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: "when distributed outperforms centralized scheduling in d2d enabled cellular networks"
  Abstract: Device-to-device (D2D) communications is a promising technique for improving the efficiency of 5G networks. Employing channel adaptive resource allocation can yield to a large enhancement in almost any performance metric of D2D communications (e.g. Energy Efficiency). In this paper, we show that minimizing the users transmission power while maintaining predefined throughput constraint can be performed by simply adapting existing LTE CSI feedback. Thus, we propose a centralized scheduling that requires the knowledge of D2D links' Channel State Information (CSI) at the base station level. However, this CSI reporting suffers from the limited number of resources available for feedback transmission. Alternately, we propose a distributed algorithm for resource allocation that benefits from the users' knowledge of their local CSI in order to minimize the users' transmission power while maintaining predefined throughput constraints. The key idea is that users compute their local performance metrics (e.g. energy efficiency) and then use a new signaling mechanism to share these values between each other. Under some condition, the performance of this distributed algorithm achieves that of the \textit{ideal} scheduling (i.e. with a global CSI knowledge of all the D2D links). We describe how these algorithms can be simply integrated to existing cellular networks. Furthermore, numerical results are presented to corroborate our claims and demonstrate the gain that the proposed scheduling algorithms bring to cellular networks.

Connected through hyperedge HE-1 (induced by source paper "a dynamic and incentive policy for selecting d2d mobile relays"):
  with members:
    - "distributed resource allocation for relay aided device to device communication under channel uncertainties a stable matching approach"
    - "performance analysis of network assisted two hop d2d communications"

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)