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: "a new cell association scheme in heterogeneous networks"
  Abstract: Cell association scheme determines which base station (BS) and mobile user (MU) should be associated with and also plays a significant role in determining the average data rate a MU can achieve in heterogeneous networks. However, the explosion of digital devices and the scarcity of spectra collectively force us to carefully re-design cell association scheme which was kind of taken for granted before. To address this, we develop a new cell association scheme in heterogeneous networks based on joint consideration of the signal-to-interference-plus-noise ratio (SINR) which a MU experiences and the traffic load of candidate BSs1. MUs and BSs in each tier are modeled as several independent Poisson point processes (PPPs) and all channels experience independently and identically distributed (i.i.d.) Rayleigh fading. Data rate ratio and traffic load ratio distributions are derived to obtain the tier association probability and the average ergodic MU data rate. Through numerical results, We find that our proposed cell association scheme outperforms cell range expansion (CRE) association scheme. Moreover, results indicate that allocating small sized and high-density BSs will improve spectral efficiency if using our proposed cell association scheme in heterogeneous networks.

Connected through hyperedge HE-1 (induced by source paper "dense small cell networks from noise limited to dense interference limited"):
  with members:
    - "on the energy efficient deployment for ultra dense heterogeneous networks with nlos and los transmissions"
    - "effect of densification on cellular network performance with bounded pathloss model"
    - "performance limits of network densification"
    - "impact of los nlos propagation and path loss in ultra dense cellular networks"
    - "coverage analysis of heterogeneous cellular networks in urban areas"
    - "the intensity matching approach a tractable stochastic geometry approximation to system level analysis of cellular networks"
    - "performance impact of idle mode capability on dense small cell networks"
    - "performance impact of los and nlos transmissions in dense cellular networks"

Connected through hyperedge HE-2 (induced by source paper "on the energy efficient deployment for ultra dense heterogeneous networks with nlos and los transmissions"):
  with members:
    - "sinr and throughput of dense cellular networks with stretched exponential path loss"
    - "effect of densification on cellular network performance with bounded pathloss model"
    - "modeling and analysis of cellular networks using stochastic geometry a tutorial"
    - "user association in 5g networks a survey and an outlook"
    - "coverage analysis of heterogeneous cellular networks in urban areas"
    - "stochastic geometric analysis of energy efficient dense cellular networks"
    - "joint downlink cell association and bandwidth allocation for wireless backhauling in two tier hetnets with large scale antenna arrays"
    - "physical layer security in heterogeneous cellular networks"

Connected through hyperedge HE-3 (induced by source paper "coverage analysis of heterogeneous cellular networks in urban areas"):
  with members:
    - "5g ultra dense cellular networks"
    - "5g wireless backhaul networks challenges and research advances"
    - "analysis of blockage effects on urban cellular networks"
    - "a tractable approach to coverage and rate in cellular 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)