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: "sum capacity and the unique separability of the parallel gaussian mac z bc network"
  Abstract: It is known that the capacity of parallel (e.g., multi-carrier) Gaussian point-to-point, multiple access and broadcast channels can be achieved by separate encoding for each subchannel (carrier) subject to a power allocation across carriers. Recent results have shown that parallel interference channels are not separable, i.e., joint coding is needed to achieve capacity in general. This work studies the separability, from a sum-capacity perspective, of single hop Gaussian interference networks with independent messages and arbitrary number of transmitters and receivers. The main result is that the only network that is always (for all values of channel coefficients) separable from a sum-capacity perspective is the MAC-Z-BC network, i.e., a network where a MAC component and a BC component are linked by a Z component. The sum capacity of this network is explicitly characterized.

Connected through hyperedge HE-1 (induced by source paper "on the optimality of treating interference as noise for k user parallel gaussian interference networks"):
  with members:
    - "real interference alignment exploiting the potential of single antenna systems"
    - "on the optimality of treating interference as noise"
    - "the ergodic capacity of phase fading interference networks"
    - "wireless network information flow a deterministic approach"
    - "ergodic fading interference channels sum capacity and separability"
    - "interference alignment from degrees of freedom to constant gap capacity approximations"
    - "the approximate capacity of the many to one and one to many gaussian interference channels"
    - "on the capacity of the k user cyclic gaussian interference channel"

Connected through hyperedge HE-2 (induced by source paper "on the synergistic benefits of alternating csit for the miso bc"):
  with members:
    - "degrees of freedom of time correlated miso broadcast channel with delayed csit"
    - "degrees of freedom region of the miso broadcast channel with general mixed csit"
    - "optimal use of current and outdated channel state information degrees of freedom of the miso bc with mixed csit"
    - "on the degrees of freedom of time correlated miso broadcast channel with delayed csit"
    - "not too delayed csit achieves the optimal degrees of freedom"
    - "ergodic fading interference channels sum capacity and separability"
    - "the degrees of freedom regions of two user and certain three user mimo broadcast channels with delayed csit"
    - "completely stale transmitter channel state information is still very useful"

Connected through hyperedge HE-3 (induced by source paper "aligned interference neutralization and the degrees of freedom of the 2x2x2 interference channel"):
  with members:
    - "distributed data storage with minimum storage regenerating codes exact and functional repair are asymptotically equally efficient"
    - "exploiting channel correlations simple interference alignment schemes with no csit"
    - "error exponents for the gaussian channel with active noisy feedback"
    - "capacity bounds for two hop interference networks"
    - "real interference alignment with real numbers"
    - "on the degrees of freedom of the k user gaussian interference channel"
    - "on the sum capacity of a class of cyclically symmetric deterministic interference channels"
    - "ergodic interference alignment"

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)