Signal Processing for 5G: Algorithms and Implementations

Chapter 2Faster-than-Nyquist Signaling for 5G Communication

John B. Anderson

1. 2.1 Introduction to FTN Signaling
   1. 2.1.1 Definition of FTN: FTN from Detection Theory
   2. 2.1.2 The Shannon Limit for FTN
   3. 2.1.3 Summary
2. 2.2 Time FTN: Receivers and Performance
   1. 2.2.1 The BCJR Algorithm and Iterative Decoding
   2. 2.2.2 Binary Coded FTN Performance
   3. 2.2.3 Four-level Coded FTN
   4. 2.2.4 Summary
3. 2.3 Frequency FTN Signaling
   1. 2.3.1 Definition of Frequency FTN
   2. 2.3.2 Implementation of Frequency FTN
   3. 2.3.3 Summary
4. 2.4 Summary of the Chapter
5. References

Fifth-generation wireless systems will transmit many more bits than their predecessors in each Hertz, second and square meter of real estate. Many ways to do this are explored in this book, and the focus of this chapter is on more efficient modulation and coding of the signals. One wants more bits per Hertz and second at a given error performance. Fortuituously, the innovations in 5G also raise the signal-to-noise ratio (SNR) by means of smaller cells, MIMO and WiFi-like local methods. This higher SNR is a key to more bits. Proper coding and modulation can raise the number further, but until now rather few coding methods make good use of higher SNRs. The subject of this chapter is faster-than-Nyquist (FTN) signaling, a leading such method that can potentially double data transmission rates. In addition, it sheds new light on notions of bandwidth, Shannon capacity and complexity that underlie data transmission. FTN is not new, but it is only recently that its implications ...