Motivation:
Compressed Sensing is an emerging technique to acquire sparse signal given a small number of measurements of the desired signal. In communication field, the signals for reconstruction always suffer from noise, which plays a vital role to determine the sufficient number of measurements needed for reconstruction.

Goal:
This work aims to investigate error bounds performance on Compressed Sensing of noisy signals and enable the analysis of performance limits of specific recovery algorithms with the help of well-known techniques in communication field (e.g. Information Theory). 

Requirements:
The lecture Channel Coding I/II and knowledge of MATLAB programming are required.