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: "capacity limits of multiuser multiantenna cognitive networks"
  Abstract: Unlike point-to-point cognitive radio, where the constraint imposed by the primary rigidly curbs the secondary throughput, multiple secondary users have the potential to more efficiently harvest the spectrum and share it among themselves. This paper analyzes the sum throughput of a multiuser cognitive radio system with multi-antenna base stations, either in the uplink or downlink mode. The primary and secondary have $N$ and $n$ users, respectively, and their base stations have $M$ and $m$ antennas, respectively. We show that an uplink secondary throughput grows with $\frac{m}{N +1}\log n$ if the primary is a downlink system, and grows with $\frac{m}{M +1}\log n$ if the primary is an uplink system. These growth rates are shown to be optimal and can be obtained with a simple threshold-based user selection rule. Furthermore, we show that the secondary throughput can grow proportional to $\log n$ while simultaneously pushing the interference on the primary down to zero, asymptotically. Furthermore, we show that a downlink secondary throughput grows with $m\log \log n$ in the presence of either an uplink or downlink primary system. In addition, the interference on the primary can be made to go to zero asymptotically while the secondary throughput increases proportionally to $\log \log n$. Thus, unlike the point-to-point case, multiuser cognitive radios can achieve non-trivial sum throughput despite stringent primary interference constraints.

Connected through hyperedge HE-1 (induced by source paper "spectrum sharing with distributed relay selection and clustering"):
  with members:
    - "interference channel with an out of band relay"
    - "on ergodic sum capacity of fading cognitive multiple access and broadcast channels"
    - "on peak versus average interference power constraints for protecting primary users in cognitive radio networks"
    - "hierarchical cooperation achieves optimal capacity scaling in ad hoc networks"
    - "cooperative relay broadcast channels"

Connected through hyperedge HE-2 (induced by source paper "power control and multiuser diversity for the distributed cognitive uplink"):
  with members:
    - "multiuser diversity gain in 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"

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)