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: "a lattice approach for optimal rate diverse wireless network coding"
  Abstract: This paper proposes an encoding/decoding framework for achieving the optimal channel capacity of the two-user broadcast channel where each user has message targeted for the other user as side information. Since the link qualities of the channels from the base station to users are different, the channel capacities are different. This fact implies different data rates for different users. For this scenario, the network coding technique can be employed to improve the transmission efficiency. However, how to simultaneously achieve the channel capacities for the two users is not straightforward. This problem is referred to as the rate-diverse wireless network coding problem. In this paper, we present a capacity-achieving framework based on linear structured nested lattice codes for rate-diverse wireless network coding. The significance of the proposed framework, besides its theoretical optimality, is its suggested design principle for linear rate-diverse wireless network coding.

Connected through hyperedge HE-1 (induced by source paper "lattice codes achieve the capacity of common message gaussian broadcast channels with coded side information"):
  with members:
    - "capacity of coded index modulation"
    - "index codes for the gaussian broadcast channel using quadrature amplitude modulation"
    - "lattice index coding"
    - "index coding with coded side information"
    - "lattice index codes from algebraic number fields"
    - "joint network and gelfand pinsker coding for 3 receiver gaussian broadcast channels with receiver message side information"
    - "the capacity of three receiver awgn broadcast channels with receiver message side information"
    - "achieving awgn channel capacity with lattice gaussian 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)