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 "interleaved training and training based transmission design for hybrid massive antenna downlink"):
  Abstract: In this paper, we study the beam-based training design jointly with the transmission design for hybrid massive antenna single-user (SU) and multiple-user (MU) systems where outage probability is adopted as the performance measure. For SU systems, we propose an interleaved training design to concatenate the feedback and training procedures, thus making the training length adaptive to the channel realization. Exact analytical expressions are derived for the average training length and the outage probability of the proposed interleaved training. For MU systems, we propose a joint design for the beam-based interleaved training, beam assignment, and MU data transmissions. Two solutions for the beam assignment are provided with different complexity-performance tradeoff. Analytical results and simulations show that for both SU and MU systems, the proposed joint training and transmission designs achieve the same outage performance as the traditional full-training scheme but with significant saving in the training overhead.

Includes members:
  Member "millimeter wave beam alignment large deviations analysis and design insights":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "analyzing the tradeoffs in using millimeter wave directional links for high data rate tactile internet applications")
  Member "codebook based hybrid precoding for millimeter wave multiuser systems":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "hybrid precoder design for cache enabled millimeter wave radio access networks")
  Member "performance scaling law for multi cell multi user massive mimo":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "performance analysis for massive mimo downlink with low complexity approximate zero forcing precoding")
  Member "an overview of signal processing techniques for millimeter wave mimo systems":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "energy efficient hybrid precoding design for integrated multicast unicast millimeter wave communications with swipt")
  Member "hybrid digital and analog beamforming design for large scale antenna arrays":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "beamforming design for large scale antenna arrays using deep learning")
  Member "beam searching and transmission scheduling in millimeter wave communications":
    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 "limited feedback hybrid precoding for multi user millimeter wave systems":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "energy efficient hybrid precoding design for integrated multicast unicast millimeter wave communications with swipt")
  Member "turbo like beamforming based on tabu search algorithm for millimeter wave massive mimo systems":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "non uniform quantization codebook based hybrid precoding to reduce feedback overhead in millimeter wave mimo systems")

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)