Turbo Coding, Turbo Equalisation and Space-Time Coding for Transmission over Fading Channels

By Lajos Hanzo. 2002

431 citations recorded by the source corpus.

Subfields: Artificial Intelligence, Computer Networks and Communications, Electrical and Electronic Engineering

View Paper: https://www.semanticscholar.org/paper/4b74b90df775548b8a992d55a0276c2f95f53787

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Artificial Intelligence

1. Harald Haas
2. Markus Rupp
3. Sándor Imre
4. Dominic C. O'Brien
5. M. Di Renzo
6. Lajos Hanzo
7. Laszlo Gyongyosi
8. J. Urgen Schmidhuber

In Computer Networks and Communications

1. M. Di Renzo
2. Yue Xiao
3. Lajos Hanzo
4. Shaoqian Li
5. Harald Haas
6. Ping Yang
7. Markus Rupp
8. Ertugrul Basar

In Electrical and Electronic Engineering

1. M. Di Renzo
2. Lajos Hanzo
3. Yue Xiao
4. Harald Haas
5. Shaoqian Li
6. Ping Yang
7. Markus Rupp
8. Sándor Imre

Citations in the corpus

• Design Guidelines for Spatial Modulation (2015, background): “On the other hand, the SD [93], [94], which is widely used in spatial multiplexing systems, avoids the exhaustive search of the potentially excessive-complexity signal constellation by examining only those candidate solutions that lie inside an SNR-dependent decoding sphere.”
• Wireless Myths, Realities, and Futures: From 3G/4G to Optical and Quantum Wireless (2012, background): “Owing to space limitations, we are unable to repeat all the relevant details here; suffice to say that among others, forward error correction (FEC) coding played a pivotal role in this process [15]–[20].”