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Random generation of linear codes

Aequationes mathematicae, 1999
Being of interest in the framework of the classification of discrete structures, the author applies combinatorial and algebraic methods for generating \((n,k)\) linear codes distributed uniformly at random over all isometry classes of linear codes. The main theoretical tools are the \textit{Dixon-Wilf-algorithm} (originally developed for the random ...
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Sparse Random Linear Network Coding With Precoded Band Codes

IEEE Communications Letters, 2017
This letter proposes a sparse network code based on band matrices for lossy networks. The proposed code is precoded, has no wrap-around, and allows only a limited number of bands. Compared with existing works, the code simplifies decoding, enables more flexible recoding, and is able to significantly reduce the reception overhead that might be caused by
Ye Li, Jun Zhu, Zhihua Bao
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Rank metric convolutional codes for Random Linear Network Coding

2012 International Symposium on Network Coding (NetCod), 2012
Random Linear Network Coding (RLNC) currently attracts a lot of attention as a technique to disseminate information in a network. In this contribution, non-coherent multi-shot RLNC is considered, that means, the unknown and time variant network is used several times.
Antonia Wachter-Zeh, Vladimir Sidorenko
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A New Efficient Secure Coding Scheme for Random Linear Network Coding

2013 22nd International Conference on Computer Communication and Networks (ICCCN), 2013
Random Linear Network Coding (RLNC) is a promising technology of Network coding (NC) {that is} verified to be both sufficient and efficient. In this paper, we propose an efficient implementation of coding process, ensuring the security against active and passive attacks, in order to deploy RLNC in real networks, especially on battery constrained mobile
Noura, Hassan   +2 more
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Application for the random network coding and models for random linear network coding

Proceedings of 2011 International Conference on Computer Science and Network Technology, 2011
In this paper, first we discuss some basic knowledge about the random network coding, then we introduce the random linear network coding with some simple models. Secondly, we will consider the coding over packets that randomly arrive to a source node for transmission to a single destination.
Wei Song, Mengli Li
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Random Linear Network Error Correction Coding

2014
Random linear network coding is feasible for noncoherent networks without errors, and its performance analysis is very important in theory and applications. This random method also can be applied to network error correction. That is, each node (maybe the source node) randomly and uniformly picks the local encoding coefficients from the base field for ...
Xuan Guang, Zhen Zhang
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Decoding Random Linear Codes in 0.091n

2014
Decoding random linear codes is one of the central problems in coding theory and code-based cryptography. In this paper a new algorithm for decoding random long linear codes is proposed. It has a lower decoding complexity exponent than other known algorithms for the codes with rates in a range from 0 to 0.6.
Abramov Andrey, Krouk Eugeniy
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On enhancing the random linear network coding

2011 17th IEEE International Conference on Networks, 2011
Network coding is a promising technology which allows coding of multiple packets in routers. Random linear network coding (RLNC), a distributed network coding scheme, insists each node to forward independent random linear combinations of incoming packets through its outgoing links.
MS Najeem, C. Siva Ram Murthy
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A queueing model for random linear coding

MILCOM 2007 - IEEE Military Communications Conference, 2007
In this work we consider coding over packets that randomly arrive to a source node for transmission to a single destination. We present a queueing model for a random linear coding scheme that adapts to the amount of traffic at the source node. If there is only one packet in the queue when the channel becomes free, then reliable transmission is carried ...
Brooke Shrader, Anthony Ephremides
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