Turbo Like Codes

PREFACE The increasing demand on high data rate and quality of service in wireless communication has to cope with limited bandwidth and energy resources. More than 50 years ago, Shannon has paved the way to optimal usage of bandwidth and energy resources by bounding the spectral efficiency vs. signal to noise ratio trade-off. However, as any information theorist, Shannon told us what is the best we can do but not how to do it [1]. In this view, turbo codes are like a dream come true: they allow approaching the theoretical Shannon capacity limit very closely. However, for the designer who wants to implement these codes, at first sight they appear to be a nightmare. We came a huge step closer in striving the theoretical limit, but see the historical axiom repeated on a different scale: we know we can achieve excellent performance with turbo codes, but not how to realize this in real devices.

Prompt Engineering, Machine Learning, OpenAI API, AI-Apps, Training Generative AI Models and Chatbots, SEO, Social Media

Learn Piping Design Engineering

AI Images and Videos: Stable Diffusion, ComfyUI, Forge WebUI, Runway, MidJourney, DALL-E, Adobe Firefly, Flux, Leonardo

Master C# programming in Visual Studio using .Net Framework. Cover all Concepts in C# with in-depth description.