Subscribe to the gold package and get unlimited access to Shamra Academy
Register a new userLinearly-Coupled Fountain Codes
175
0
0.0
(
0
)
Added by
Shenghao Yang
Publication date
2014
fields
Informatics Engineering
and research's language is
English
Ask ChatGPT about the research
No Arabic abstract
Network-coded multiple access (NCMA) is a communication scheme for wireless multiple-access networks where physical-layer network coding (PNC) is employed. In NCMA, a user encodes and spreads its message into multiple packets. Time is slotted and multiple users transmit packets (one packet each) simultaneously in each timeslot. A sink node aims to decode the messages of all the users from the sequence of receptions over successive timeslots. For each timeslot, the NCMA receiver recovers multiple linear combinations of the packets transmitted in that timeslot, forming a system of linear equations. Different systems of linear equations are recovered in different timeslots. A message decoder then recovers the original messages of all the users by jointly solving multiple systems of linear equations obtained over different timeslots. We propose a low-complexity digital fountain approach for this coding problem, where each source node encodes its message into a sequence of packets using a fountain code. The aforementioned systems of linear equations recovered by the NCMA receiver effectively couple these fountain codes together. We refer to the coupling of the fountain codes as a linearly-coupled (LC) fountain code. The ordinary belief propagation (BP) decoding algorithm for conventional fountain codes is not optimal for LC fountain codes. We propose a batched BP decoding algorithm and analyze the convergence of the algorithm for general LC fountain codes. We demonstrate how to optimize the degree distributions and show by numerical results that the achievable rate region is nearly optimal. Our approach significantly reduces the decoding complexity compared with the previous NCMA schemes based on Reed-Solomon codes and random linear codes, and hence has the potential to increase throughput and decrease delay in computation-limited NCMA systems.
rate research
Read More
We introduce a new family of Fountain codes that are systematic and also have sparse parities. Given an input of $k$ symbols, our codes produce an unbounded number of output symbols, generating each parity independently by linearly combining a logarithmic number of randomly selected input symbols. The construction guarantees that for any $epsilon>0$ accessing a random subset of $(1+epsilon)k$ encoded symbols, asymptotically suffices to recover the $k$ input symbols with high probability. Our codes have the additional benefit of logarithmic locality: a single lost symbol can be repaired by accessing a subset of $O(log k)$ of the remaining encoded symbols. This is a desired property for distributed storage systems where symbols are spread over a network of storage nodes. Beyond recovery upon loss, local reconstruction provides an efficient alternative for reading symbols that cannot be accessed directly. In our code, a logarithmic number of disjoint local groups is associated with each systematic symbol, allowing multiple parallel reads. Our main mathematical contribution involves analyzing the rank of sparse random matrices with specific structure over finite fields. We rely on establishing that a new family of sparse random bipartite graphs have perfect matchings with high probability.
Linear nested codes, where two or more sub-codes are nested in a global code, have been proposed as candidates for reliable multi-terminal communication. In this paper, we consider nested array-based spatially coupled low-density parity-check (SC-LDPC) codes and propose a line-counting based optimization scheme for minimizing the number of dominant absorbing sets in order to improve its performance in the high signal-to-noise ratio regime. Since the parity-check matrices of different nested sub-codes partially overlap, the optimization of one nested sub-code imposes constraints on the optimization of the other sub-codes. To tackle these constraints, a multi-step optimization process is applied first to one of the nested codes, then sequential optimization of the remaining nested codes is carried out based on the constraints imposed by the previously optimized sub-codes. Results show that the order of optimization has a significant impact on the number of dominant absorbing sets in the Tanner graph of the code, resulting in a tradeoff between the performance of a nested code structure and its optimization sequence: the code which is optimized without constraints has fewer harmful structures than the code which is optimized with constraints. We also show that for certain code parameters, dominant absorbing sets in the Tanner graphs of all nested codes are completely removed using our proposed optimization strategy.
Partially information coupled turbo codes (PIC-TCs) is a class of spatially coupled turbo codes that can approach the BEC capacity while keeping the encoding and decoding architectures of the underlying component codes unchanged. However, PIC-TCs have significant rate loss compared to its component rate-1/3 turbo code, and the rate loss increases with the coupling ratio. To absorb the rate loss, in this paper, we propose the partially information coupled duo-binary turbo codes (PIC-dTCs). Given a rate-1/3 turbo code as the benchmark, we construct a duo-binary turbo code by introducing one extra input to the benchmark code. Then, parts of the information sequence from the original input are coupled to the extra input of the succeeding code blocks. By looking into the graph model of PIC-dTC ensembles, we derive the exact density evolution equations of the PIC-dTC ensembles, and compute their belief propagation decoding thresholds on the binary erasure channel. Simulation results verify the correctness of our theoretical analysis, and also show significant error performance improvement over the uncoupled rate-1/3 turbo codes and existing designs of spatially coupled turbo codes.
A new type of spatially coupled low-density parity-check (SC-LDPC) codes motivated by practical storage applications is presented. SC-LDPCL codes (suffix L stands for locality) can be decoded locally at the level of sub-blocks that are much smaller than the full code block, thus offering flexible access to the coded information alongside the strong reliability of the global full-block decoding. Toward that, we propose constructions of SC-LDPCL codes that allow controlling the trade-off between local and global correction performance. In addition to local and global decoding, the paper develops a density-evolution analysis for a decoding mode we call semi-global decoding, in which the decoder has access to the requested sub-block plus a prescribed number of sub-blocks around it. SC-LDPCL codes are also studied under a channel model with variability across sub-blocks, for which decoding-performance lower bounds are derived.
Spatially-coupled (SC) LDPC codes have recently emerged as an excellent choice for error correction in modern data storage and communication systems due to their outstanding performance. It has long been known that irregular graph codes offer performance advantage over their regular counterparts. In this paper, we present a novel combinatorial framework for designing finite-length irregular SC LDPC codes. Our irregular SC codes have the desirable properties of regular SC codes thanks to their structure while offering significant performance benefits that come with the node degree irregularity. Coding constructions proposed in this work contribute to the existing portfolio of finite-length graph code designs.
Log in to be able to interact and post comments
comments
Fetching comments
Sign in to be able to follow your search criteria
