Polar Codes for Channel and Source Coding
By Nadine Hussami, Satish Babu Korada, Rüdiger L. Urbanke. arXiv.org, 2009
570 citations recorded by the source corpus.
Subfields: Computer Networks and Communications, Electrical and Electronic Engineering
View Paper: https://www.semanticscholar.org/paper/c2eca4c1fa24b05ec94cf3cfe6a0ffd3bf555989
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Computer Networks and Communications
- Alexander Vardy
- Kai Niu
- Kai Chen
- E. Arıkan
- Ido Tal
- Hessam Mahdavifar
- Satish Babu Korada
- Rüdiger L. Urbanke
In Electrical and Electronic Engineering
- Alexander Vardy
- Hessam Mahdavifar
- Ido Tal
- Satish Babu Korada
- E. Arıkan
- Rüdiger L. Urbanke
- Kai Niu
- Kai Chen
Citations in the corpus
- Source polarization (2010, background): “We should remark that polar coding for Slepian-Wolf problem was first studied in [6], [2], and [3] under the assumptions that X, Y ∼ Ber(12 ), and X ⊕ Y ∼ Ber(p).”
- Polar codes are optimal for lossy source coding (2009, methodology): “Note th at the construction used in [16] is different from the current construction.”
- Systematic Polar Coding (2011, background): “For a representative list of papers discussing potential applications of polar coding, we cite [2], [3], [4], [5], [6], [7].”
- How to Construct Polar Codes (2011, background): “It is essentially a restatement of [13, Lemma 4.7].”
- CRC-Aided Decoding of Polar Codes (2012, background): “Belief propagation (BP) [3], [4] and linear programming (LP) [5] decoders are reported to have a significant improvement over SC.”
- Achieving the Secrecy Capacity of Wiretap Channels Using Polar Codes (2010, methodology): “It is also possibl e that other methods of decoding polar codes (such as belief propag ation [18] or recursive-list decoding [13]) may be relativel y robust to not fixing a small set X of bad channels.”