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: "network topology adaptation and interference coordination for energy saving in heterogeneous networks"
  Abstract: Interference coupling in heterogeneous networks introduces the inherent non-convexity to the network resource optimization problem, hindering the development of effective solutions. A new framework based on multi-pattern formulation has been proposed in this paper to study the energy efficient strategy for joint cell activation, user association and multicell multiuser channel allocation. One key feature of this interference pattern formulation is that the patterns remain fixed and independent of the optimization process. This creates a favorable opportunity for a linear programming formulation while still taking interference coupling into account. A tailored algorithm is developed to solve the formulated network energy saving problem in the dual domain by exploiting the problem structure, which gives a significant complexity saving compared to using standard solvers. Numerical results show a huge improvement in energy saving achieved by the proposed scheme.

Connected through hyperedge HE-1 (induced by source paper "energy management in heterogeneous networks with cell activation user association and interference coordination"):
  with members:
    - "energy efficient cell activation user association and spectrum allocation in heterogeneous networks"
    - "traffic driven spectrum allocation in heterogeneous networks"
    - "base station activation and linear transceiver design for optimal resource management in heterogeneous networks"
    - "optimal joint user association and resource allocation in heterogeneous networks via sparsity pursuit"
    - "joint user association and reuse pattern selection in heterogeneous networks"
    - "group sparse beamforming for green cloud ran"
    - "base station selection for energy efficient network operation with the majorization minimization algorithm"
    - "user association for load balancing in heterogeneous cellular networks"

Connected through hyperedge HE-2 (induced by source paper "optimized sensor collaboration for estimation of temporally correlated parameters"):
  with members:
    - "large scale convex optimization for dense wireless cooperative networks"
    - "optimal power allocation for distributed blue estimation with linear spatial collaboration"
    - "distributed estimation and detection with bounded transmissions over gaussian multiple access channels"
    - "controlled collaboration for linear coherent estimation in wireless sensor networks"
    - "optimal identical binary quantizer design for distributed estimation"
    - "on linear coherent estimation with spatial collaboration"
    - "distributed detection over fading macs with multiple antennas at the fusion center"
    - "estimation diversity and energy efficiency in distributed sensing"

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.NI(Networking and Internet Architecture)