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: "distributed mac protocol design for full duplex cognitive radio networks"
  Abstract: In this paper, we consider the Medium Access Control (MAC) protocol design for full-duplex cognitive radio networks (FDCRNs). Our design exploits the fact that full-duplex (FD) secondary users (SUs) can perform spectrum sensing and access simultaneously, which enable them to detect the primary users' (PUs) activity during transmission. The developed FD MAC protocol employs the standard backoff mechanism as in the 802.11 MAC protocol. However, we propose to adopt the frame fragmentation during the data transmission phase for timely detection of active PUs where each data packet is divided into multiple fragments and the active SU makes sensing detection at the end of each data fragment. Then, we develop a mathematical model to analyze the throughput performance of the proposed FD MAC protocol. Furthermore, we propose an algorithm to configure the MAC protocol so that efficient self-interference management and sensing overhead control can be achieved. Finally, numerical results are presented to evaluate the performance of our design and demonstrate the throughput enhancement compared to the existing half-duplex (HD) cognitive MAC protocol.

Connected through hyperedge HE-1 (induced by source paper "power allocation for full duplex relay selection in underlay cognitive radio networks coherent versus non coherent scenarios"):
  with members:
    - "power control and relay selection in full duplex cognitive relay networks coherent versus non coherent scenarios"
    - "passive self interference suppression for full duplex infrastructure nodes"
    - "widely linear digital self interference cancellation in direct conversion full duplex transceiver"
    - "in band full duplex wireless challenges and opportunities"
    - "experiment driven characterization of full duplex wireless systems"
    - "distributed mac protocol for cognitive radio networks design analysis and optimization"
    - "full duplex bidirectional mimo achievable rates under limited dynamic range"

Connected through hyperedge HE-2 (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"
    - "full duplex wireless communications for cognitive radio networks"

Connected through hyperedge HE-3 (induced by source paper "power control and relay selection in full duplex cognitive relay networks coherent versus non coherent scenarios"):
  with members:
    - "design and optimal configuration of full duplex mac protocol for cognitive radio networks considering self interference"
    - "distributed mac protocol for cognitive radio networks design analysis and optimization"

Connected through hyperedge HE-4 (induced by source paper "design and optimal configuration of full duplex mac protocol for cognitive radio networks considering self interference"):
  with members:
    - "passive self interference suppression for full duplex infrastructure nodes"
    - "joint cooperative spectrum sensing and mac protocol design for multi channel cognitive radio networks"
    - "widely linear digital self interference cancellation in direct conversion full duplex transceiver"
    - "design and characterization of a full duplex multiantenna system for wifi networks"
    - "full duplex cooperative cognitive radio with transmit imperfections"
    - "in band full duplex wireless challenges and opportunities"
    - "channel assignment with access contention resolution for cognitive radio networks"
    - "experiment driven characterization of full duplex wireless systems"

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)