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: "spatial topology adjustment for minimizing multicell network power consumption"
  Abstract: While the deployment of base stations (BSs) becomes increasingly dense in order to accommodate the growth in traffic demand, these BSs may be under-utilized during most hours except peak hours. Accordingly, the deactivation of these under-utilized BSs is regarded as the key to reducing network power consumption; however, the remaining active BSs should increase their transmit power in order to fill network coverage holes that result from BS switching off. This paper investigates the optimal balance between such beneficial and harmful effects of BS switching off in terms of minimizing the network power consumption, through comprehensively considering the spatial BS distribution, BS transmit power, BS power consumption behaviors, radio propagation environments, and frequency reuse. When BSs are deployed according to a homogeneous Poisson point process, the suboptimal and approximated design problems are formulated as geometric programming and the solutions lead to insightful design principles for the key design parameters including the spatial density, transmit power, and frequency reuse of remaining active BSs. The numerical results demonstrate that these solutions are very close to the optimal balances.

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"
    - "area spectral efficiency analysis and energy consumption minimization in multiantenna poisson distributed networks"
    - "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"

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)