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 user scheduling in energy harvesting wireless networks"
  Abstract: We consider a wireless network where multiple energy harvesting transmitters communicate with the common receiver in a time sharing manner. In each slot, a transmitter can either harvest energy or send its data to the receiver. Given a time deadline, the goal is to maximize the sum-rate of transmitters under random energy arrivals with both perfect and imperfect channel state information (CSI) at the receiver. The original sumrate maximization (SRM) problem is a non-convex mixed integer non-linear program (MINLP). To obtain the optimal scheduling policy, we first reduce the original optimization problem to a convex MINLP and solve it using the generalized Benders decomposition algorithm. We observe that the SRM problem results in an unfair rate allocation among transmitters, i.e., the transmitter closer to the receiver achieves a higher rate than that by the transmitter farther from the receiver. Hence, to induce fairness among transmitters, we consider the minimumrate maximization (MRM) problem. For the bounded channel estimation error, we obtain a robust scheduling policy by solving the worst-case SRM and MRM problems. Finally, we compare the proposed policies with myopic policies studied in the literature and show that the former outperform the latter in terms of achievable rates.

Connected through hyperedge HE-1 (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"
    - "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"
    - "optimizing user association and spectrum allocation in hetnets a utility perspective"

Connected through hyperedge HE-2 (induced by source paper "throughput maximization for full duplex wireless powered communication networks"):
  with members:
    - "optimal resource allocation in full duplex wireless powered communication network"
    - "full duplex wireless powered communication network with energy causality"
    - "throughput maximization in wireless powered communication networks"
    - "multi antenna wireless powered communication with energy beamforming"
    - "mimo broadcasting for simultaneous wireless information and power transfer"
    - "optimum transmission policies for battery limited energy harvesting nodes"

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)