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: "iterative joint beamforming training with constant amplitude phased arrays in millimeter wave communications"
  Abstract: In millimeter-wave communications (MMWC), in order to compensate for high propagation attenuation, phased arrays are favored to achieve array gain by beamforming, where transmitting and receiving antenna arrays need to be jointly trained to obtain appropriate antenna weight vectors (AWVs). Since the amplitude of each element of the AWV is usually constraint constant to simplify the design of phased arrays in MMWC, the existing singular vector based beamforming training scheme cannot be used for such devices. Thus, in this letter, a steering vector based iterative beamforming training scheme, which exploits the directional feature of MMWC channels, is proposed for devices with constant-amplitude phased arrays. Performance evaluations show that the proposed scheme achieves a fast convergence rate as well as a near optimal array gain.

Connected through hyperedge HE-1 (induced by source paper "channel estimation and transmission for intelligent reflecting surface assisted thz communications"):
  with members:
    - "intelligent reflecting surface design for mimo system by maximizing sum path gains"
    - "achievable rate maximization by passive intelligent mirrors"
    - "intelligent reflecting surface enhanced wireless network via joint active and passive beamforming"
    - "reconfigurable intelligent surfaces for energy efficiency in wireless communication"
    - "hierarchical codebook design for beamforming training in millimeter wave communication"
    - "limited feedback hybrid precoding for multi user millimeter wave systems"
    - "channel estimation and hybrid precoding for millimeter wave cellular systems"

Connected through hyperedge HE-2 (induced by source paper "millimeter wave mimo channel estimation using overlapped beam patterns and rate adaptation"):
  with members:
    - "fast channel estimation for millimetre wave wireless systems using overlapped beam patterns"
    - "race a rate adaptive channel estimation approach for millimeter wave mimo systems"
    - "hierarchical codebook design for beamforming training in millimeter wave communication"
    - "pilot beam sequence design for channel estimation in millimeter wave mimo systems a pomdp framework"
    - "iterative eigenvalue decomposition and multipath grouping tx rx joint beamformings for millimeter wave communications"
    - "channel estimation and hybrid precoding for millimeter wave cellular systems"
    - "millimeter wave cellular wireless networks potentials and challenges"
    - "millimeter wave channel modeling and cellular capacity evaluation"

Connected through hyperedge HE-3 (induced by source paper "hierarchical codebook design for beamforming training in millimeter wave communication"):
  with members:
    - "fast channel estimation for millimetre wave wireless systems using overlapped beam patterns"
    - "frequency selective hybrid precoding for limited feedback millimeter wave systems"
    - "limited feedback hybrid precoding for multi user millimeter wave systems"
    - "iterative eigenvalue decomposition and multipath grouping tx rx joint beamformings for millimeter wave communications"
    - "compressed sensing based multi user millimeter wave systems how many measurements are needed"
    - "channel estimation and hybrid precoding for millimeter wave cellular systems"
    - "spatially sparse precoding in millimeter wave mimo systems"
    - "suboptimal spatial diversity scheme for 60 ghz millimeter wave wlan"

Connected through hyperedge HE-4 (induced by source paper "exploiting device to device communications to enhance spatial reuse for popular content downloading in directional mmwave small cells"):
  with members:
    - "exploiting multi hop relaying to overcome blockage in directional mmwave small cells"
    - "exploiting device to device communications in joint scheduling of access and backhaul for mmwave small cells"
    - "modeling analysis and optimization of multicast device to device transmissions"
    - "wireless backhaul node placement for small cell networks"
    - "coding the beams improving beamforming training in mmwave communication system"
    - "femtocell networks a survey"

Connected through hyperedge HE-5 (induced by source paper "low complexity hybrid precoding and channel estimation based on hierarchical multi beam search for millimeter wave mimo systems"):
  with members:
    - "iterative eigenvalue decomposition and multipath grouping tx rx joint beamformings for millimeter wave communications"
    - "channel estimation and hybrid precoding for millimeter wave cellular systems"
    - "spatially sparse precoding in millimeter wave mimo systems"
    - "suboptimal spatial diversity scheme for 60 ghz millimeter wave wlan"
    - "millimeter wave beamforming for wireless backhaul and access in small cell networks"

Connected through hyperedge HE-6 (induced by source paper "boosting spatial reuse via multiple path multihop scheduling for directional mmwave wpans"):
  with members:
    - "coding the beams improving beamforming training in mmwave communication system"

Connected through hyperedge HE-7 (induced by source paper "iterative eigenvalue decomposition and multipath grouping tx rx joint beamformings for millimeter wave communications"):
  with members:
    - "spatially sparse precoding in millimeter wave mimo systems"
    - "suboptimal spatial diversity scheme for 60 ghz millimeter wave wlan"

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)