Reed-Solomon (RS) codes are a class of codes known for their good error correction capabilities.
Many decoding algorithms exist for these codes over finite fields.
In the 1980s, RS codes over the complex field were first investigated.
With the appearance of Compressed Sensing (CS), RS codes over the complex field found their new application.
Known algorithms (such as the Berlekamp-Massey and the extended Euclidean) have already been adapted to cope with the computational difficulties arising from the finite precision of floating-point number representation and noise.

The main goal of this thesis is to extend the decoding radius beyond half the minimum distance.
This is done by using built-in soft information that is obtained during the decoding process itself.
Algorithms such as Generalized Minimum Distance (GMD) and Chase-like decoding should be investigated and adapted if needed.
The performance of these decoding algorithms should be evaluated by numerical simulations.