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 "beam training and data transmission optimization in millimeter wave vehicular networks"):
  Abstract: Future vehicular communication networks call for new solutions to support their capacity demands, by leveraging the potential of the millimeter-wave (mm-wave) spectrum. Mobility, in particular, poses severe challenges in their design, and as such shall be accounted for. A key question in mm-wave vehicular networks is how to optimize the trade-off between directive Data Transmission (DT) and directional Beam Training (BT), which enables it. In this paper, learning tools are investigated to optimize this trade-off. In the proposed scenario, a Base Station (BS) uses BT to establish a mm-wave directive link towards a Mobile User (MU) moving along a road. To control the BT/DT trade-off, a Partially Observable (PO) Markov Decision Process (MDP) is formulated, where the system state corresponds to the position of the MU within the road link. The goal is to maximize the number of bits delivered by the BS to the MU over the communication session, under a power constraint. The resulting optimal policies reveal that adaptive BT/DT procedures significantly outperform common-sense heuristic schemes, and that specific mobility features, such as user position estimates, can be effectively used to enhance the overall system performance and optimize the available system resources.

Includes members:
  Member "optimal beam sweeping and communication in mobile millimeter wave networks":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "mobility and blockage aware communications in millimeter wave vehicular networks")
  Member "inverse multipath fingerprinting for millimeter wave v2i beam alignment":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "mobility and blockage aware communications in millimeter wave vehicular networks")
  Member "millimeter wave vehicular communication to support massive automotive sensing":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "mobility and blockage aware communications in millimeter wave vehicular networks")
  Member "initial access in 5g mmwave cellular networks":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "mobility and blockage aware communications in millimeter wave vehicular networks")
  Member "tracking mm wave channel dynamics fast beam training strategies under mobility":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "joint path selection and rate allocation framework for 5g self backhauled mm wave networks")
  Member "perseus randomized point based value iteration for pomdps":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "mobility and blockage aware communications in millimeter wave vehicular networks")
  Member "reinforcement learning a survey":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "online fast adaptation and knowledge accumulation a new approach to continual learning")

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)