human: Given a hyperedge-centered hypergraph: <hypergraph>, where the center hyperedge is induced by one source paper and its member nodes are the cited papers.

Details of the hypergraph:
Center hyperedge (induced by source paper "system level modeling and optimization of the energy efficiency in cellular networks a stochastic geometry framework"):
  Abstract: In this paper, we analyze and optimize the energy efficiency of downlink cellular networks. With the aid of tools from stochastic geometry, we introduce a new closed-form analytical expression of the potential spectral efficiency (bit/sec/m$^2$). In the interference-limited regime for data transmission, unlike currently available mathematical frameworks, the proposed analytical formulation depends on the transmit power and deployment density of the base stations. This is obtained by generalizing the definition of coverage probability and by accounting for the sensitivity of the receiver not only during the decoding of information data, but during the cell association phase as well. Based on the new formulation of the potential spectral efficiency, the energy efficiency (bit/Joule) is given in a tractable closed-form formula. An optimization problem is formulated and is comprehensively studied. It is mathematically proved, in particular, that the energy efficiency is a unimodal and strictly pseudo-concave function in the transmit power, given the density of the base stations, and in the density of the base stations, given the transmit power. Under these assumptions, therefore, a unique transmit power and density of the base stations exist, which maximize the energy efficiency. Numerical results are illustrated in order to confirm the obtained findings and to prove the usefulness of the proposed framework for optimizing the network planning and deployment of cellular networks from the energy efficiency standpoint.

Includes members:
  Member "effect of densification on cellular network performance with bounded pathloss model":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "hetnets coverage modeling and analysis over fox s mathcal h fading channels")
  Member "modeling and analysis of cellular networks using stochastic geometry a tutorial":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "area spectral efficiency and sinr scaling laws in multi antenna cellular networks")
  Member "enhanced cellular coverage and throughput using rateless codes":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "rate statistics in cellular downlink a per user analysis of rateless coded transmission")
  Member "area spectral efficiency analysis and energy consumption minimization in multiantenna poisson distributed networks":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "area spectral efficiency analysis of multi antenna two tier cellular networks")
  Member "stochastic geometric analysis of energy efficient dense cellular networks":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "on the energy efficient deployment for ultra dense heterogeneous networks with nlos and los transmissions")
  Member "the intensity matching approach a tractable stochastic geometry approximation to system level analysis of cellular networks":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "smart radio environments empowered by ai reconfigurable meta surfaces an idea whose time has come")
  Member "a survey of energy efficient techniques for 5g networks and challenges ahead":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "5g network slicing using sdn and nfv a survey of taxonomy architectures and future challenges")
  Member "spatial spectrum and energy efficiency of random cellular networks":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "spatio temporal modeling for massive and sporadic access")

Question: Please tell me which class the source paper 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)