human: Given a hyperedge-centered hypergraph: <hypergraph>, where the center hyperedge is induced by one source paper and its member nodes are the cited papers.

Details of the hypergraph:
Center hyperedge (induced by source paper "device to device communication in cellular networks"):
  Abstract: A constant need to increase the network capacity for meeting the growing demands of the subscribers has led to the evolution of cellular communication networks from the first generation (1G) to the fifth generation (5G). There will be billions of connected devices in the near future. Such a large number of connections are expected to be heterogeneous in nature, demanding higher data rates, lesser delays, enhanced system capacity and superior throughput. The available spectrum resources are limited and need to be flexibly used by the mobile network operators (MNOs) to cope with the rising demands. An emerging facilitator of the upcoming high data rate demanding next generation networks (NGNs) is device-to-device (D2D) communication. An extensive survey on device-to-device (D2D) communication has been presented in this paper, including the plus points it offers; the key open issues associated with it like peer discovery, resource allocation etc, demanding special attention of the research community; some of its integrant technologies like millimeter wave D2D (mmWave), ultra dense networks (UDNs), cognitive D2D, handover procedure in D2D and its numerous use cases. Architecture is suggested aiming to fulfill all the subscriber demands in an optimal manner. The Appendix mentions some ongoing standardization activities and research projects of D2D communication. Proposed architecture for resource allocation in device-to-device (D2D) communication. In order to meet the rising subscriber demands and provide them satisfactory services, D2D communication is being looked upon as an emerging technology of the next generation networks. For optimal sharing of resources between the D2D users and cellular users in the cellular networks, a sectored antenna is used at the base station, dividing the entire coverage area into three sectors of 120° each. This supports reduction in interference between the two types of users thereby, improving system performance.Display Omitted Roadmap of D2D communication through the generations of wireless communication.Outline of D2D communication; supporting architectures and use cases.Integrant features (like Ultra Dense networks, millimeter wave communication, cooperative communication, network coding etc.) to enhance utility of D2D communication in the next generation networks.Key open challenges and some important algorithms to overcome them.Proposed architecture for optimal resource allocation and throughput maximization.

Includes members:
  Member "energy efficient joint resource allocation and power control for d2d communications":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "learning to branch accelerating resource allocation in wireless networks")
  Member "exploiting device to device communications to enhance spatial reuse for popular content downloading in directional mmwave small cells":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "device to device communications enabled multicast scheduling with the multi level codebook in mmwave small cells")
  Member "a survey on device to device communication in cellular networks":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "simultaneous energy harvesting and information transmission in a mimo full duplex system a machine learning based design")
  Member "cognitive and energy harvesting based d2d communication in cellular networks stochastic geometry modeling and analysis":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "analysis of d2d communication with rf energy harvesting and interference management")
  Member "low rate machine type communication via wireless device to device d2d links":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "applying device to device communication to enhance iot services")
  Member "base station assisted device to device communications for high throughput wireless video networks":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "degrees of freedom of cache aided wireless cellular networks")
  Member "power control for d2d underlaid cellular networks modeling algorithms and analysis":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "analysis of d2d communication with rf energy harvesting and interference management")

Question: Please tell me which class the source paper 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)