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 "tractable model for rate in self backhauled millimeter wave cellular networks"):
  Abstract: Millimeter wave (mmW) cellular systems will require high gain directional antennas and dense base station (BS) deployments to overcome high near field path loss and poor diffraction. As a desirable side effect, high gain antennas provide interference isolation, providing an opportunity to incorporate self-backhauling--BSs backhauling among themselves in a mesh architecture without significant loss in throughput--to enable the requisite large BS densities. The use of directional antennas and resource sharing between access and backhaul links leads to coverage and rate trends that differ significantly from conventional microwave ($\mu$W) cellular systems. In this paper, we propose a general and tractable mmW cellular model capturing these key trends and characterize the associated rate distribution. The developed model and analysis is validated using actual building locations from dense urban settings and empirically-derived path loss models. The analysis shows that in sharp contrast to the interference limited nature of $\mu$W cellular networks, the spectral efficiency of mmW networks (besides total rate) also increases with BS density particularly at the cell edge. Increasing the system bandwidth, although boosting median and peak rates, does not significantly influence the cell edge rate. With self-backhauling, different combinations of the wired backhaul fraction (i.e. the faction of BSs with a wired connection) and BS density are shown to guarantee the same median rate (QoS).

Includes members:
  Member "asymptotic deployment gain a simple approach to characterize the sinr distribution in general cellular networks":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "smart radio environments empowered by ai reconfigurable meta surfaces an idea whose time has come")
  Member "on the joint impact of beamwidth and orientation error on throughput in directional wireless poisson networks":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "analyzing the tradeoffs in using millimeter wave directional links for high data rate tactile internet applications")
  Member "an overview of load balancing in hetnets old myths and open problems":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "a hybrid model based and data driven approach to spectrum sharing in mmwave cellular networks")
  Member "coverage and rate analysis for millimeter wave cellular networks":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "optimizing information freshness in wireless networks a stochastic geometry approach")
  Member "what will 5g be":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "5g network slicing using sdn and nfv a survey of taxonomy architectures and future challenges")
  Member "millimeter wave cellular wireless networks potentials and challenges":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "wirelessly powered sensor networks power allocation for channel estimation and energy beamforming")
  Member "on association cells in random heterogeneous networks":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "millimeter wave integrated access and backhaul in 5g performance analysis and design insights")
  Member "millimeter wave channel modeling and cellular capacity evaluation":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "coverage analysis of uavs in millimeter wave networks a stochastic geometry approach")

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)