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: "optimal harvest or transmit strategy for energy harvesting underlay cognitive radio network"
  Abstract: An underlay cognitive radio network with energy harvesting is considered which operates in slotted fashion. The primary user (PU) transmits with a constant power in each slot, while the secondary user (SU) either harvests energy from primary's transmission or transmits its data. We propose an optimal offline harvest-or-transmit strategy where in each slot, SU takes a decision whether to harvest energy or transmit its data limiting interference at the primary receiver. We aim to maximize the achievable rate of SU under energy causality and interference constraints. The optimization problem is formulated as a mixed integer non-linear program and the optimal harvest-or-transmit policy is obtained using generalized Benders decomposition algorithm. Through simulations, we analyze the effects of various system parameters and interference constraint at the primary receiver on the optimal policy.

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"
    - "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"
    - "on energy cooperation in energy harvesting underlay cognitive radio network"
    - "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"

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)