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 "multiuser mimo achievable rates with downlink training and channel state feedback"):
  Abstract: We consider a MIMO fading broadcast channel and compute achievable ergodic rates when channel state information is acquired at the receivers via downlink training and it is provided to the transmitter by channel state feedback. Unquantized (analog) and quantized (digital) channel state feedback schemes are analyzed and compared under various assumptions. Digital feedback is shown to be potentially superior when the feedback channel uses per channel state coefficient is larger than 1. Also, we show that by proper design of the digital feedback link, errors in the feedback have a minor effect even if simple uncoded modulation is used on the feedback channel. We discuss first the case of an unfaded AWGN feedback channel with orthogonal access and then the case of fading MIMO multi-access (MIMO-MAC). We show that by exploiting the MIMO-MAC nature of the uplink channel, a much better scaling of the feedback channel resource with the number of base station antennas can be achieved. Finally, for the case of delayed feedback, we show that in the realistic case where the fading process has (normalized) maximum Doppler frequency shift 0 < F < 1/2, a fraction 1 - 2F of the optimal multiplexing gain is achievable. The general conclusion of this work is that very significant downlink throughput is achievable with simple and efficient channel state feedback, provided that the feedback link is properly designed.

Includes members:
  Member "channel state feedback over the mimo mac":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "network mimo with linear zero forcing beamforming large system analysis impact of channel estimation and reduced complexity scheduling")
  Member "mode switching for the multi antenna broadcast channel based on delay and channel quantization":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "delay performance of the multiuser miso downlink under imperfect csi and finite length coding")
  Member "optimized training and feedback for mimo downlink channels":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "large system analysis of linear precoding in correlated miso broadcast channels under limited feedback")
  Member "channel state feedback schemes for multiuser mimo ofdm downlink":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "deep convolutional compression for massive mimo csi feedback")
  Member "antenna combining for the mimo downlink channel":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "hybrid beamforming noma for mmwave communications")
  Member "space division multiple access with a sum feedback rate constraint":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "modeling analysis and optimization of caching in multi antenna small cell networks")
  Member "multi user diversity vs accurate channel feedback for mimo broadcast channels":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "fundamental limits in correlated fading mimo broadcast channels benefits of transmit correlation diversity")
  Member "mimo broadcast channels with finite rate feedback":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "dl based csi feedback and cooperative recovery in massive mimo")

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)