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 "robust beamforming in interference channels with imperfect transmitter channel information"):
  Abstract: We consider $K$ links operating concurrently in the same spectral band. Each transmitter has multiple antennas, while each receiver uses a single antenna. This setting corresponds to the multiple-input single-output interference channel. We assume perfect channel state information at the single-user decoding receivers whereas the transmitters only have estimates of the true channels. The channel estimation errors are assumed to be bounded in elliptical regions whose geometry is known at the transmitters. Robust beamforming optimizes worst-case received power gains, and a Pareto optimal point is a worst-case achievable rate tuple from which it is impossible to increase a link's performance without degrading the performance of another. We characterize the robust beamforming vectors necessary to operate at any Pareto optimal point. Moreover, these beamforming vectors are parameterized by $K(K-1)$ real-valued parameters. We analyze the system's spectral efficiency at high and low signal-to-noise ratio (SNR). Zero forcing transmission achieves full multiplexing gain at high SNR only if the estimation errors scale linearly with inverse SNR. If the errors are SNR independent, then single-user transmission is optimal at high SNR. At low SNR, robust maximum ratio transmission optimizes the minimum energy per bit for reliable communication. Numerical simulations illustrate the gained theoretical results.

Includes members:
  Member "distributed robust multicell coordinated beamforming with imperfect csi an admm approach":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "robust urllc packet scheduling of ofdm systems")
  Member "pareto characterization of the multicell mimo performance region with simple receivers":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "linear transceiver optimization in multicell mimo based on the generalized benders decomposition")
  Member "robust monotonic optimization framework for multicell miso systems":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "robust resource allocation for pd noma based miso heterogeneous networks with comp technology")
  Member "achievable and crystallized rate regions of the interference channel with interference as noise":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "treating interference as noise in cellular networks a stochastic geometry approach")
  Member "robust linear precoder design for multi cell downlink transmission":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "non orthogonal unicast and broadcast transmission via joint beamforming and ldm in cellular networks")
  Member "optimal beamforming in interference networks with perfect local channel information":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "heterogeneous multi tier networks improper signaling for joint rate energy optimization")
  Member "cooperative interference management with miso beamforming":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "intelligent reflecting surface aided multiple access capacity region and deployment strategy")
  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)