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: "uplink interference analysis for two tier cellular networks with diverse users under random spatial patterns"
  Abstract: Multi-tier architecture improves the spatial reuse of radio spectrum in cellular networks, but it introduces complicated heterogeneity in the spatial distribution of transmitters, which brings new challenges in interference analysis. In this work, we present a stochastic geometric model to evaluate the uplink interference in a two-tier network considering multi-type users and base stations. Each type of tier-1 users and tier-2 base stations are modeled as independent homogeneous Poisson point processes, and tier-2 users are modeled as locally non-homogeneous clustered Poisson point processes centered at tier-2 base stations. By applying a superposition-aggregation-superposition approach, we quantify the interference at both tiers. Our model is also able to capture the impact of two types of exclusion regions, where either tier-2 base stations or tier-2 users are restricted in order to avoid cross-tier interference. As an important application of this analytical model, an intensity planning scenario is investigated, in which we aim to maximize the total income of the network operator with respect to the intensities of tier-2 cells, under constraints on the outage probabilities of tier-1 and tier-2 users. The result of our interference analysis suggests that this maximization can be converted to a standard convex optimization problem. Finally, numerical studies further demonstrate the correctness of our analysis.

Connected through hyperedge HE-1 (induced by source paper "outage performance of uplink two tier networks under backhaul constraints"):
  with members:
    - "on stochastic geometry modeling of cellular uplink transmission with truncated channel inversion power control"
    - "heterogeneous cellular networks with flexible cell association a comprehensive downlink sinr analysis"
    - "modeling and analysis of k tier downlink heterogeneous cellular networks"
    - "open vs closed access femtocells in the uplink"
    - "uplink capacity and interference avoidance for two tier femtocell networks"

Connected through hyperedge HE-2 (induced by source paper "outage analysis of uplink two tier networks"):
  with members:
    - "on stochastic geometry modeling of cellular uplink transmission with truncated channel inversion power control"
    - "understanding the benefits of open access in femtocell networks stochastic geometric analysis in the uplink"
    - "analytical modeling of uplink cellular networks"
    - "heterogeneous cellular networks with flexible cell association a comprehensive downlink sinr analysis"
    - "modeling and analysis of k tier downlink heterogeneous cellular networks"
    - "a tractable approach to coverage and rate in cellular networks"
    - "open vs closed access femtocells in the uplink"
    - "power control in two tier femtocell networks"

Connected through hyperedge HE-3 (induced by source paper "understanding the benefits of open access in femtocell networks stochastic geometric analysis in the uplink"):
  with members:
    - "offloading in heterogeneous networks modeling analysis and design insights"
    - "analytical modeling of uplink cellular networks"
    - "open closed and shared access femtocells in the downlink"
    - "modeling and analysis of k tier downlink heterogeneous cellular networks"
    - "open vs closed access femtocells in the uplink"
    - "uplink capacity and interference avoidance for two tier femtocell 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.NI(Networking and Internet Architecture)