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 "performance of dynamic and static tdd in self backhauled millimeter wave cellular networks"):
  Abstract: Initial deployments of millimeter wave (mm-wave) cellular networks are likely to be enabled with self-backhauling. In this paper, we propose a random spatial model to analyze uplink (UL) and downlink (DL) signal to interference plus noise ratio distribution and mean rates corresponding to different access-backhaul and UL–DL resource allocation schemes in a self-backhauled mm-wave cellular network with Poisson point process (PPP) deployment of users and base stations (BSs). In particular, we focus on heuristic implementations of static and dynamic time division duplexing (TDD) for access links with synchronized or unsynchronized access-backhaul (SAB or UAB) time splits. We propose PPP approximations to characterize the distribution of the new types of interference encountered with dynamic TDD and UAB. These schemes offer better resource utilization than static TDD and SAB, however, potentially higher interference makes their choice non-trivial and the offered gains sensitive to different network parameters, including UL/DL traffic asymmetry, user load per BS or number of slave BSs per master BS. One can harness notable gains from UAB and/or dynamic TDD only if backhaul links are designed to have much larger throughput than the access links.

Includes members:
  Member "modeling and analyzing millimeter wave cellular systems":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "coverage analysis of uavs in millimeter wave networks a stochastic geometry approach")
  Member "modeling and analysis of cellular networks using stochastic geometry a tutorial":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "area spectral efficiency and sinr scaling laws in multi antenna cellular networks")
  Member "joint backhaul access analysis of full duplex self backhauling heterogeneous networks":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "millimeter wave integrated access and backhaul in 5g performance analysis and design insights")
  Member "downlink and uplink cell association with traditional macrocells and millimeter wave small cells":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "intelligent uav base station selection in urban environments a supervised learning approach")
  Member "analysis of massive mimo enabled downlink wireless backhauling for full duplex small cells":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "millimeter wave integrated access and backhaul in 5g performance analysis and design insights")
  Member "user point processes in cellular networks":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "scheduling policies for federated learning in wireless networks")
  Member "the intensity matching approach a tractable stochastic geometry approximation to system level analysis of cellular networks":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "smart radio environments empowered by ai reconfigurable meta surfaces an idea whose time has come")
  Member "modeling and performance analysis of clustered device to device networks":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "optimizing joint probabilistic caching and channel access for clustered d2d 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.IT(Information Theory)