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: "capacity bounds for wireless ergodic fading broadcast channels with partial csit"
  Abstract: The two-user wireless ergodic fading Broadcast Channel (BC) with partial Channel State Information at the Transmitter (CSIT) is considered. The CSIT is given by an arbitrary deterministic function of the channel state. This characteristic yields a full control over how much state information is available, from perfect to no information. In literature, capacity derivations for wireless ergodic fading channels, specifically for fading BCs, mostly rely on the analysis of channels comprising of parallel sub-channels. This technique is usually suitable for the cases where perfect state information is available at the transmitters. In this paper, new arguments are proposed to directly derive (without resorting to the analysis of parallel channels) capacity bounds for the two-user fading BC with both common and private messages based on the existing bounds for the discrete channel. Specifically, a novel approach is developed to adapt and evaluate the well-known UV-outer bound for the Gaussian fading channel using the entropy power inequality. Our approach indeed sheds light on the role of broadcast auxiliaries in the fading channel. It is shown that the derived outer bound is optimal for the channel with perfect CSIT as well as for some special cases with partial CSIT. Our outer bound is also directly applicable to the case without CSIT which has been recently considered in several papers. Next, the approach is developed to analyze for the fading BC with secrecy. In the case of perfect CSIT, a full characterization of the secrecy capacity region is derived for the channel with common and confidential messages. This result completes a gap in a previous work by Ekrem and Ulukus. For the channel without common message, the secrecy capacity region is also derived when the transmitter has access only to the degradedness ordering of the channel.

Connected through hyperedge HE-1 (induced by source paper "capacity bounds and a certain capacity region for special three receiver broadcast channels with side information"):
  with members:
    - "three receiver broadcast channels with side information"
    - "duality between channel capacity and rate distortion with two sided state information"

Connected through hyperedge HE-2 (induced by source paper "the capacity region of the wireless ergodic fading interference channel with partial csit to within one bit"):
  with members:
    - "fundamental limits of communications in interference networks part i basic structures"
    - "fundamental limits of communications in interference networks part ii information flow in degraded networks"
    - "ergodic fading interference channels sum capacity and separability"
    - "interference mitigation through limited transmitter cooperation"
    - "feedback capacity of the gaussian interference channel to within 2 bits"
    - "a general coding scheme for two user fading interference channels"
    - "interference mitigation through limited receiver cooperation"
    - "outage analysis of block fading gaussian interference channels"

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)