human: Given a node-centered hypergraph: <hypergraph>, where nodes represent papers and hyperedges represent sets of papers co-cited by a source paper.

Details of the hypergraph:
Center node: "tomlinson harashima precoding for multiuser mimo systems with quantized csi feedback and user scheduling"
  Abstract: This paper studies the sum rate performance of a low complexity quantized CSI-based Tomlinson-Harashima (TH) precoding scheme for downlink multiuser MIMO transmission, employing greedy user selection. The asymptotic distribution of the output-signal-to-interference-plus-noise ratio of each selected user and the asymptotic sum rate as the number of users K grows large are derived by using extreme value theory. For fixed finite signal-to-noise ratios and a finite number of transmit antennas n#N# T#N#, we prove that as K grows large, the proposed approach can achieve the optimal sum rate scaling of the MIMO broadcast channel. We also prove that, if we ignore the precoding loss, the average sum rate of this approach converges to the average sum capacity of the MIMO broadcast channel. Our results provide insights into the effect of multiuser interference caused by quantized CSI on the multiuser diversity gain.

Connected through hyperedge HE-1 (induced by source paper "on the throughput of large but finite mimo networks using schedulers"):
  with members:
    - "network mimo with linear zero forcing beamforming large system analysis impact of channel estimation and reduced complexity scheduling"
    - "multi user mimo scheduling in the fourth generation cellular uplink"
    - "multi cell mimo downlink with cell cooperation and fair scheduling a large system limit analysis"
    - "user scheduling for heterogeneous multiuser mimo systems a subspace viewpoint"
    - "sum rates rate allocation and user scheduling for multi user mimo vector perturbation precoding"
    - "maximum sum rate of mimo multiuser scheduling with linear receivers"

Connected through hyperedge HE-2 (induced by source paper "tomlinson harashima precoded rate splitting for multiuser mimo systems"):
  with members:
    - "rate splitting for max min fair multigroup multicast beamforming in overloaded systems"
    - "optimal dof region of the k user miso bc with partial csit"
    - "widely linear precoding for large scale mimo with iqi algorithms and performance analysis"
    - "sum rate maximization for linearly precoded downlink multiuser miso systems with partial csit a rate splitting approach"
    - "miso networks with imperfect csit a topological rate splitting approach"
    - "robust transmission in downlink multiuser miso systems a rate splitting approach"
    - "rate splitting for mimo wireless networks a promising phy layer strategy for lte evolution"
    - "a rate splitting strategy for massive mimo with imperfect csit"

Connected through hyperedge HE-3 (induced by source paper "rate analysis of two receiver miso broadcast channel with finite rate feedback a rate splitting approach"):
  with members:
    - "sum rate maximization for linearly precoded downlink multiuser miso systems with partial csit a rate splitting approach"
    - "sum rate maximization for mu miso with partial csit using joint multicasting and broadcasting"
    - "achieving max min fairness for mu miso with partial csit a multicast assisted transmission"
    - "aligned image sets under channel uncertainty settling a conjecture by lapidoth shamai and wigger on the collapse of degrees of freedom under finite precision csit"
    - "quantized csi based tomlinson harashima precoding in multiuser mimo systems"
    - "optimal dof region of the two user miso bc with general alternating csit"
    - "miso broadcast channel with imperfect and un matched csit in the frequency domain dof region and transmission strategies"
    - "degrees of freedom region of miso ofdma broadcast channel with imperfect csit"

Question: Please tell me which class the center node 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)