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: "dynamic base station operation in large scale green cellular networks"
  Abstract: In this paper, to minimize the on-grid energy cost in a large-scale green cellular network, we jointly design the optimal base station (BS) on/off operation policy and the on-grid energy purchase policy from a network-level perspective. Due to the fluctuations of the on-grid energy prices, the harvested renewable energy, and the network traffic loads over time, as well as the BS coordination to hand over the traffic offloaded from the inactive BSs to the active BSs, it is generally NP-hard to find a network-level optimal adaptation policy that can minimize the on-grid energy cost over a long-term and yet assures the downlink transmission quality at the same time. Aiming at the network-level dynamic system design, we jointly apply stochastic geometry (Geo) for large-scale green cellular network analysis and dynamic programming (DP) for adaptive BS on/off operation design and on-grid energy purchase design, and thus propose a new Geo-DP design approach. By this approach, we obtain the optimal BS on/off policy, which shows that the optimal BSs' active operation probability in each horizon is just sufficient to assure the required downlink transmission quality with time-varying load in the large-scale cellular network. We also propose a suboptimal on-grid energy purchase policy with low-complexity, where the low-price on-grid energy is over-purchased in the current horizon only when the current storage level and the future renewable energy level are both low. We compare the proposed policy with the existing schemes and show that our proposed policy can more efficiently save the on-grid energy cost over time.

Connected through hyperedge HE-1 (induced by source paper "online policies for throughput maximization of energy constrained wireless powered communication systems"):
  with members:
    - "optimization of energy constrained wireless powered communication networks with heterogeneous nodes"
    - "wireless power meets energy harvesting a joint energy allocation approach in ofdm based system"
    - "resource allocation and fairness in wireless powered cooperative cognitive radio networks"
    - "battery powered devices in wpcns"
    - "on optimal policies in full duplex wireless powered communication networks"
    - "an overview of sustainable green 5g networks"
    - "optimal design of non orthogonal multiple access with wireless power transfer"
    - "energy efficient resource allocation for wireless powered communication networks"

Connected through hyperedge HE-2 (induced by source paper "green 5g heterogeneous networks through dynamic small cell operation"):
  with members:
    - "energy group buying with loading sharing for 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-3 (induced by source paper "optimal resource allocation for comp based cellular systems with base station switching"):
  with members:
    - "a stochastic geometry framework for analyzing pairwise cooperative 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)