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: "sinr and throughput of dense cellular networks with stretched exponential path loss"
  Abstract: Distance-based attenuation is a critical aspect of wireless communications. As opposed to the ubiquitous power-law path loss model, this paper proposes a stretched exponential path loss model that is suitable for short-range communication. In this model, the signal power attenuates over a distance $r$ as $e^{-\alpha r^{\beta}}$, where $\alpha,\beta$ are tunable parameters. Using experimental propagation measurements, we show that the proposed model is accurate for short to moderate distances in the range $r \in (5,300)$ meters and so is a suitable model for dense and ultradense networks. We integrate this path loss model into a downlink cellular network with base stations modeled by a Poisson point process, and derive expressions for the coverage probability, potential throughput, and area spectral efficiency. Although the most general result for coverage probability has a double integral, several special cases are given where the coverage probability has a compact or even closed form. We then show that the potential throughput is maximized for a particular BS density and then collapses to zero for high densities, assuming a fixed SINR threshold. We next prove that the area spectral efficiency, which assumes an adaptive SINR threshold, is non-decreasing with the BS density and converges to a constant for high densities.

Connected through hyperedge HE-1 (induced by source paper "area spectral efficiency and sinr scaling laws in multi antenna cellular networks"):
  with members:
    - "scaling laws of dense multi antenna cellular networks"
    - "a unified asymptotic analysis of area spectral efficiency in ultradense cellular networks"
    - "performance limits of network densification"
    - "modeling and analysis of cellular networks using stochastic geometry a tutorial"
    - "performance impact of base station antenna heights in dense cellular networks"
    - "a primer on cellular network analysis using stochastic geometry"
    - "scaling laws for ergodic spectral efficiency in mimo poisson networks"
    - "cooperative base station coloring for pair wise multi cell coordination"

Connected through hyperedge HE-2 (induced by source paper "scaling laws of dense multi antenna cellular networks"):
  with members:
    - "a unified asymptotic analysis of area spectral efficiency in ultradense cellular networks"
    - "performance limits of network densification"
    - "performance impact of base station antenna heights in dense cellular networks"
    - "spectral efficiency scaling laws in dense random wireless networks with multiple receive antennas"
    - "downlink cellular network analysis with multi slope path loss models"
    - "downlink mimo hetnets modeling ordering results and performance analysis"
    - "transmission capacity of wireless networks"
    - "a tractable approach to coverage and rate in cellular networks"

Connected through hyperedge HE-3 (induced by source paper "impact of spatial multiplexing on throughput of ultra dense mmwave ap network"):
  with members:
    - "modeling and analyzing millimeter wave cellular systems"
    - "stochastic geometry modeling and analysis of multi tier millimeter wave cellular networks"
    - "limited feedback hybrid precoding for multi user millimeter wave systems"
    - "coverage and rate analysis for millimeter wave cellular networks"
    - "what will 5g be"
    - "a tractable approach to coverage and rate in cellular networks"

Connected through hyperedge HE-4 (induced by source paper "local large deviation principle large deviation principle and information theory for the signal to interference and noise ratio graph models"):
  with members:
    - "interference modeling in cognitive radio networks a survey"
    - "local large deviations mcmillian theorem for multitype galton watson processes"
    - "lossy asymptotic equipartition property for geometric networked data structures"
    - "sinr model with best server association for high availability studies of wireless networks"

Connected through hyperedge HE-5 (induced by source paper "local large deviation principle large deviation principle for the signal to interference and noise ratio graph models"):
  with members:
    - "local large deviations mcmillian theorem for multitype galton watson processes"

Connected through hyperedge HE-6 (induced by source paper "a brief history on the theoretical analysis of dense small cell wireless networks"):
  with members:
    - "optimal base station antenna downtilt in downlink cellular networks"
    - "ultra dense networks is there a limit to spatial spectrum reuse"
    - "wireless powered dense cellular networks how many small cells do we need"
    - "inter operator base station coordination in spectrum shared millimeter wave cellular networks"
    - "downlink cellular network analysis with los nlos propagation and elevated base stations"
    - "performance impact of base station antenna heights in dense cellular networks"
    - "modeling infrastructure sharing in mmwave networks with shared spectrum licenses"
    - "spatially correlated content caching for device to device communications"

Connected through hyperedge HE-7 (induced by source paper "self organized scheduling request for uplink 5g networks a d2d clustering approach"):
  with members:
    - "power control and channel allocation for d2d underlaid cellular networks"
    - "ultra reliable and low latency wireless communication tail risk and scale"
    - "modeling and analysis of cellular networks using stochastic geometry a tutorial"
    - "the meta distribution of the sir for cellular networks with power control"
    - "stochastic geometry modeling and analysis of single and multi cluster wireless networks"
    - "spatiotemporal stochastic modeling of iot enabled cellular networks scalability and stability analysis"
    - "analytical modeling of interference aware power control for the uplink of heterogeneous cellular networks"
    - "modeling cellular networks with full duplex d2d communication a stochastic geometry approach"

Connected through hyperedge HE-8 (induced by source paper "a unified asymptotic analysis of area spectral efficiency in ultradense cellular networks"):
  with members:
    - "stochastic geometry analysis of ultra dense networks impact of antenna height and performance limits"
    - "modeling and analyzing millimeter wave cellular systems"
    - "effect of densification on cellular network performance with bounded pathloss model"
    - "performance limits of network densification"
    - "downlink cellular network analysis with los nlos propagation and elevated base stations"
    - "modeling and analysis of cellular networks using stochastic geometry a tutorial"
    - "performance impact of base station antenna heights in dense cellular networks"
    - "unified stochastic geometry modeling and analysis of cellular networks in los nlos and shadowed fading"

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)