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 "d2d enhanced heterogeneous cellular networks with dynamic tdd"):
  Abstract: Over the last decade, the growing amount of uplink (UL) and downlink (DL) mobile data traffic has been characterized by substantial asymmetry and time variations. Dynamic time-division duplex (TDD) has the capability to accommodate to the traffic asymmetry by adapting the UL/DL configuration to the current traffic demands. In this work, we study a two-tier heterogeneous cellular network (HCN) where the macro tier and small cell tier operate according to a dynamic TDD scheme on orthogonal frequency bands. To offload the network infrastructure, mobile users in proximity can engage in device-to-device (D2D) communications, whose activity is determined by a carrier sensing multiple access (CSMA) scheme to protect the ongoing infrastructure-based and D2D transmissions. We present an analytical framework for evaluating the network performance in terms of  load-aware  coverage probability and network throughput. The proposed framework allows quantification of the effect on the coverage probability of the most important TDD system parameters, such as the UL/DL configuration, the base station density, and the bias factor. In addition, we evaluate how the bandwidth partition and the D2D network access scheme affect the total network throughput. Through the study of the tradeoff between coverage probability and D2D user activity, we provide guidelines for the optimal design of D2D network access.

Includes members:
  Member "spectrum sharing for device to device communication in cellular networks":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "sense and predict harnessing spatial interference correlation for cognitive radio networks")
  Member "dynamic uplink downlink optimization in tdd based small cell networks":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "dynamic tdd interference analysis in macro cell and small cell deployments")
  Member "successive interference cancellation in heterogeneous cellular networks":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "cooperative caching and transmission design in cluster centric small cell networks")
  Member "resource optimization in device to device cellular systems using time frequency hopping":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "interference prediction in wireless networks stochastic geometry meets recursive filtering")
  Member "efficiency resource allocation for device to device underlay communication systems a reverse iterative combinatorial auction based approach":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "sub channel allocation for device to device underlaying full duplex mmwave small cells using coalition formation games")
  Member "offloading in heterogeneous networks modeling analysis and design insights":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "smart radio environments empowered by ai reconfigurable meta surfaces an idea whose time has come")
  Member "analytical modeling of uplink cellular networks":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "dynamic tdd interference analysis in macro cell and small cell deployments")
  Member "heterogeneous cellular networks with flexible cell association a comprehensive downlink sinr analysis":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "stochastic geometry analysis of sojourn time in multi tier cellular networks")

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)