Fast Simulation and Prototyping with AFF3CT

Abstract

This demonstration intends to present AFF3CT (A Fast Forward 3rror Correction Tool). The main objective of AFF3CT is to provide a portable, open source, fast and flexible software to the channel coding community in such a way that researchers can spend more time on channel coding / algorithmic problems instead of software development issues. It is also intended to facilitate the process of hardware verification and debug with the objective of fast prototyping. I. SIMULATION OF A DIGITAL COMMUNICATION CHAIN Despite the wide variety of existing communication systems , all of them are based on a common abstract model that was proposed by the genius founder of information theory, Claude Shannon [1]. Figure 1 shows the synoptic of such a communication chain. In this structure, the channel encoder and decoder determine the achievable error rate of the system. Moreover, the channel decoder is a large contributor in the overall computational complexity of the system. On the eve of the 5th generation of mobile communication systems, one of the challenges is to imagine systems able to transmit a huge amount of data in a very short amount of time at a very small energy cost in a wide variety of environments. In such a context, researchers work at refining some existing coding schemes (encoder + decoder) in such a way that the system has a low residual error rate and that the associated decoder is fast, flexible and has a low complexity. The validation of a new coding scheme requires the estimation of the error rate performance. Unfortunately, most of the time, no simple mathematical model exists to predict the performance of a channel encoder/decoder. The only simple solution is to perform a Monte Carlo simulation of the whole communication chain: some data are pseudo-randomly generated, encoded, modulated, noised, decoded and the performance is estimated by measuring the Bit Error Rate (BER) and the Frame Error Rate (FER) at the receiver side. This apparently simple setup leads to three main problems. Reproducibility: It is usually a tedious task to reproduce the results from the literature. This can be explained by the large amount of empirical parameters necessary to define one communication system and not all of them are reported in the publications. Moreover, it is rare that researchers actually share the source code of their simulator. As a consequence, a large amount of time is spent ‘reinventing the wheel’ only to be able to compare to the state-of-the-art results.

Publication
The 20th International Workshop on Signal Processing Systems (SiPS 2017)