human: Given a node-centered hypergraph: <hypergraph>, where nodes represent papers and hyperedges represent sets of papers co-cited by a source paper.

Details of the hypergraph:
Center node: "millimeter wave distance dependent large scale propagation measurements and path loss models for outdoor and indoor 5g systems"
  Abstract: This paper presents millimeter-wave propagation measurements for urban micro-cellular and indoor office scenarios at 28 GHz and 73 GHz, and investigates the corresponding path loss using five types of path loss models, the singlefrequency floating-intercept (FI) model, single-frequency closein (CI) free space reference distance model, multi-frequency alpha-beta-gamma (ABG) model, multi-frequency CI model, and multi-frequency CI model with a frequency-weighted path loss exponent (CIF), in both line-of-sight and non-line-of-sight environments. Results show that the CI and CIF models provide good estimation and exhibit stable behavior over frequencies and distances, with a solid physical basis and less computational complexity when compared with the FI and ABG models. Furthermore, path loss in outdoor scenarios shows little dependence on frequency beyond the first meter of free space propagation, whereas path loss tends to increase with frequency in addition to the increased free space path loss in indoor environments. Therefore, the CI model is suitable for outdoor environments over multiple frequencies, while the CIF model is more appropriate for indoor modeling. This work shows that both the CI and CIF models use fewer parameters and offer more convenient closedform expressions suitable for analysis, without compromising model accuracy when compared to current 3GPP and WINNER path loss models.

Connected through hyperedge HE-1 (induced by source paper "path loss and directional gain measurements at 28 ghz for non line of sight coverage of indoors with corridors"):
  with members:
    - "small scale local area and transitional millimeter wave propagation for 5g communications"
    - "overview of millimeter wave communications for fifth generation 5g wireless networks with a focus on propagation models"
    - "indoor office plan environment and layout based mmwave path loss models for 28 ghz and 73 ghz"

Connected through hyperedge HE-2 (induced by source paper "map assisted millimeter wave localization for accurate position location"):
  with members:
    - "leveraging mmwave imaging and communications for simultaneous localization and mapping"
    - "position locationing for millimeter wave systems"
    - "accurate and robust indoor localization systems using ultra wideband signals"

Connected through hyperedge HE-3 (induced by source paper "position locationing for millimeter wave systems"):
  with members:
    - "propagation measurement system and approach at 140 ghz moving to 6g and above 100 ghz"
    - "base station diversity propagation measurements at 73 ghz millimeter wave for 5g coordinated multipoint comp analysis"
    - "initial access in 5g mmwave cellular networks"
    - "28 ghz and 73 ghz millimeter wave indoor propagation measurements and path loss models"

Connected through hyperedge HE-4 (induced by source paper "deep q learning for self organizing networks fault management and radio performance improvement"):
  with members:
    - "partially blind handovers for mmwave new radio aided by sub 6 ghz lte signaling"
    - "adam a method for stochastic optimization"
    - "playing atari with deep reinforcement learning"

Connected through hyperedge HE-5 (induced by source paper "partially blind handovers for mmwave new radio aided by sub 6 ghz lte signaling"):
  with members:
    - "xgboost a scalable tree boosting system"

Connected through hyperedge HE-6 (induced by source paper "overview of millimeter wave communications for fifth generation 5g wireless networks with a focus on propagation models"):
  with members:
    - "indoor office wideband penetration loss measurements at 73 ghz"
    - "study on 3gpp rural macrocell path loss models for millimeter wave wireless communications"
    - "investigation and comparison of 3gpp and nyusim channel models for 5g wireless communications"
    - "millimeter wave small scale spatial statistics in an urban microcell scenario"
    - "a novel millimeter wave channel simulator and applications for 5g wireless communications"
    - "small scale local area and transitional millimeter wave propagation for 5g communications"
    - "5g 3gpp like channel models for outdoor urban microcellular and macrocellular environments"
    - "millimeter wave human blockage at 73 ghz with a simple double knife edge diffraction model and extension for directional antennas"

Connected through hyperedge HE-7 (induced by source paper "modeling and design of millimeter wave networks for highway vehicular communication"):
  with members:
    - "millimeter wave vehicular communication to support massive automotive sensing"
    - "wireless vehicular networks in emergencies a single frequency network approach"
    - "analysis and optimization of sparse random linear network coding for reliable multicast services"
    - "stochastic geometry modeling and analysis of multi tier millimeter wave cellular networks"
    - "millimeter wave cellular networks a mac layer perspective"
    - "tractable model for rate in self backhauled millimeter wave cellular networks"
    - "coverage and rate analysis for millimeter wave cellular networks"
    - "what will 5g be"

Connected through hyperedge HE-8 (induced by source paper "path loss beamforming gain and time dynamics measurements at 28 ghz for 90 indoor coverage"):
  with members:
    - "overview of millimeter wave communications for fifth generation 5g wireless networks with a focus on propagation models"
    - "indoor 5g 3gpp like channel models for office and shopping mall environments"

Question: Please tell me which class the center node 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)