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: "dynamic scheduling for delay guarantees for heterogeneous cognitive radio users"
  Abstract: We study an uplink multi secondary user (SU) system having statistical delay constraints, and an average interference constraint to the primary user (PU). SUs with heterogeneous interference channel statistics, to the PU, experience heterogeneous delay performances since SUs causing low interference are scheduled more frequently than those causing high interference. We propose a scheduling algorithm that can provide arbitrary average delay guarantees to SUs irrespective of their statistical channel qualities. We derive the algorithm using the Lyapunov technique and show that it yields bounded queues and satisfy the interference constraints. Using simulations, we show its superiority over the Max-Weight algorithm.

Connected through hyperedge HE-1 (induced by source paper "delay optimal joint scheduling and power control for cognitive radio uplinks"):
  with members:
    - "joint scheduling and power control for delay guarantees in heterogeneous cognitive radios"
    - "separation of signals consisting of amplitude and instantaneous frequency rrc pulses using snr uniform training"
    - "delay optimal scheduling and power control for instantaneous interference limited crs"
    - "throughput optimization in multichannel cognitive radios with hard deadline constraints"

Connected through hyperedge HE-2 (induced by source paper "joint scheduling and power control for delay guarantees in heterogeneous cognitive radios"):
  with members:
    - "scheduling and power allocation to optimize service and queue waiting times in cognitive radio uplinks"
    - "throughput optimization in multichannel cognitive radios with hard deadline constraints"
    - "optimal power cost management using stored energy in data centers"

Connected through hyperedge HE-3 (induced by source paper "delay optimal scheduling and power control for instantaneous interference limited crs"):
  with members:
    - "delay optimal joint scheduling and power control for cognitive radio uplinks"
    - "throughput optimization in multichannel cognitive radios with hard deadline constraints"

Connected through hyperedge HE-4 (induced by source paper "supervised machine learning for signals having rrc shaped pulses"):
  with members:
    - "separation of signals consisting of amplitude and instantaneous frequency rrc pulses using snr uniform training"
    - "throughput maximization in multi channel cognitive radio systems with delay constraints"

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)