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: "resource management for device to device underlay communication"
  Abstract: Device-to-Device (D2D) communication will become a key feature supported by next generation cellular networks, a topic of enormous importance to modern communication. Currently, D2D serves as an underlay to the cellular network as a means to increase spectral efficiency. Although D2D communication brings large benefits in terms of system capacity, it also causes interference as well as increased computation complexity to cellular networks as a result of spectrum sharing. Thus, efficient resource management must be performed to guarantee a target performance level of cellular communication. This brief presents the state-of-the-art research on resource management for D2D communication underlaying cellular networks. Those who work with D2D communication will use this books information to help ensure their work is as efficient as possible. Along with the survey of existing work, this book also includes the fundamental theories, key techniques, and applications.

Connected through hyperedge HE-1 (induced by source paper "underlay drone cell for temporary events impact of drone height and aerial channel environments"):
  with members:
    - "uav aided offloading for cellular hotspot"
    - "coverage and rate analysis for unmanned aerial vehicle base stations with los nlos propagation"
    - "uplink coverage performance of an underlay drone cell for temporary events"
    - "a tutorial on uavs for wireless networks applications challenges and open problems"
    - "dronecells improving 5g spectral efficiency using drone mounted flying base stations"
    - "joint trajectory and communication design for multi uav enabled wireless networks"
    - "coverage analysis for low altitude uav networks in urban environments"
    - "uplink performance analysis of a drone cell in a random field of ground interferers"

Connected through hyperedge HE-2 (induced by source paper "spatial motifs for device to device network analysis dna in cellular networks"):
  with members:
    - "spectral and energy efficiency of uplink d2d underlaid massive mimo cellular networks"
    - "fundamentals of cluster centric content placement in cache enabled device to device networks"
    - "modeling and performance analysis of clustered device to device networks"
    - "unmanned aerial vehicle with underlaid device to device communications performance and tradeoffs"
    - "context aware small cell networks how social metrics improve wireless resource allocation"
    - "a survey on device to device communication in cellular networks"
    - "cognitive and energy harvesting based d2d communication in cellular networks stochastic geometry modeling and analysis"
    - "modeling analysis and optimization of multicast device to device transmissions"

Connected through hyperedge HE-3 (induced by source paper "sinr threshold scheduling with binary power control for d2d networks"):
  with members:
    - "optimality of treating interference as noise a combinatorial perspective"
    - "power control for d2d underlaid cellular networks modeling algorithms and analysis"
    - "wireless network information flow a deterministic approach"

Connected through hyperedge HE-4 (induced by source paper "multi cell device to device communications a spectrum sharing and densification study"):
  with members:
    - "are we approaching the fundamental limits of wireless network densification"
    - "a survey on device to device communication in cellular networks"

Connected through hyperedge HE-5 (induced by source paper "decentralized opportunistic access for d2d underlaid cellular networks"):
  with members:
    - "the meta distribution of the sir for cellular networks with power control"
    - "user point processes in cellular networks"
    - "poisson hole process theory and applications to wireless networks"
    - "mode selection resource allocation and power control for d2d enabled two tier cellular network"
    - "d2d enhanced heterogeneous cellular networks with dynamic tdd"
    - "an analytical framework for device to device communication in cellular networks"
    - "a survey on device to device communication in cellular networks"
    - "on stochastic geometry modeling of cellular uplink transmission with truncated channel inversion power control"

Connected through hyperedge HE-6 (induced by source paper "optimal qos aware channel assignment in d2d communications with partial csi"):
  with members:
    - "qos aware joint mode selection and channel assignment for d2d communications"
    - "hybrid centralized distributed resource allocation for device to device communication underlaying cellular networks"
    - "a survey on device to device communication in cellular networks"
    - "spectrum sharing for device to device communication in cellular networks"
    - "distributed resource allocation in device to device enhanced cellular networks"
    - "what will 5g be"
    - "emerging technologies and research challenges for 5g wireless networks"
    - "five disruptive technology directions for 5g"

Connected through hyperedge HE-7 (induced by source paper "dynamic clustering and user association in wireless small cell networks with social considerations"):
  with members:
    - "a survey on device to device communication in cellular networks"
    - "indian buffet game with negative network externality and non bayesian social learning"
    - "five disruptive technology directions for 5g"
    - "enhanced intercell interference coordination challenges in heterogeneous networks"
    - "peer effects and stability in matching markets"
    - "a tutorial on spectral clustering"

Connected through hyperedge HE-8 (induced by source paper "radio resource allocation for device to device underlay communication using hypergraph theory"):
  with members:
    - "learning based constraint satisfaction with sensing restrictions"

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.GT(Computer Science and Game Theory)