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 "joint spatial division and multiplexing"):
  Abstract: We propose Joint Spatial Division and Multiplexing (JSDM), an approach to multiuser MIMO downlink that exploits the structure of the correlation of the channel vectors in order to allow for a large number of antennas at the base station while requiring reduced-dimensional Channel State Information at the Transmitter (CSIT). This allows for significant savings both in the downlink training and in the CSIT feedback from the user terminals to the base station, thus making the use of a large number of base station antennas potentially suitable also for Frequency Division Duplexing (FDD) systems, for which uplink/downlink channel reciprocity cannot be exploited. JSDM forms the multiuser MIMO downlink precoder by concatenating a pre-beamforming matrix, which depends only on the channel second-order statistics, with a classical multiuser precoder, based on the instantaneous knowledge of the resulting reduced dimensional effective channels. We prove a simple condition under which JSDM incurs no loss of optimality with respect to the full CSIT case. For linear uniformly spaced arrays, we show that such condition is closely approached when the number of antennas is large. For this case, we use Szego asymptotic theory of large Toeplitz matrices to design a DFT-based pre-beamforming scheme requiring only coarse information about the users angles of arrival and angular spread. Finally, we extend these ideas to the case of a two-dimensional base station antenna array, with 3-dimensional beamforming, including multiple beams in the elevation angle direction. We provide guidelines for the pre-beamforming optimization and calculate the system spectral efficiency under proportional fairness and maxmin fairness criteria, showing extremely attractive performance. Our numerical results are obtained via an asymptotic random matrix theory tool known as deterministic equivalent approximation.

Includes members:
  Member "a coordinated approach to channel estimation in large scale multiple antenna systems":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "on the pilot contamination attack in multi cell multiuser massive mimo networks")
  Member "network mimo with linear zero forcing beamforming large system analysis impact of channel estimation and reduced complexity scheduling":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "joint user selection power allocation and precoding design with imperfect csit for multi cell mu mimo downlink systems")
  Member "achieving massive mimo spectral efficiency with a not so large number of antennas":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "performance of multi cell massive mimo systems with interference decoding")
  Member "improved subspace estimation for multivariate observations of high dimension the deterministic signals case":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "report on two step knowledge aided iterative esprit algorithm")
  Member "completely stale transmitter channel state information is still very useful":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "achievable dof regions of three user mimo broadcast channel with delayed csit")
  Member "aiming perfectly in the dark blind interference alignment through staggered antenna switching":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "linear degrees of freedom of mimo broadcast channels with reconfigurable antennas in the absence of csit")
  Member "training and feedback optimization for multiuser mimo downlink":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "artificial noisy mimo systems under correlated scattering rayleigh fading a physical layer security approach")
  Member "multiuser mimo achievable rates with downlink training and channel state feedback":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "beyond dirty paper coding for multi antenna broadcast channel with partial csit a rate splitting approach")

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)