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: "provisioning energy efficiency and qos for multi carrier comp with limited feedback"
  Abstract: We consider resource allocation (RA) in multi-carrier coordinated multi-point (CoMP) systems with limited feedback, in which a cluster of base stations (BSs), each equipped with multiple antennas, are connect to each other and/or a central processor via backhauls/fronthauls. The main objective of coordinated RA is to select user equipments (UEs) on each subcarrier, dynamically decide upon the cluster size for each subcarrier, and finally partition the feedback resources, provisioned for acquisition of channel direction information (CDI) across all subcarriers, active cells, and selected UEs, in order to maximize the weighted sum utility (WSU). We show how to recast the WSU maximization problem to achieve spectral efficiency, quality-of-service (QoS), and energyefficiency (EE). Specifically, we investigate four instances of WSU to maximize practical system objectives: (i) weighted sum capacity, (ii) weighted sum effective capacity, (iii) weighted sum energy-efficiency (EE), and (iv) weighted sum effective EE. The unified composition of these problems through WSU allows us to use the same set of developed algorithms for all cases. The algorithms have a greedy structure achieving fast convergence, and successfully cope with the huge computational complexity of RA problems, mostly rooted in their combinatorial compositions. Our simulation results shed lights on the network optimization by discovering insights on appropriate cluster-size, distribution of BSs in the cluster, and the number of subcarriers. The proposed UE scheduling and subcarrier assignment are shown to improve the system performance by several orders-of-magnitude.

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)