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: "energy group buying with loading sharing for green cellular networks"
  Abstract: In the emerging hybrid electricity market, mobile network operators (MNOs) of cellular networks can make day-ahead energy purchase commitments at low prices and real-time flexible energy purchase at high prices. To minimize electricity bills, it is essential for MNOs to jointly optimize the day-ahead and real-time energy purchase based on their time-varying wireless traffic load. In this paper, we consider two different MNOs coexisting in the same area, and exploit their collaboration in both energy purchase and wireless load sharing for energy cost saving. Specifically, we propose a new approach named energy group buying with load sharing, in which the two MNOs are aggregated as a single group to make the day-ahead and real-time energy purchase, and their base stations (BSs) share the wireless traffic to maximally turn lightly-loaded BSs into sleep mode. When the two MNOs belong to the same entity and aim to minimize their total energy cost, we use the two-stage stochastic programming to obtain the optimal day-ahead and real-time energy group buying jointly with wireless load sharing. When the two MNOs belong to different entities and are self-interested in minimizing their individual energy costs, we propose a novel repeated Nash bargaining scheme for them to negotiate and share their energy costs under energy group buying and load sharing. Our proposed repeated Nash bargaining scheme is shown to achieve Pareto-optimal and fair energy cost reductions for both MNOs.

Connected through hyperedge HE-1 (induced by source paper "context aware group buying in ultra dense small cell networks unity is strength"):
  with members:
    - "two sided matching based cooperative spectrum sharing"
    - "load optimization with user association in cooperative and load coupled lte networks"
    - "user mobility evaluation for 5g small cell networks based on individual mobility model"
    - "5g ultra dense cellular networks"
    - "coalitional games with overlapping coalitions for interference management in small cell networks"

Connected through hyperedge HE-2 (induced by source paper "adaptively directional wireless power transfer for large scale sensor networks"):
  with members:
    - "green 5g heterogeneous networks through dynamic small cell operation"
    - "wireless powered communication opportunities and challenges"
    - "spatial throughput maximization of wireless powered communication networks"
    - "user cooperation in wireless powered communication networks"
    - "energy beamforming with one bit feedback"
    - "wireless networks with rf energy harvesting a contemporary survey"
    - "multiuser miso beamforming for simultaneous wireless information and power transfer"
    - "simultaneous information and energy transfer in large scale networks with without relaying"

Connected through hyperedge HE-3 (induced by source paper "green 5g heterogeneous networks through dynamic small cell operation"):
  with members:
    - "dynamic base station operation in large scale green cellular networks"
    - "spatial throughput maximization of wireless powered communication networks"
    - "what will 5g be"
    - "joint energy and spectrum cooperation for cellular communication systems"
    - "offloading in heterogeneous networks modeling analysis and design insights"
    - "user association for load balancing in heterogeneous cellular networks"
    - "optimal power and range adaptation for green broadcasting"
    - "green cellular networks a survey some research issues and challenges"

Connected through hyperedge HE-4 (induced by source paper "dynamic base station operation in large scale green cellular networks"):
  with members:
    - "green 5g heterogeneous networks through dynamic small cell operation"
    - "energy harvesting wireless communications a review of recent advances"
    - "comp meets smart grid a new communication and energy cooperation paradigm"
    - "a general utility optimization framework for energy harvesting based wireless communications"
    - "spatial throughput maximization of wireless powered communication networks"
    - "a lyapunov optimization approach for green cellular networks with hybrid energy supplies"
    - "quantifying potential energy efficiency gain in green cellular wireless networks"
    - "base station sleeping and resource allocation in renewable energy powered 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)