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: "performance analysis of large intelligent surfaces liss uplink spectral efficiency and pilot training"
  Abstract: Large intelligent surfaces (LISs) constitute a new and promising wireless communication paradigm that relies on the integration of a massive number of antenna elements over the entire surfaces of man-made structures. The LIS concept provides many advantages, such as the capability to provide reliable and space-intensive communications by effectively establishing line-of-sight (LOS) channels. In this paper, the system spectral efficiency (SSE) of an uplink LIS system is asymptotically analyzed under a practical LIS environment with a well-defined uplink frame structure. In order to verify the impact on the SSE of pilot contamination, the SSE of a multi-LIS system is asymptotically studied and a theoretical bound on its performance is derived. Given this performance bound, an optimal pilot training length for multi-LIS systems subjected to pilot contamination is characterized and, subsequently, the performance-maximizing number of devices that the LIS system must service is derived. Simulation results show that the derived analyses are in close agreement with the exact mutual information in presence of a large number of antennas, and the achievable SSE is limited by the effect of pilot contamination and intra/inter-LIS interference through the LOS path, even if the LIS is equipped with an infinite number of antennas. Additionally, the SSE obtained with the proposed pilot training length and number of scheduled devices is shown to reach the one obtained via a brute-force search for the optimal solution.

Connected through hyperedge HE-1 (induced by source paper "millimeter wave communications with an intelligent reflector performance optimization and distributional reinforcement learning"):
  with members:
    - "intelligent reflecting surface meets ofdm protocol design and rate maximization"
    - "reflections in the sky millimeter wave communication with uav carried intelligent reflectors"
    - "reflect and transmit array antennas for scalable and energy efficient mmwave massive mimo"
    - "intelligent reflecting and transmitting surface aided millimeter wave massive mimo"
    - "a vision of 6g wireless systems applications trends technologies and open research problems"
    - "enabling large intelligent surfaces with compressive sensing and deep learning"
    - "intelligent reflecting surface enhanced wireless network via joint active and passive beamforming"
    - "fractional programming for communication systems part i power control and beamforming"

Connected through hyperedge HE-2 (induced by source paper "optimizations with intelligent reflecting surfaces irss in 6g wireless networks power control quality of service max min fair beamforming for unicast broadcast and multicast with multi antenna mobile users and multiple irss"):
  with members:
    - "over the air computation via intelligent reflecting surfaces"
    - "miso wireless communication systems via intelligent reflecting surfaces"
    - "cascaded channel estimation for large intelligent metasurface assisted massive mimo"
    - "reflection probability in wireless networks with metasurface coated environmental objects an approach based on random spatial processes"
    - "an interpretable neural network for configuring programmable wireless environments"
    - "beamforming optimization for wireless network aided by intelligent reflecting surface with discrete phase shifts"
    - "weighted sum power maximization for intelligent reflecting surface aided swipt"
    - "enabling large intelligent surfaces with compressive sensing and deep learning"

Connected through hyperedge HE-3 (induced by source paper "matrix calibration based cascaded channel estimation for reconfigurable intelligent surface assisted multiuser mimo"):
  with members:
    - "cascaded channel estimation for large intelligent metasurface assisted massive mimo"
    - "passive beamforming and information transfer via large intelligent surface"
    - "enabling large intelligent surfaces with compressive sensing and deep learning"
    - "intelligent reflecting surface enhanced wireless network via joint active and passive beamforming"
    - "reconfigurable intelligent surfaces for energy efficiency in wireless communication"
    - "large intelligent surface assisted wireless communication exploiting statistical csi"
    - "optimization based amp for phase retrieval the impact of initialization and ell_2 regularization"
    - "millimeter wave channel estimation via exploiting joint sparse and low rank structures"

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)