By Tracey Ho

ISBN-10: 0511396759

ISBN-13: 9780511396755

ISBN-10: 052187310X

ISBN-13: 9780521873109

Community coding delivers to noticeably impression the best way communications networks are designed, operated, and understood. This booklet offers a unified and intuitive evaluate of the idea, purposes, demanding situations, and destiny instructions of this rising box, and is a must have source for these operating in wireline or instant networking. • makes use of an engineering method - explains the guidelines and functional thoughts • Covers mathematical underpinnings, sensible algorithms, code choice, defense, and community administration • Discusses key subject matters of inter-session (non-multicast) community coding, lossy networks, lossless networks, and subgraph-selection algorithms beginning with uncomplicated ideas, types, and concept, then overlaying a middle subset of effects with complete proofs, Ho and Lun offer an authoritative advent to community coding that offers either the history to aid study and the sensible issues for designing coded networks. this can be an important source for graduate scholars and researchers in digital and machine engineering and for practitioners within the communications undefined.

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**Additional info for Network Coding: An Introduction**

**Sample text**

The algebraic convolutional network coding approach presented in this chapter is from Koetter and M´edard [82]. Various aspects of convolutional network coding, including constructive coding and decoding techniques, are addressed in Erez and Feder [38, 39], Fragouli and Soljanin [43], and Li and Yeung [84]. The linear network coding approach for correlated sources is an extension by Ho et al. [61] of the linear coding approach in Csisz´ar [29] for the Slepian–Wolf problem. Separation of source coding and network coding is addressed in [112].

The source bits at X i are grouped into vectors of ri bits which we refer to as symbols. ) manner from the same joint distribution Q. We employ a vector linear network code that operates on blocks of bits corresponding to n symbols from each source. ‡ Let ck be the capacity of arc k. For each block, each node v transmits, on each of its output arcs k, nck bits formed as random linear combinations of input bits (source bits originating at v and bits received on input arcs). 4. x1 ∈ Fnr 2 and x2 ∈ F2 are vectors of source bits being multicast to the receivers, and the matrices ϒi are matrices of random bits.

We thus consider each packet as a vector of symbols from Fq ; we refer to such a vector as a packet vector. We can think of source packets and transmitted packets as analogous to source processes and arc processes, respectively, in the static network model. The kth symbol of a transmitted packet is a scalar linear function of the kth symbol of each of its constituent packets, and this function is the same for all k. This is analogous to the formation of an arc process Yl as a linear combination of one or more of the input processes of node o(l) in the static model.

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