Laura Conde-Canencia

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—Layered decoding is known to provide efficient and high-throughput implementation of LDPC decoders. However, the implementation of the layered architecture is not always straightforward because of the memory access conflicts in the a-posteriori information memory. In this paper, we focus our attention on a particular type of conflict introduced by the(More)
—Classically, the association of high-order modulation techniques to binary channel coding suffers from significant information loss due to the computation of the channel probabilities at the bit level. In this paper, we investigate the association of Non-Binary Low-Density Parity-Check codes (NB-LDPC) and Cyclic Code-Shift Keying (CCSK) which aims at(More)
—This paper presents the architecture, performance and implementation results of a serial GF(64)-LDPC decoder based on a reduced-complexity version of the Extended Min-Sum algorithm. The main contributions of this work correspond to the variable node processing, the codeword decision and the elementary check node processing. Post-synthesis area results show(More)
Many of the current LDPC implementations of DVB-S2, T2 or WiMAX standard use the so-called layered architecture combined with pipeline. However, the pipeline process may introduce memory access conflicts. The resolution of these conflicts requires careful scheduling combined with dedicated hardware and/or idle cycle insertion. In this paper, based on the(More)
1 Abstract—Non-binary LDPC codes are now recognized as a potential competitor to binary coded solutions, especially when the codeword length is small or moderate. More and more works are reported with good performance/complexity tradeoffs, which make non-binary solutions interesting for practical applications, such as 4G-wireless systems or DVB-like(More)
This paper presents a detailed complexity study of the existing non-binary LDPC decoding algorithms in order to rigorously compare them from a hardware perspective. The Belief Propagation algorithm is first considered as well as its derivative versions in the frequency and logarithm domains. We then focus on the Extended Min-Sum and its recent simplified(More)
—Associative memories are capable of retrieving previously stored patterns given parts of them. This feature makes them good candidates for pattern detection in images. Clustered Neural Networks is a recently-introduced family of associative memories that allows a fast pattern retrieval when implemented in hardware. In this paper, we propose a new pattern(More)
Layered decoding is known to provide efficient and high-throughput implementation of LDPC decoders. However, two main issues affect performance and area of practical implementations: quantization and memory. Quantization can strongly degrade performance and memory area can constitute up to 70% of the total area of the decoder implementation. This is the(More)