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: "on energy cooperation in energy harvesting underlay cognitive radio network"
  Abstract: In this paper, we consider an energy harvesting cognitive radio network (EH-CRN), where a primary and a secondary user coexist in underlay mode. Both the transmitters have energy harvesting capability and are equipped with finite capacity battery to store the harvested energy. In addition, the secondary user (SU) has an independent energy transfer unit such that it can transfer some portion of it's harvested energy to the primary user (PU). We obtain an optimal transmit power and energy transfer policy for single-slot and a suboptimal policy for multi-slot scenario maximizing the number of bits transmitted by SU under the primary sum-rate constraint in an offline setting. For both cases, the effect of energy cooperation on the system performance is studied and it is observed that energy cooperation results in higher SU throughput.

Connected through hyperedge HE-1 (induced by source paper "harvest or transmit policy for cognitive radio networks a learning theoretic approach"):
  with members:
    - "spectrum access in cognitive radio using a two stage reinforcement learning approach"
    - "optimal harvest or transmit strategy for energy harvesting underlay cognitive radio network"
    - "end to end throughput maximization for underlay multi hop cognitive radio networks with rf energy harvesting"
    - "online time sharing policy in energy harvesting cognitive radio network with channel uncertainty"
    - "on optimal offline time sharing policy for energy harvesting underlay cognitive radio"
    - "an optimal transmission policy for energy harvesting systems with continuous energy and data arrivals"
    - "optimal time sharing in underlay cognitive radio systems with rf energy harvesting"
    - "on green energy powered cognitive radio networks"

Connected through hyperedge HE-2 (induced by source paper "optimal harvest or transmit strategy for energy harvesting underlay cognitive radio network"):
  with members:
    - "optimal time sharing in underlay cognitive radio systems with rf energy harvesting"
    - "on information and energy cooperation in energy harvesting cognitive radio"
    - "information and energy cooperation in cognitive radio networks"
    - "on green energy powered cognitive radio 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)