Publications

2011-07-12

Proceedings of the 13th annual conference companion on Genetic and evolutionary computation (published)

Session details: Digital entertainment technologies and arts track papers

Mike Preuss

2011-07-12

Proceedings of the 13th annual conference on Genetic and evolutionary computation (published)

Session details: Digital entertainment technologies and arts track posters

Mike Preuss

2011-07-12

Proceedings of the 13th annual conference companion on Genetic and evolutionary computation (published)

Session details: Digital entertainment technologies and arts track papers

Mike Preuss

2011-07-12

Annual Conference on Genetic and Evolutionary Computation (published)

Stochastic Multiple Stream Decoding of Cortex Codes

Matthieu Arzel

Cyril Lahuec

Christophe Jego

Yvain Bruned

Being one of the most efficient solutions to implement forward error correction (FEC) decoders based on belief propagation, stochastic proce… (see more)ssing is thus a method worthy of consideration when addressing the decoding of emerging codes such as Cortex codes. This code family offers short block codes with large Hamming distances. Unfortunately, their construction introduces many hidden variables making them difficult to be efficiently decoded with digital circuits implementing the Sum-Product algorithm. With the introduction of multiple stochastic streams, the proposed solution alleviates the hidden variables problem thus yielding decoding performances close to optimal. Morevover, this new stochastic architecture is more efficient in terms of complexity-throughput ratio compared to recently published stochastic decoders using either edge or tracking forecast memories.

2011-07-01

IEEE Transactions on Signal Processing (published)

Stochastic Multiple Stream Decoding of Cortex Codes

Matthieu Arzel

Cyril Lahuec

Christophe Jego

Yvain Bruned

Being one of the most efficient solutions to implement forward error correction (FEC) decoders based on belief propagation, stochastic proce… (see more)ssing is thus a method worthy of consideration when addressing the decoding of emerging codes such as Cortex codes. This code family offers short block codes with large Hamming distances. Unfortunately, their construction introduces many hidden variables making them difficult to be efficiently decoded with digital circuits implementing the Sum-Product algorithm. With the introduction of multiple stochastic streams, the proposed solution alleviates the hidden variables problem thus yielding decoding performances close to optimal. Morevover, this new stochastic architecture is more efficient in terms of complexity-throughput ratio compared to recently published stochastic decoders using either edge or tracking forecast memories.

2011-07-01

IEEE Transactions on Signal Processing (published)

Stochastic Decoding of Turbo Codes

Quang Trung Dong

Matthieu Arzel

Christophe Jego

Stochastic computation is a technique in which operations on probabilities are performed on random bit streams. Stochastic decoding of forwa… (see more)rd error-correction (FEC) codes is inspired by this technique. This paper extends the application of the stochastic decoding approach to the families of convolutional codes and turbo codes. It demonstrates that stochastic computation is a promising solution to improve the data throughput of turbo decoders with very simple implementations. Stochastic fully-parallel turbo decoders are shown to achieve the error correction performance of conventional a posteriori probability (APP) decoders. To our knowledge, this is the first stochastic turbo decoder which decodes a state-of-the-art turbo code. Additionally, an innovative systematic technique is proposed to cope with stochastic additions, responsible for the throughput bottleneck.

2010-12-01

IEEE Transactions on Signal Processing (published)

Stochastic Decoding of Turbo Codes

Q. Dong

Matthieu Arzel

Christophe Jego

Stochastic computation is a technique in which operations on probabilities are performed on random bit streams. Stochastic decoding of forwa… (see more)rd error-correction (FEC) codes is inspired by this technique. This paper extends the application of the stochastic decoding approach to the families of convolutional codes and turbo codes. It demonstrates that stochastic computation is a promising solution to improve the data throughput of turbo decoders with very simple implementations. Stochastic fully-parallel turbo decoders are shown to achieve the error correction performance of conventional a posteriori probability (APP) decoders. To our knowledge, this is the first stochastic turbo decoder which decodes a state-of-the-art turbo code. Additionally, an innovative systematic technique is proposed to cope with stochastic additions, responsible for the throughput bottleneck.

2010-12-01

IEEE Transactions on Signal Processing (published)

Multiscale Gossip for Efficient Decentralized Averaging in Wireless Packet Networks

Konstantinos I. Tsianos

Michael Rabbat

This paper describes and analyzes a hierarchical algorithm called Multiscale Gossip for solving the distributed average consensus problem in… (see more) wireless sensor networks. The algorithm proceeds by recursively partitioning a given network. Initially, nodes at the finest scale gossip to compute local averages. Then, using multi-hop communication and geographic routing to communicate between nodes that are not directly connected, these local averages are progressively fused up the hierarchy until the global average is computed. We show that the proposed hierarchical scheme with

2010-11-09

ArXiv (preprint)

arxiv.org

Relaxation Dynamics in Stochastic Iterative Decoders

S. Tehrani

C. Winstead

Shie Mannor

S. Howard

Vincent C. Gaudet

Stochastic decoding is a recently proposed approach for graph-based iterative error control decoding. We present and investigate three hyste… (see more)resis methods for stochastic decoding on graphs with cycles and show their close relationship with the successive relaxation method. Implementation results demonstrate the tradeoff in bit error rate performance with circuit complexity.

2010-11-01

IEEE Transactions on Signal Processing (published)

Relaxation Dynamics in Stochastic Iterative Decoders

Saeed Sharifi Tehrani

Chris Winstead

Shie Mannor

Sheryl L. Howard

Vincent C. Gaudet

Stochastic decoding is a recently proposed approach for graph-based iterative error control decoding. We present and investigate three hyste… (see more)resis methods for stochastic decoding on graphs with cycles and show their close relationship with the successive relaxation method. Implementation results demonstrate the tradeoff in bit error rate performance with circuit complexity.

2010-11-01

IEEE Transactions on Signal Processing (published)

Majority-Based Tracking Forecast Memories for Stochastic LDPC Decoding

Saeed Sharifi Tehrani

Ali Naderi

Guy-Armand Kamendje

Saied Hemati

Shie Mannor

This paper proposes majority-based tracking forecast memories (MTFMs) for area efficient high throughput ASIC implementation of stochastic L… (see more)ow-Density Parity-Check (LDPC) decoders. The proposed method is applied for ASIC implementation of a fully parallel stochastic decoder that decodes the (2048, 1723) LDPC code from the IEEE 802.3an (10GBASE-T) standard. The decoder occupies a silicon core area of 6.38 mm2 in CMOS 90 nm technology, achieves a maximum clock frequency of 500 MHz, and provides a maximum core throughput of 61.3 Gb/s. The decoder also has good decoding performance and error-floor behavior and provides a bit error rate (BER) of about 4 × 10-13 at Eb/N0=5.15 dB. To the best of our knowledge, the implemented decoder is the most area efficient fully parallel soft -decision LDPC decoder reported in the literature.

2010-09-01

IEEE Transactions on Signal Processing (published)