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: "channel estimation and transmission for intelligent reflecting surface assisted thz communications"
  Abstract: Intelligent reflecting surface (IRS) is envisioned as a promising technology to broaden signal coverage and enhance transmission in terahertz (THz) communications. Due to the passivity of IRS, the channel measurement can not be achieved by traditional pilot manner and the subsequent cooperative transmission design remains an open problem. This paper investigates the channel estimation and transmission solutions for massive multiple input multiple output (MIMO) IRS-assisted THz system. The channel estimation is realized by beam training and the quantization error is analyzed for evaluating performance. In addition, a novel hierarchical search codebook design is proposed as a low-complexity basis of beam training. Based on above foundations, we propose a cooperative channel estimation procedure to tactfully acquire the channel knowledge. Finally, by leveraging obtained channel information, the designs of IRS and transceivers are directly provided in closed form without reconstructing the full channel matrix or additional optimization. Simulation and numerical results are presented to illustrate the minimum signal to noise ratio (SNR) required for beam training and the efficacy of the proposed transmission solutions.

Connected through hyperedge HE-1 (induced by source paper "channel estimation and hybrid beamforming for reconfigurable intelligent surfaces assisted thz communications"):
  with members:
    - "secure wireless communication via intelligent reflecting surface"
    - "capacity characterization for intelligent reflecting surface aided mimo communication"
    - "intelligent reflecting surface meets ofdm protocol design and rate maximization"
    - "intelligent reflecting surface design for mimo system by maximizing sum path gains"
    - "energy efficient multi user miso communication using low resolution large intelligent surfaces"
    - "achievable rate maximization by passive intelligent mirrors"
    - "intelligent reflecting surface enhanced wireless network via joint active and passive beamforming"
    - "beyond massive mimo the potential of data transmission with large intelligent surfaces"

Connected through hyperedge HE-2 (induced by source paper "channel estimation method and phase shift design for reconfigurable intelligent surface assisted mimo networks"):
  with members:
    - "joint active and passive beamforming optimization for intelligent reflecting surface assisted swipt under qos constraints"
    - "bilinear recovery using adaptive vector amp"
    - "intelligent reflecting surface with discrete phase shifts channel estimation and passive beamforming"
    - "cascaded channel estimation for large intelligent metasurface assisted massive mimo"
    - "hybrid beamforming for reconfigurable intelligent surface based multi user communications achievable rates with limited discrete phase shifts"
    - "channel estimation for intelligent reflecting surface assisted multiuser communications"
    - "reliability analysis of large intelligent surfaces liss rate distribution and outage probability"
    - "reconfigurable intelligent surface assisted uav communication joint trajectory design and passive beamforming"

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)