30 research outputs found
Erasure Codes with a Banded Structure for Hybrid Iterative-ML Decoding
This paper presents new FEC codes for the erasure channel, LDPC-Band, that
have been designed so as to optimize a hybrid iterative-Maximum Likelihood (ML)
decoding. Indeed, these codes feature simultaneously a sparse parity check
matrix, which allows an efficient use of iterative LDPC decoding, and a
generator matrix with a band structure, which allows fast ML decoding on the
erasure channel. The combination of these two decoding algorithms leads to
erasure codes achieving a very good trade-off between complexity and erasure
correction capability.Comment: 5 page
Analysis of Quasi-Cyclic LDPC codes under ML decoding over the erasure channel
In this paper, we show that Quasi-Cyclic LDPC codes can efficiently
accommodate the hybrid iterative/ML decoding over the binary erasure channel.
We demonstrate that the quasi-cyclic structure of the parity-check matrix can
be advantageously used in order to significantly reduce the complexity of the
ML decoding. This is achieved by a simple row/column permutation that
transforms a QC matrix into a pseudo-band form. Based on this approach, we
propose a class of QC-LDPC codes with almost ideal error correction performance
under the ML decoding, while the required number of row/symbol operations
scales as , where is the number of source symbols.Comment: 6 pages, ISITA1
A Decoding Algorithm for LDPC Codes Over Erasure Channels with Sporadic Errors
none4An efficient decoding algorithm for low-density parity-check (LDPC) codes on erasure channels with sporadic errors (i.e., binary error-and-erasure channels with error probability much smaller than the erasure probability) is proposed and its performance analyzed. A general single-error multiple-erasure (SEME) decoding algorithm is first described, which may be in principle used with any binary linear block code. The algorithm is optimum whenever the non-erased part of the received word is affected by at most one error, and is capable of performing error detection of multiple errors. An upper bound on the average block error probability under SEME decoding is derived for the linear random code ensemble. The bound is tight and easy to implement. The algorithm is then adapted to LDPC codes, resulting in a simple modification to a previously proposed efficient maximum likelihood LDPC erasure decoder which exploits the parity-check matrix sparseness. Numerical results reveal that LDPC codes under efficient SEME decoding can closely approach the average performance of random codes.noneG. Liva; E. Paolini; B. Matuz; M. ChianiG. Liva; E. Paolini; B. Matuz; M. Chian
Memory and Complexity Analysis of On-the-Fly Coding Schemes for Multimedia Multicast Communications
A new class of erasure codes for delay-constraint applications, called on-the-fly coding, have recently been introduced for their improvements in terms of recovery delay and achievable capacity. Despite their promising characteristics, little is known about the complexity of the systematic and non-systematic variants of this code, notably for live multicast transmission of multimedia content which is their ideal use case. Our paper aims to fill this gap and targets specifically the metrics relevant to mobile receivers with limited resources: buffer size requirements and computation complexity of the receiver. As our contribution, we evaluate both code variants on uniform and bursty erasure channels. Results obtained are unequivocal and demonstrate that the systematic codes outperform the nonsystematic ones, in terms of both the buffer occupancy and computation overhead
Band Codes for Energy-Efficient Network Coding with Application to P2P Mobile Streaming
A key problem in random network coding (NC) lies in the complexity and energy
consumption associated with the packet decoding processes, which hinder its
application in mobile environments. Controlling and hence limiting such factors
has always been an important but elusive research goal, since the packet degree
distribution, which is the main factor driving the complexity, is altered in a
non-deterministic way by the random recombinations at the network nodes. In
this paper we tackle this problem proposing Band Codes (BC), a novel class of
network codes specifically designed to preserve the packet degree distribution
during packet encoding, ecombination and decoding. BC are random codes over
GF(2) that exhibit low decoding complexity, feature limited and controlled
degree distribution by construction, and hence allow to effectively apply NC
even in energy-constrained scenarios. In particular, in this paper we motivate
and describe our new design and provide a thorough analysis of its performance.
We provide numerical simulations of the performance of BC in order to validate
the analysis and assess the overhead of BC with respect to a onventional NC
scheme. Moreover, peer-to-peer media streaming experiments with a random-push
protocol show that BC reduce the decoding complexity by a factor of two, to a
point where NC-based mobile streaming to mobile devices becomes practically
feasible.Comment: To be published in IEEE Transacions on Multimedi
Analysis of Quasi-Cyclic LDPC codes under ML decoding over the erasure channel
International audienceIn this paper, we show that over the binary erasure channel, Quasi-Cyclic LDPC codes can efficiently accommodate the hybrid iterative/ML decoding. We demonstrate that the quasi- cyclic structure of the parity-check matrix can be advantageously used in order to significantly reduce the complexity of the ML decoding. This is achieved by a simple row/column permutation that transforms a QC matrix into a pseudo-band form. Based on this approach, we propose a class of QC-LDPC codes with almost ideal error correction performance under the ML decoding, while the required number of row/symbol operations scales as k √k, where k is the number of source symbols
The deep space network
Progress is reported in flight project support, tracking and data acquisition research and technology, network engineering, hardware and software implementation, and operations. The functions and facilities of the Deep Space Network are emphasized