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: "effects of base station spatial interdependence on interference correlation and network performance"
  Abstract: The spatial-and-temporal correlation of interference has been well studied in Poisson networks where the interfering base stations (BSs) are independent of each other. However, there exists spatial interdependence including attraction and repulsion among the BSs in practical wireless networks, affecting the interference distribution and hence the network performance. In view of this, by modeling the network as a Poisson clustered process, we study the effects of spatial interdependence among BSs on the interference distribution and prove that BS clustering increases the level of interference correlation. In particular, it is shown that the level increases as the attraction between the BSs increases. To quantify the effects of spatial interdependence among BSs on network performance, we consider heterogeneous cellular networks in which small-cell BSs exhibit a clustered topology in practice. Furthermore, a retransmission scheme is assumed since it amplifies the effects of interference correlation. It is shown that the repulsion between BSs from different tiers improves the outage performance of macro users while it has little impact on that of small-cell users. In addition, it is proved that the effects of BS clustering on the outage performance can be neglected if the mean number of clustering BSs is small.

Connected through hyperedge HE-1 (induced by source paper "on coverage probability with type ii harq in large uplink cellular networks"):
  with members:
    - "the meta distribution of the sir for cellular networks with power control"
    - "user point processes in cellular networks"
    - "on stochastic geometry modeling of cellular uplink transmission with truncated channel inversion power control"
    - "diversity polynomials for the analysis of temporal correlations in wireless 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)