human: Given a node-centered hypergraph: <hypergraph>, where nodes represent papers and hyperedges represent sets of papers co-cited by a source paper.

Details of the hypergraph:
Center node: "circular shift linear network coding"
  Abstract: We study a class of linear network coding (LNC) schemes, called  circular-shift  LNC, whose encoding operations consist of only circular-shifts and bit-wise additions. Formulated as a special vector linear code over GF(2), an    $L$   -dimensional circular-shift linear code of degree    $\delta $    restricts its local encoding kernels to be the summation of at most    $\delta $    cyclic permutation matrices of size    $L$   . We show that on a general network, for a certain block length    $L$   , every scalar linear solution over GF(   $2^{L-1}$   ) can induce an    $L$   -dimensional circular-shift linear solution with 1-bit redundancy per-edge transmission. Consequently, specific to a multicast network, such a circular-shift linear solution of an arbitrary degree    $\delta $    can be efficiently constructed, which has an interesting complexity tradeoff between encoding and decoding with different choices of    $\delta $   . By further proving that circular-shift LNC is insufficient to achieve the exact capacity of certain multicast networks, we show the optimality of the efficiently constructed circular-shift linear solution in the sense that its 1-bit redundancy is inevitable. Finally, both theoretical and numerical analysis imply that with increasing    $L$   , a randomly constructed circular-shift linear code has linear solvability behavior comparable to a randomly constructed permutation-based linear code, but has shorter overheads.

Connected through hyperedge HE-1 (induced by source paper "delay complexity trade off of random linear network coding in wireless broadcast"):
  with members:
    - "circular shift linear network codes with arbitrary odd block lengths"
    - "approximating throughput and packet decoding delay in linear network coded wireless broadcast"
    - "decoding delay performance of random linear network coding for broadcast"
    - "optimal control for network coding broadcast"
    - "on vector linear solvability of multicast networks"
    - "decoding and file transfer delay balancing in network coding broadcast"
    - "completion delay minimization for instantly decodable network codes"
    - "throughput delay analysis of random linear network coding for wireless broadcasting"

Connected through hyperedge HE-2 (induced by source paper "circular shift linear network codes with arbitrary odd block lengths"):
  with members:
    - "linear network coding over rings part ii vector codes and non commutative alphabets"
    - "a class of non linearly solvable networks"
    - "on the message dimensions of vector linearly solvable networks"
    - "on vector linear solvability of multicast networks"
    - "vector network coding based on subspace codes outperforms scalar linear network coding"

Question: Please tell me which class the center node belongs to. The 40 classes are: cs.NA(Numerical Analysis), cs.MM(Multimedia), cs.LO(Logic in Computer Science), cs.CY(Computers and Society), cs.CR(Cryptography and Security), cs.DC(Distributed, Parallel, and Cluster Computing), cs.HC(Human-Computer Interaction), cs.CE(Computational Engineering, Finance, and Science), cs.NI(Networking and Internet Architecture), cs.CC(Computational Complexity), cs.AI(Artificial Intelligence), cs.MA(Multiagent Systems), cs.GL(General Literature), cs.NE(Neural and Evolutionary Computing), cs.SC(Symbolic Computation), cs.AR(Hardware Architecture), cs.CV(Computer Vision and Pattern Recognition), cs.GR(Graphics), cs.ET(Emerging Technologies), cs.SY(Systems and Control), cs.CG(Computational Geometry), cs.OH(Other Computer Science), cs.PL(Programming Languages), cs.SE(Software Engineering), cs.LG(Machine Learning), cs.SD(Sound), cs.SI(Social and Information Networks), cs.RO(Robotics), cs.IT(Information Theory), cs.PF(Performance), cs.CL(Computation and Language), cs.IR(Information Retrieval), cs.MS(Mathematical Software), cs.FL(Formal Languages and Automata Theory), cs.DS(Data Structures and Algorithms), cs.OS(Operating Systems), cs.GT(Computer Science and Game Theory), cs.DB(Databases), cs.DL(Digital Libraries), cs.DM(Discrete Mathematics). Directly output the class name.

gpt: cs.IT(Information Theory)