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 "ray of arrival passing for indirect beam training in cooperative millimeter wave mimo networks"):
  Abstract: This paper is concerned with the channel estimation problem in multi-cell Millimeter (mmWave) wireless systems. We develop a novel Ray-of-Arrival Passing for Indirect (RAPID) Beam Training framework, in which a network consisting of multiple BS are able to work cooperatively to estimate jointly the UE channels. To achieve this aim, we consider the spatial geometry of the mmWave environment and transform conventional angular domain beamforming concepts into the more euclidean, Ray-based domain. Leveraging this model, we then consider the conditional probabilities that pilot signals are received in each direction, given that the deployment of each BS is known to the network. Simulation results show that RAPID is able to improve the average estimation of the network and significantly increase the rate of poorer quality links. Furthermore, we also show that, when a coverage rate threshold is considered, RAPID is able to improve greatly the probability that multiple link options will be available to a user at any given time.

Includes members:
  Member "fast channel estimation for millimetre wave wireless systems using overlapped beam patterns":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "compressed sensing channel estimation for ofdm with non gaussian multipath gains")
  Member "improved handover through dual connectivity in 5g mmwave mobile networks":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "wireless edge computing with latency and reliability guarantees")
  Member "millimeter wave mimo channel estimation using overlapped beam patterns and rate adaptation":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "secure communication for spatially sparse millimeter wave massive mimo channels via hybrid precoding")
  Member "race a rate adaptive channel estimation approach for millimeter wave mimo systems":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "beam on graph simultaneous channel estimation for mmwave mimo systems with multiple users")
  Member "hierarchical codebook design for beamforming training in millimeter wave communication":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "edge cache assisted secure low latency millimeter wave transmission")
  Member "initial access in 5g mmwave cellular networks":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "mobility and blockage aware communications in millimeter wave vehicular networks")
  Member "multi connectivity in 5g mmwave cellular networks":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "wireless edge computing with latency and reliability guarantees")
  Member "compressed sensing based multi user millimeter wave systems how many measurements are needed":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "deep learning for massive mimo channel state acquisition and feedback")

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)