Genetic Algorithms to Maximize the Relevant Mutual Information in Communication Receivers

Electronics, vol. 10, pp. 1434

Abstract

The preservation of relevant mutual information under compression is the fundamental challenge of the information bottleneck method. It has many applications in machine learning and in communications. The recent literature describes successful applications of this concept in quantized detection and channel decoding schemes. The focal idea is to build receiver algorithms intended to preserve the maximum possible amount of relevant information, despite very coarse quantization. The existent literature shows that the resulting quantized receiver algorithms can achieve performance very close to that of conventional high-precision systems. Moreover, all demanding signal processing operations get replaced with lookup operations in the considered system design. In this paper, we develop the idea of maximizing the preserved relevant information in communication receivers further by considering parametrized systems. Such systems can help overcome the need of lookup tables in cases where their huge sizes make them impractical. We propose to apply genetic algorithms which are inspired from the natural evolution of the species for the problem of parameter optimization. We exemplarily investigate receiver-sided channel output quantization and demodulation to illustrate the notable performance and the flexibility of the proposed concept.

Authors 6

1. Jan Lewandowsky corresponding

   Fraunhofer Institute for Communication, Information Processing and Ergonomics

   Affiliation as printed

   Fraunhofer Institute for Communication, Information Processing and Ergonomics, Fraunhoferstraße 20, 53343 Wachtberg, Germany

2. Sumedh Dongare

   Technische Universität Darmstadt

   Affiliation as printed

   Communications Engineering Lab, Technical University of Darmstadt, Landgraf-Georg-Straße 4, 64283 Darmstadt, Germany

3. Rocío Martín Lima

   Fraunhofer Institute for Communication, Information Processing and Ergonomics

   Affiliation as printed

   Fraunhofer Institute for Communication, Information Processing and Ergonomics, Fraunhoferstraße 20, 53343 Wachtberg, Germany

4. Marc Adrat

   Fraunhofer Institute for Communication, Information Processing and Ergonomics

   Affiliation as printed

   Fraunhofer Institute for Communication, Information Processing and Ergonomics, Fraunhoferstraße 20, 53343 Wachtberg, Germany

5. Matthias Schrammen Aachen Institute of Communication Systems

   RWTH Aachen University

   Affiliation as printed

   Institute of Communication Systems, RWTH Aachen University, Muffeter Weg 3a, 52074 Aachen, Germany

6. Peter Jax Aachen Institute of Communication Systems

   RWTH Aachen University

   Affiliation as printed

   Institute of Communication Systems, RWTH Aachen University, Muffeter Weg 3a, 52074 Aachen, Germany