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 "stochastic geometric coverage analysis in mmwave cellular networks with realistic channel and antenna radiation models"):
  Abstract: Millimeter-wave (mmWave) bands will play an important role in 5G wireless systems. The system performance can be assessed by using models from stochastic geometry that cater for the directivity in the desired signal transmissions as well as the interference, and by calculating the signal-to-interference-plus-noise ratio (SINR) coverage. Nonetheless, the correctness of the existing coverage expressions derived through stochastic geometry may be questioned, as it is not clear whether they capture the impact of the detailed mmWave channel and antenna features. In this study, we propose an SINR coverage analysis framework that includes realistic channel model (from NYU) and antenna element radiation patterns (with isotropic/directional radiation). We first introduce two parameters, aligned gain and misaligned gain, associated with the desired signal beam and the interfering signal beam, respectively. We provide the distributions of the aligned and misaligned gains through curve fitting of system-simulation results. The distribution of these gains is used to determine the distribution of the SINR. We compare the obtained analytical SINR coverage with the corresponding SINR coverage calculated via system-level simulations. The results show that both aligned and misaligned gains can be modeled as exponential-logarithmically distributed random variables with the highest accuracy, and can further be approximated as exponentially distributed random variables with reasonable accuracy. These approximations are thus expected to be useful to evaluate the system performance under ultra-reliable and low-latency communication (URLLC) and evolved mobile broadband (eMBB) scenarios, respectively.

Includes members:
  Member "study of realistic antenna patterns in 5g mmwave cellular scenarios":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "machine learning aided design of thinned antenna arrays for optimized network level performance")
  Member "ultra reliable and low latency wireless communication tail risk and scale":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "optimized age of information tail for ultra reliable low latency communications in vehicular networks")
  Member "coverage and connectivity analysis of millimeter wave vehicular networks":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "coverage analysis of uavs in millimeter wave networks a stochastic geometry approach")
  Member "millimeter wave interference avoidance via building aware associations":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "sense and predict harnessing spatial interference correlation for cognitive radio networks")
  Member "modeling and analyzing millimeter wave cellular systems":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "coverage analysis of uavs in millimeter wave networks a stochastic geometry approach")
  Member "coverage analysis for millimeter wave networks the impact of directional antenna arrays":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "analyzing the tradeoffs in using millimeter wave directional links for high data rate tactile internet applications")
  Member "stochastic geometric coverage analysis in mmwave cellular networks with a realistic channel model":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "nuts and bolts of a realistic stochastic geometric analysis of mmwave hetnets hardware impairments and channel aging")
  Member "correction factor for analysis of mimo wireless networks with highly directional beamforming":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "joint path selection and rate allocation framework for 5g self backhauled mm wave 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)