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: "area spectral efficiency analysis and energy consumption minimization in multiantenna poisson distributed networks"
  Abstract: We obtain the expression and a lower-bound for area spectral efficiency (ASE) of single-tier Poisson distributed networks considering multiuser MIMO (MU-MIMO) transmission. With the help of the lower-bound, we observe some interesting results. These results are validated via numerical results for the original expression. We find that ASE can be viewed as a concave function with respect to the number of antennas and active users. For the purpose of maximizing ASE, we demonstrate that the optimal number of active users is a fixed portion of the number of antennas. With the optimal number of active users, we observe that ASE increases linearly with the number of antennas. Another contribution of this paper is joint optimization of the base station (BS) density, the number of antennas, and active users to minimize the network energy consumption. We demonstrate that the optimal combination of the number of antennas and active users is the solution that maximizes the energy-efficiency. Besides the optimal algorithm, we propose a suboptimal algorithm to reduce the computational complexity, which can achieve near-optimal performance.

Connected through hyperedge HE-1 (induced by source paper "system level modeling and optimization of the energy efficiency in cellular networks a stochastic geometry framework"):
  with members:
    - "effect of densification on cellular network performance with bounded pathloss model"
    - "modeling and analysis of cellular networks using stochastic geometry a tutorial"
    - "enhanced cellular coverage and throughput using rateless codes"
    - "stochastic geometric analysis of energy efficient dense cellular networks"
    - "the intensity matching approach a tractable stochastic geometry approximation to system level analysis of cellular networks"
    - "a survey of energy efficient techniques for 5g networks and challenges ahead"
    - "spatial spectrum and energy efficiency of random cellular networks"
    - "stochastic geometry modeling of cellular networks analysis simulation and experimental validation"

Connected through hyperedge HE-2 (induced by source paper "area spectral efficiency analysis of multi antenna two tier cellular networks"):
  with members:
    - "the intensity matching approach a tractable stochastic geometry approximation to system level analysis of cellular networks"
    - "performance analysis of massive mimo for cell boundary users"
    - "success probability and area spectral efficiency in multiuser mimo hetnets"
    - "what will 5g be"
    - "analysis of joint transmit receive diversity in downlink mimo heterogeneous cellular networks"
    - "throughput and energy efficiency analysis of small cell networks with multi antenna base stations"
    - "downlink mimo hetnets modeling ordering results and performance analysis"
    - "average rate of downlink heterogeneous cellular networks over generalized fading channels a stochastic geometry approach"

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)