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: "on the sum capacity of degraded gaussian multiaccess relay channels"
  Abstract: The sum-capacity is studied for a K-user degraded Gaussian multiaccess relay channel (MARC) where the multiaccess signal received at the destination from the K sources and relay is a degraded version of the signal received at the relay from all sources, given the transmit signal at the relay. An outer bound on the capacity region is developed using cutset bounds. An achievable rate region is obtained for the decode-and-forward (DF) strategy. It is shown that for every choice of input distribution, the rate regions for the inner (DF) and outer bounds are given by the intersection of two K-dimensional polymatroids, one resulting from the multiaccess link at the relay and the other from that at the destination. Although the inner and outer bound rate regions are not identical in general, for both cases, a classical result on the intersection of two polymatroids is used to show that the intersection belongs to either the set of active cases or inactive cases, where the two bounds on the K-user sum-rate are active or inactive, respectively. It is shown that DF achieves the capacity region for a class of degraded Gaussian MARCs in which the relay has a high SNR link to the destination relative to the multiaccess link from the sources to the relay. Otherwise, DF is shown to achieve the sum-capacity for an active class of degraded Gaussian MARCs for which the DF sum-rate is maximized by a polymatroid intersection belonging to the set of active cases. This class is shown to include the class of symmetric Gaussian MARCs where all users transmit at the same power.

Connected through hyperedge HE-1 (induced by source paper "opportunistic communications in fading multiaccess relay channels"):
  with members:
    - "wireless network information flow a deterministic approach"
    - "fading broadcast channels with state information at the receivers"
    - "the two user gaussian interference channel a deterministic view"
    - "opportunism in multiuser relay channels scheduling routing and spectrum reuse"

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)