Alexandre Giulietti – författare

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 paved the way to optimal usage of bandwidth and energy resources by bounding the spectral efficient vs. signal to noise ratio trade-off. However, as an information theorist, Shannon explained the best that can be done but not how to do it. 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. "Turbo Codes: Desirable and Designable" introduces the basics of turbo codes in their different flavours (more specifically, parallel concatenated convolutional turbo codes and block turbo codes). Through the application of systemic design methodology that considers data transfer and storage as top priority candidates for optimization, the authors show how turbo codes can be implemented and the attractive performance results that can be achieved in throughput, latency and energy consumption.These solutions and results make turbo-codes close competitors to traditional coding scheme such as convolutional codes or algebraic codes. Finally, a real-life prototype of parallel concatenated convolutional (turbo-) codes is presented. A complete turbo codes ASIC data-flow is described together with on-board power, speed and coding gain measurements that demonstrate the effectiveness of the proposed solution.

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.