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: "multiuser diversity gain in cognitive networks"
  Abstract: Dynamic allocation of resources to the \emph{best} link in large multiuser networks offers considerable improvement in spectral efficiency. This gain, often referred to as \emph{multiuser diversity gain}, can be cast as double-logarithmic growth of the network throughput with the number of users. In this paper we consider large cognitive networks granted concurrent spectrum access with license-holding users. The primary network affords to share its under-utilized spectrum bands with the secondary users. We assess the optimal multiuser diversity gain in the cognitive networks by quantifying how the sum-rate throughput of the network scales with the number of secondary users. For this purpose we look at the optimal pairing of spectrum bands and secondary users, which is supervised by a central entity fully aware of the instantaneous channel conditions, and show that the throughput of the cognitive network scales double-logarithmically with the number of secondary users ($N$) and linearly with the number of available spectrum bands ($M$), i.e., $M\log\log N$. We then propose a \emph{distributed} spectrum allocation scheme, which does not necessitate a central controller or any information exchange between different secondary users and still obeys the optimal throughput scaling law. This scheme requires that \emph{some} secondary transmitter-receiver pairs exchange $\log M$ information bits among themselves. We also show that the aggregate amount of information exchange between secondary transmitter-receiver pairs is {\em asymptotically} equal to $M\log M$. Finally, we show that our distributed scheme guarantees fairness among the secondary users, meaning that they are equally likely to get access to an available spectrum band.

Connected through hyperedge HE-1 (induced by source paper "fundamental limits of cdf based scheduling throughput fairness and feedback overhead"):
  with members:
    - "opportunistic interference mitigation achieves optimal degrees of freedom in wireless multi cell uplink networks"

Connected through hyperedge HE-2 (induced by source paper "distributed cognitive multiple access networks power control scheduling and multiuser diversity"):
  with members:
    - "multiuser diversity for the cognitive uplink with generalized fading and reduced primary s cooperation"
    - "power control and multiuser diversity for the distributed cognitive uplink"
    - "on ergodic sum capacity of fading cognitive multiple access and broadcast channels"
    - "investigation on multiuser diversity in spectrum sharing based cognitive radio networks"

Connected through hyperedge HE-3 (induced by source paper "cognitive radio with random number of secondary number of users"):
  with members:
    - "multi user diversity with random number of users"
    - "investigation on multiuser diversity in spectrum sharing based cognitive radio networks"

Connected through hyperedge HE-4 (induced by source paper "multiuser diversity for the cognitive uplink with generalized fading and reduced primary s cooperation"):
  with members:
    - "on ergodic sum capacity of fading cognitive multiple access and broadcast channels"
    - "optimal power allocation for fading channels in cognitive radio networks ergodic capacity and outage capacity"
    - "investigation on multiuser diversity in spectrum sharing based cognitive radio networks"

Connected through hyperedge HE-5 (induced by source paper "power control and multiuser diversity for the distributed cognitive uplink"):
  with members:
    - "capacity limits of multiuser multiantenna cognitive networks"
    - "on ergodic sum capacity of fading cognitive multiple access and broadcast channels"
    - "investigation on multiuser diversity in spectrum sharing based cognitive radio networks"

Connected through hyperedge HE-6 (induced by source paper "asymptotically optimal feedback protocol design for cognitive multiple access channels"):
  with members:
    - "on ergodic sum capacity of fading cognitive multiple access and broadcast channels"
    - "optimal power allocation for fading channels in cognitive radio networks ergodic capacity and outage capacity"
    - "investigation on multiuser diversity in spectrum sharing based cognitive radio networks"

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)