FPGA Impementation of Erasure-Only Reed Solomon Decoders for Hybrid-ARQ Systems
March 30, 2016 Β· Declared Dead Β· π Signal Processing and Communications Applications Conference
"No code URL or promise found in abstract"
Evidence collected by the PWNC Scanner
Authors
Cansu Sen, Soner Yesil, Ertugrul Kolagasioglu
arXiv ID
1603.09062
Category
cs.AR: Hardware Architecture
Cross-listed
cs.IT
Citations
0
Venue
Signal Processing and Communications Applications Conference
Last Checked
3 months ago
Abstract
This paper presents the usage of the Reed Solomon Codes as the Forward Error Correction (FEC) unit of the Hybrid Automatic Repeat Request (ARQ) methods. Parametric and flexible FPGA implementation details of such Erasure-Only RS decoders with high symbol lengths (e.g. GF(2^32)) have been presented. The design is based on the GF(2m) multiplier logic core operating at a single clock cycle, where the resource utilization and throughput are both directly proportional to the number of these cores. For a fixed implementation, the throughput inversely decreases with the number of erasures to be corrected. Implementation in Zynq7020 SoC device of an example GF(2^32)-RS Decoder capable of correcting 64-erasures with a single multiplier resulted in 1641-LUTs and 188-FFs achieving 15Mbps, whereas the design with 8 multipliers resulted in 6128-LUTs and 628-FFs achieving 100Mbps.
Community Contributions
Found the code? Know the venue? Think something is wrong? Let us know!
π Similar Papers
In the same crypt β Hardware Architecture
R.I.P.
π»
Ghosted
R.I.P.
π»
Ghosted
Corona: System Implications of Emerging Nanophotonic Technology
R.I.P.
π»
Ghosted
A scalable multi-core architecture with heterogeneous memory structures for Dynamic Neuromorphic Asynchronous Processors (DYNAPs)
R.I.P.
π»
Ghosted
SpAtten: Efficient Sparse Attention Architecture with Cascade Token and Head Pruning
R.I.P.
π»
Ghosted
Neural Cache: Bit-Serial In-Cache Acceleration of Deep Neural Networks
R.I.P.
π»
Ghosted
SpArch: Efficient Architecture for Sparse Matrix Multiplication
Died the same way β π» Ghosted
R.I.P.
π»
Ghosted
Federated Learning: Strategies for Improving Communication Efficiency
R.I.P.
π»
Ghosted
Deep Convolutional Neural Networks for Computer-Aided Detection: CNN Architectures, Dataset Characteristics and Transfer Learning
R.I.P.
π»
Ghosted
Explanation in Artificial Intelligence: Insights from the Social Sciences
R.I.P.
π»
Ghosted