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: "a unified framework for the ergodic capacity of spectrum sharing cognitive radio systems"
  Abstract: We consider a spectrum sharing communication scenario in which a primary and a secondary users are communicating, simultaneously, with their respective destinations using the same frequency carrier. Both optimal power profile and ergodic capacity are derived for fading channels, under an average transmit power and an instantaneous interference outage constraints. Unlike previous studies, we assume that the secondary user has a noisy version of the cross link and the secondary link Channel State Information (CSI). After deriving the capacity in this case, we provide an ergodic capacity generalization, through a unified expression, that encompasses several previously studied spectrum sharing settings. In addition, we provide an asymptotic capacity analysis at high and low signal-to-noise ratio (SNR). Numerical results, applied for independent Rayleigh fading channels, show that at low SNR regime, only the secondary channel estimation matters with no effect of the cross link on the capacity; whereas at high SNR regime, the capacity is rather driven by the cross link CSI. Furthermore, a practical on-off power allocation scheme is proposed and is shown, through numerical results, to achieve the full capacity at high and low SNR regimes and suboptimal rates in the medium SNR regime.

Connected through hyperedge HE-1 (induced by source paper "on the performance analysis of underlay cognitive radio systems a deployment perspective"):
  with members:
    - "sensing throughput tradeoff for interweave cognitive radio system a deployment centric viewpoint"
    - "estimation throughput tradeoff for underlay cognitive radio systems"
    - "the effects of limited channel knowledge on cognitive radio system capacity"
    - "optimal power allocation for fading channels in cognitive radio networks ergodic capacity and outage capacity"
    - "channel capacity limits of cognitive radio in asymmetric fading environments"

Connected through hyperedge HE-2 (induced by source paper "energy efficient power allocation in cognitive radio systems with imperfect spectrum sensing"):
  with members:
    - "wireless networks with rf energy harvesting a contemporary survey"
    - "energy efficient power adaptation for cognitive radio systems under imperfect channel sensing"
    - "optimal power allocation for fading channels in cognitive radio networks ergodic capacity and outage capacity"

Connected through hyperedge HE-3 (induced by source paper "throughput of cognitive radio systems with finite blocklength codes"):
  with members:
    - "the effects of limited channel knowledge on cognitive radio system capacity"
    - "performance analysis of cognitive radio systems under qos constraints and channel uncertainty"
    - "throughput analysis of buffer constrained wireless systems in the finite blocklength regime"
    - "optimal power allocation for fading channels in cognitive radio networks ergodic capacity and outage capacity"

Connected through hyperedge HE-4 (induced by source paper "error rate analysis of cognitive radio transmissions with imperfect channel sensing"):
  with members:
    - "the effects of limited channel knowledge on cognitive radio system capacity"
    - "optimal power allocation for fading channels in cognitive radio networks ergodic capacity and outage capacity"

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)