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: "full duplex wireless communications for cognitive radio networks"
  Abstract: Abstract—As a key in cognitive radio networks (CRNs), dy-namic spectrum access needs to be carefully designed to minimizethe interference and delay to the primary (licensed) users. One ofthe main challenges in dynamic spectrum access is to determinewhen the secondary (unlicensed) users can use the spectrum.In particular, when the secondary user is using the spectrum,if the primary user becomes active to use the spectrum, it isusually hard for the secondary user to detect the primary userinstantaneously, thus causing unexpected interference and delayto primary users. The secondary user cannot detect the presenceof primary users instantaneously because the secondary useris unable to detect the spectrum at the same time while it istransmitting. To solve this problem, we propose the full duplexwireless communications scheme for CRNs. In particular, weemploy the Antennas Cancellation (AC), the RF InterferenceCancellation (RIC), and the Digital Interference Cancellation(DIC) techniques for secondary users so that the secondary usercan scan for active primary users while it is transmitting. Oncedetecting the presence of primary users, the secondary user willrelease the spectrum instantaneously to avoid the interferenceand delay to primary users. We analyze the packet loss rateof primary users in wireless full duplex CRNs, and comparethem with the packet loss rate of primary users in wireless halfduplex CRNs. Our analyses and simulations show that using ourdevelopped wireless full duplex CRNs, the packet loss rate ofprimary users can be signiﬁcantly decreased as compared wit hthat of primary users by using the half duplex CRNs.Index Terms—Cognitive radio networks (CRNs), full duplexCRNs, dynamic spectrum sensing, packet loss rate, interferencecontrol.

Connected through hyperedge HE-1 (induced by source paper "adaptive full duplex communications in cognitive radio networks"):
  with members:
    - "full duplex cognitive radio a new design paradigm for enhancing spectrum usage"
    - "distributed mac protocol design for full duplex cognitive radio networks"

Connected through hyperedge HE-2 (induced by source paper "in band full duplex wireless challenges and opportunities"):
  with members:
    - "cancellation of power amplifier induced nonlinear self interference in full duplex transceivers"
    - "passive self interference suppression for full duplex infrastructure nodes"
    - "advanced self interference cancellation and multiantenna techniques for full duplex radios"
    - "analysis of oscillator phase noise effects on self interference cancellation in full duplex ofdm radio transceivers"
    - "design and characterization of a full duplex multiantenna system for wifi networks"
    - "full duplex transceiver system calculations analysis of adc and linearity challenges"
    - "simultaneous transmission and reception algorithm design and system level performance"
    - "rate gain region and design tradeoffs for full duplex wireless communications"

Connected through hyperedge HE-3 (induced by source paper "rate gain region and design tradeoffs for full duplex wireless communications"):
  with members:
    - "design and characterization of a full duplex multiantenna system for wifi networks"
    - "experiment driven characterization of full duplex wireless systems"
    - "full duplex bidirectional mimo achievable rates under limited dynamic range"

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)