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: "deterministic relay networks with state information"
  Abstract: Motivated by fading channels and erasure channels, the problem of reliable communication over deterministic relay networks is studied, in which relay nodes receive a function of the incoming signals and a random network state. An achievable rate is characterized for the case in which destination nodes have full knowledge of the state information. If the relay nodes receive a linear function of the incoming signals and the state in a finite field, then the achievable rate is shown to be optimal, meeting the cut-set upper bound on the capacity. This result generalizes on a unified framework the work of Avestimehr, Diggavi, and Tse on the deterministic networks with state dependency, the work of Dana, Gowaikar, Palanki, Hassibi, and Effros on linear erasure networks with interference, and the work of Smith and Vishwanath on linear erasure networks with broadcast.

Connected through hyperedge HE-1 (induced by source paper "on min cut algorithms for half duplex relay networks"):
  with members:
    - "approximately achieving gaussian relay network capacity with lattice codes"

Connected through hyperedge HE-2 (induced by source paper "slepian wolf coding over cooperative relay networks"):
  with members:
    - "wireless network information flow a deterministic approach"
    - "wyner ziv coding over broadcast channels digital schemes"
    - "approximate capacity of gaussian relay networks"
    - "protocols for half duplex multiple relay networks"
    - "analysis of a mixed strategy for multiple relay networks"

Connected through hyperedge HE-3 (induced by source paper "capacity of a class of linear binary field multi source relay networks"):
  with members:
    - "the approximate capacity of the many to one and one to many gaussian interference channels"
    - "ergodic interference alignment"
    - "on models of multi user gaussian channels with fading"
    - "approximate capacity of the two way relay channel a deterministic approach"
    - "multiple access outerbounds and the inseparability of parallel interference channels"
    - "the two user gaussian interference channel a deterministic view"
    - "approximate capacity of gaussian relay networks"
    - "transmission techniques for relay interference networks"

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)