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: "downlink cellular network analysis with multi slope path loss models"
  Abstract: Existing cellular network analyses, and even simulations, typically use the standard path loss model where received power decays like $\|x\|^{-\alpha}$ over a distance $\|x\|$. This standard path loss model is quite idealized, and in most scenarios the path loss exponent $\alpha$ is itself a function of $\|x\|$, typically an increasing one. Enforcing a single path loss exponent can lead to orders of magnitude differences in average received and interference powers versus the true values. In this paper we study \emph{multi-slope} path loss models, where different distance ranges are subject to different path loss exponents. We focus on the dual-slope path loss function, which is a piece-wise power law and continuous and accurately approximates many practical scenarios. We derive the distributions of SIR, SNR, and finally SINR before finding the potential throughput scaling, which provides insight on the observed cell-splitting rate gain. The exact mathematical results show that the SIR monotonically decreases with network density, while the converse is true for SNR, and thus the network coverage probability in terms of SINR is maximized at some finite density. With ultra-densification (network density goes to infinity), there exists a \emph{phase transition} in the near-field path loss exponent $\alpha_0$: if $\alpha_0 >1$ unbounded potential throughput can be achieved asymptotically; if $\alpha_0 <1$, ultra-densification leads in the extreme case to zero throughput.

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"
    - "sinr and throughput of dense cellular networks with stretched exponential path loss"
    - "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"

Connected through hyperedge HE-2 (induced by source paper "resource management in wireless networks via multi agent deep reinforcement learning"):
  with members:
    - "spectrum sharing in vehicular networks based on multi agent reinforcement learning"
    - "dota 2 with large scale deep reinforcement learning"
    - "on the power of curriculum learning in training deep networks"
    - "a deep q learning method for downlink power allocation in multi cell networks"
    - "deep reinforcement learning for distributed uncoordinated cognitive radios resource allocation"
    - "zpd teaching strategies for deep reinforcement learning from demonstrations"
    - "intelligent power control for spectrum sharing in cognitive radios a deep reinforcement learning approach"
    - "quantifying generalization in reinforcement learning"

Connected through hyperedge HE-3 (induced by source paper "scaling laws of dense multi antenna cellular networks"):
  with members:
    - "sinr and throughput of dense cellular networks with stretched exponential path loss"
    - "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 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-4 (induced by source paper "modeling and performance analysis in cache enabled millimeter wave hetnets with access and backhaul integration"):
  with members:
    - "modeling and analysis of d2d millimeter wave networks with poisson cluster processes"
    - "a unified asymptotic analysis of area spectral efficiency in ultradense cellular networks"
    - "downlink cellular network analysis with los nlos propagation and elevated base stations"
    - "modeling analysis and optimization of coded caching in small cell networks"
    - "dense small cell networks from noise limited to dense interference limited"
    - "coverage in downlink heterogeneous mmwave cellular networks with user centric small cell deployment"
    - "caching at the wireless edge design aspects challenges and future directions"
    - "energy efficiency of downlink networks with caching at base stations"

Connected through hyperedge HE-5 (induced by source paper "sense and predict harnessing spatial interference correlation for cognitive radio networks"):
  with members:
    - "ultra reliable and low latency communications in 5g downlink physical layer aspects"
    - "millimeter wave interference avoidance via building aware associations"
    - "the connectivity of millimeter wave networks in urban environments modeled using random lattices"
    - "macro diversity in cellular networks with random blockages"
    - "sense and predict opportunistic mac based on spatial interference correlation for cognitive radio networks"
    - "downlink and uplink cell association with traditional macrocells and millimeter wave small cells"
    - "spatio temporal interference correlation and joint coverage in cellular networks"
    - "design and analysis of initial access in millimeter wave cellular networks"

Connected through hyperedge HE-6 (induced by source paper "spectral efficiency analysis in dense massive mimo networks"):
  with members:
    - "network deployment for maximal energy efficiency in uplink with multislope path loss"
    - "massive mimo has unlimited capacity"
    - "performance impact of base station antenna heights in dense cellular networks"
    - "impact of los nlos propagation and path loss in ultra dense cellular networks"
    - "are we approaching the fundamental limits of wireless network densification"
    - "deploying dense networks for maximal energy efficiency small cells meet massive mimo"
    - "5g ultra dense cellular networks"
    - "massive mimo for next generation wireless systems"

Connected through hyperedge HE-7 (induced by source paper "caching or no caching in dense hetnets"):
  with members:
    - "modeling and analysis of cellular networks using stochastic geometry a tutorial"
    - "effect of retransmissions on optimal caching in cache enabled small cell networks"
    - "optimization and analysis of probabilistic caching in n tier heterogeneous networks"
    - "cache enabled heterogeneous cellular networks optimal tier level content placement"
    - "optimal geographic caching in cellular networks"
    - "what will 5g be"
    - "five disruptive technology directions for 5g"
    - "modeling and analysis of k tier downlink heterogeneous cellular networks"

Connected through hyperedge HE-8 (induced by source paper "on the coverage and capacity of ultra dense networks with directional transmissions"):
  with members:
    - "a unified asymptotic analysis of area spectral efficiency in ultradense cellular networks"
    - "downlink cellular network analysis with los nlos propagation and elevated base stations"
    - "performance analysis of millimeter wave relaying impacts of beamwidth and self interference"
    - "are we approaching the fundamental limits of wireless network densification"
    - "coverage and rate analysis for millimeter wave cellular networks"
    - "what will 5g be"
    - "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.IT(Information Theory)