codes are a class of forward error correction (FEC) codes that offer energy efficiency close to the limits predicted by information theory. The features of the turbo codes include parallel concatenation, recursive convolutional encoding, non uniform interleaving, and an associated iterative decoding algorithm. Although the iterative decoding algorithm has been primarily used for the decoding of turbo codes, it represents a solution to a more general class of estimation problem that can be described as follows: a data set directly or indirectly derives the state transitions of two or more Markov processes; the output of one or more of the Markov processes is observed through noise; based on the observation the original data set is estimated. Turbo codes are traditionally viewed as block codes with research focusing on block interleaver design and block decoding architectures. Though block Turbo coding can be overlayed on an indefinite stream, but in applications where messages are essentially indefinitely long strings, advantages accrue to the stream-oriented viewpoint. Because turbo codes operate at low Signal-to-Noise Ratios (SNRs), the process of phase estimation and tracking becomes difficult to perform. Additionally, the turbo decoding algorithm requires precise estimates of the channel gain and noise variance. In this dissertation, simulation of Stream Oriented Turbo Codes (SOTC) has been carried out using C++. The performance of SOTC has been evaluated using Sliding Window maximum-a-posteriori of first type (SWI-MAP) as decoding algorithm for AWGN environment. Finally performance is also evaluated for Rayleigh flat fading using pilot symbol technique and SWI-MAP is used as decoding algorithm
URI: http://hdl.handle.net/123456789/9841
Other Identifiers: M.Tech
Research Supervisor/ Guide: Varma, S. K.
metadata.dc.type: M.Tech Dessertation
Appears in Collections:MASTERS' THESES (E & C)

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