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Low-Density Codes Based on Chaotic Systems for Low-Density Codes Based on Chaotic Systems for Simple Encoding

Publications associées (75)

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Distributed sensor failure detection in sensor networks

Pascal Frossard, Nikolaos Thomos, Tamara Tosic

We investigate the problem of distributed sensors' failure detection in networks with a small number of defective sensors, whose measurements differ significantly from neighbouring sensor measurements. We build on the sparse nature of the binary sensor fai ...

Elsevier Science Bv2013

Extended Polar Codes Perform Better in Terms of Compound Rate and Scaling Behavior

Seyed Hamed Hassani

Polar codes provably achieve the capacity of a wide array of channels under successive decoding. However, in terms of some practical aspects, these codes do not perform optimally and need further improvement. In this paper, we consider two such aspects: un ...

Ieee2013

Polar Codes: Finite Length Implementation, Error Correlations and Multilevel Modulation

Shannon, in his seminal work, formalized the transmission of data over a communication channel and determined its fundamental limits. He characterized the relation between communication rate and error probability and showed that as long as the communicatio ...

2012

Compute-and-Forward: Harnessing Interference Through Structured Codes

Michael Christoph Gastpar

Abstract—Interference is usually viewed as an obstacle to communication in wireless networks. This paper proposes a new strategy, compute-and-forward, that exploits interference to obtain significantly higher rates between users in a network. The key idea ...

Institute of Electrical and Electronics Engineers2011

Exchange of Limits: Why Iterative Decoding Works

Rüdiger Urbanke, Satish Babu Korada

We consider communication over binary-input memoryless output-symmetric channels using low-density parity-check codes and message-passing decoding. The asymptotic (in the length) performance of such a combination for a fixed number of iterations is given b ...

2011

Exchange of Limits: Why Iterative Decoding Works

Rüdiger Urbanke, Satish Babu Korada

Institute of Electrical and Electronics Engineers2011

Symbol-Pair Codes: Algebraic Constructions and Asymptotic Bounds

Yuval Cassuto

For the recently proposed model of symbol-pair channels, we advance the pair-error coding theory with algebraic cyclic-code constructions and asymptotic bounds on code rates. Cyclic codes for pair-errors are constructed by a careful use of duals of known t ...

Ieee Service Center, 445 Hoes Lane, Po Box 1331, Piscataway, Nj 08855-1331 Usa2011

A 15.8 pJ/bit/iter quasi-cyclic LDPC decoder for IEEE 802.11n in 90 nm CMOS

Andreas Peter Burg, Pascal Andreas Meinerzhagen, Christoph Studer

We present a low-power quasi-cyclic (QC) low density parity check (LDPC) decoder that meets the throughput requirements of the highest-rate (600 Mbps) modes of the IEEE 802.11n WLAN standard. The design is based on the layered offset-min-sum algorithm and ...

IEEE2010

Not Just for Errors: Codes for Fast and Secure Flash Storage

Yuval Cassuto

Error-correcting codes are normally employed in storage devices to guarantee the integrity of data in the presence of errors. This paper presents two schemes where error-correcting codes are used for entirely different purposes. In the first part of the pa ...

Ieee Service Center, 445 Hoes Lane, Po Box 1331, Piscataway, Nj 08855-1331 Usa2010

Polar codes for channel and source coding

Satish Babu Korada

The two central topics of information theory are the compression and the transmission of data. Shannon, in his seminal work, formalized both these problems and determined their fundamental limits. Since then the main goal of coding theory has been to find ...

EPFL2009