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: "base station selection for energy efficient network operation with the majorization minimization algorithm"
  Abstract: In this paper, we study the problem of reducing the energy consumption in a mobile communication network; we select the smallest set of active base stations that can preserve the quality of service (the minimum data rate) required by the users. In more detail, we start by posing this problem as an integer programming problem, the solution of which shows the optimal assignment (in the sense of minimizing the total energy consumption) between base stations and users. In particular, this solution shows which base stations can then be switched off or put in idle mode to save energy. However, solving this problem optimally is intractable in general, so in this study we develop a suboptimal approach that builds upon recent techniques that have been successfully applied to, among other problems, sparse signal reconstruction, portfolio optimization, statistical estimation, and error correction. More precisely, we relax the original integer programming problem as a minimization problem where the objective function is concave and the constraint set is convex. The resulting relaxed problem is still intractable in general, but we can apply the majorization-minimization algorithm to find good solutions (i.e., solutions attaining low objective value) with a low-complexity algorithm. In contrast to state-of-the-art approaches, the proposed algorithm can take into account inter-cell interference, is suitable for large-scale problems, and can be applied to heterogeneous networks (networks where base station consume different amounts of energy)

Connected through hyperedge HE-1 (induced by source paper "a note on decoding order in optimizing multi cell noma"):
  with members:
    - "a robust machine learning method for cell load approximation in wireless networks"
    - "a framework for optimizing multi cell noma delivering demand with less resource"
    - "resource optimization with load coupling in multi cell noma"
    - "on optimal power allocation for downlink non orthogonal multiple access systems"
    - "energy aware wireless relay selection in load coupled ofdma cellular networks"
    - "load optimization with user association in cooperative and load coupled lte networks"
    - "dynamic user clustering and power allocation for uplink and downlink non orthogonal multiple access noma systems"
    - "elementary properties of positive concave mappings with applications to network planning and optimization"

Connected through hyperedge HE-2 (induced by source paper "resource allocation in green dense cellular networks complexity and algorithms"):
  with members:
    - "large scale spectrum allocation for cellular networks via sparse optimization"
    - "optimal user scheduling in energy harvesting wireless networks"
    - "scalable spectrum allocation and user association in networks with many small cells"
    - "boost base station on off switching strategy for energy efficient massive mimo hetnets"
    - "online ski rental for on off scheduling of energy harvesting base stations"
    - "online energy efficient packet scheduling for a common deadline with and without energy harvesting"
    - "gate greening at the edges"
    - "energy efficient cell activation user association and spectrum allocation in heterogeneous networks"

Connected through hyperedge HE-3 (induced by source paper "resource optimization with load coupling in multi cell noma"):
  with members:
    - "a robust machine learning method for cell load approximation in wireless networks"
    - "a framework for optimizing multi cell noma delivering demand with less resource"
    - "on optimal power allocation for downlink non orthogonal multiple access systems"
    - "energy aware wireless relay selection in load coupled ofdma cellular networks"
    - "sub channel assignment power allocation and user scheduling for non orthogonal multiple access networks"
    - "load optimization with user association in cooperative and load coupled lte networks"
    - "elementary properties of positive concave mappings with applications to network planning and optimization"
    - "power and channel allocation for non orthogonal multiple access in 5g systems tractability and computation"

Connected through hyperedge HE-4 (induced by source paper "the role of asymptotic functions in network optimization and feasibility studies"):
  with members:
    - "performance limits of solutions to network utility maximization problems"
    - "elementary properties of positive concave mappings with applications to network planning and optimization"
    - "power and load coupling in cellular networks for energy optimization"
    - "joint downlink base station association and power control for max min fairness computation and complexity"
    - "data offloading in load coupled networks a utility maximization framework"
    - "toward energy efficient 5g wireless communications technologies"
    - "analysis of cell load coupling for lte network planning and optimization"

Connected through hyperedge HE-5 (induced by source paper "energy management in heterogeneous networks with cell activation user association and interference coordination"):
  with members:
    - "network topology adaptation and interference coordination for energy saving in heterogeneous networks"
    - "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"
    - "user association for load balancing in heterogeneous cellular networks"

Connected through hyperedge HE-6 (induced by source paper "traffic demand aware topology control for enhanced energy efficiency of cellular networks"):
  with members:
    - "kernel based adaptive online reconstruction of coverage maps with side information"
    - "power and load coupling in cellular networks for energy optimization"
    - "power estimation in lte systems with the general framework of standard interference mappings"
    - "analysis of cell load coupling for lte network planning and optimization"
    - "enhanced intercell interference coordination challenges in heterogeneous networks"

Connected through hyperedge HE-7 (induced by source paper "network topology adaptation and interference coordination for energy saving in heterogeneous networks"):
  with members:
    - "joint user association and reuse pattern selection in heterogeneous networks"

Connected through hyperedge HE-8 (induced by source paper "energy efficient cell activation user association and spectrum allocation in heterogeneous networks"):
  with members:
    - "energy management in heterogeneous networks with cell activation user association and interference coordination"
    - "licensed and unlicensed spectrum allocation in heterogeneous networks"
    - "traffic driven spectrum allocation in heterogeneous networks"
    - "optimal joint user association and resource allocation in heterogeneous networks via sparsity pursuit"

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)