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 cognitive radio a new design paradigm for enhancing spectrum usage"
  Abstract: With the rapid growth of demand for ever-increasing data rate, spectrum resources have become more and more scarce. As a promising technique to increase the efficiency of the spectrum utilization, cognitive radio (CR) technique has the great potential to meet such a requirement by allowing un-licensed users to coexist in licensed bands. In conventional CR systems, the spectrum sensing is performed at the beginning of each time slot before the data transmission. This unfortunately results in two major problems: 1) transmission time reduction due to sensing, and 2) sensing accuracy impairment due to data transmission. To tackle these problems, in this paper we present a new design paradigm for future CR by exploring the full-duplex (FD) techniques to achieve the simultaneous spectrum sensing and data transmission. With FD radios equipped at the secondary users (SUs), SUs can simultaneously sense and access the vacant spectrum, and thus, significantly improve sensing performances and meanwhile increase data transmission efficiency. The aim of this article is to transform the promising conceptual framework into the practical wireless network design by addressing a diverse set of challenges such as protocol design and theoretical analysis. Several application scenarios with FD enabled CR are elaborated, and key open research directions and novel algorithms in these systems are discussed.

Connected through hyperedge HE-1 (induced by source paper "opportunism in dynamic spectrum access for 5g a concept and its application to duplexing"):
  with members:
    - "sense and predict opportunistic mac based on spatial interference correlation for cognitive radio networks"
    - "compact full duplex mimo radios in d2d underlaid cellular networks from system design to prototype results"
    - "prototyping real time full duplex radios"

Connected through hyperedge HE-2 (induced by source paper "a non parametric multi stage learning framework for cognitive spectrum access in iot networks"):
  with members:
    - "multi armed bandit learning in iot networks learning helps even in non stationary settings"
    - "spectrum access in cognitive radio using a two stage reinforcement learning approach"

Connected through hyperedge HE-3 (induced by source paper "adaptive full duplex communications in cognitive radio networks"):
  with members:
    - "distributed mac protocol design for full duplex cognitive radio networks"
    - "full duplex wireless communications for cognitive radio networks"

Connected through hyperedge HE-4 (induced by source paper "sliding window spectrum sensing for full duplex cognitive radios with low access latency"):
  with members:
    - "baseband and rf hardware impairments in full duplex wireless systems experimental characterisation and suppression"
    - "in band full duplex wireless challenges and opportunities"
    - "exploiting self interference suppression for improved spectrum awareness efficiency in cognitive radio systems"

Connected through hyperedge HE-5 (induced by source paper "resource allocation in full duplex communications for future wireless networks"):
  with members:
    - "simultaneous bidirectional link selection in full duplex mimo systems"
    - "low complexity end to end performance optimization in mimo full duplex relay systems"

Connected through hyperedge HE-6 (induced by source paper "full duplex mac protocol design and analysis"):
  with members:
    - "listen and talk full duplex cognitive radio networks"
    - "pushing the limits of full duplex design and real time implementation"

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.NI(Networking and Internet Architecture)