The principle of Compressed Sensing (CS) allows to find the unique sparsest solution to an under-determined system of linear equations in polynomial time. This concept has also been recently applied to error correction. Similar to Reed-Solomon (RS) Codes, this approach utilizes multi-valued symbols. Also because of these multi-valued symbols, the resulting coding scheme is very sensitive to non-sparse noise, e.g., AWGN, and has only been successfully applied to channels with impulse noise.

Therefore, it is investigated in this thesis, whether a quantized CS-based error correction scheme can handle AWGN, if it is used as outer code of a system based on code concatenation.

The objectives of this thesis are the introduction of CS with a special focus on a high-dimensional interpretation, the selection of a CS-based error correction scheme suited for concatenation and the comparison with existing systems.