Convolutional Encoder/Decoder of Rate 1/N Codes 1.0

In this project, we seek to minimize the gap-to-capacity (given by Shannond-deOaos theoretical limit) of a rate 1/3 code (also can be modified for 1/N). This is done via a convolutional encoder/decoder for varying memory elements as well for both soft and hard decoding scheme. We show that the gap-to-capacity can be minimized with respect to the suboptimal un-coded code word or a (3,1) repetition code. Although better schemes are available such as LDPC and turbo codes, we have chosen the convolutional code for its simplicity and generality. Our model of transmission is binary-input AWGN channel. Also, I attached my paper to demonstrate how the code can be easily modified for other rates and different varying element sizes. Provides detail overview of Convolution Coding scheme.For More Information: http://www.romeilsandhu.com

Requirements:	No special requirements
Platforms:	Matlab
Keyword:	Attached,  Binaryinput,  Channel,  Chosen,  Coding,  Convolution,  Demonstrate,  Detail,  Easily,  Generality,  Information,  Model,  Overview,  Paper,  Rates,  Schemefor,  Simplicity,  Transmission
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