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: "multigroup multicast precoding in massive mimo"
  Abstract: Optimal physical layer multicasting (PLM) is an NP-hard problem that for simplicity has been studied under idealistic assumptions, e.g., availability of perfect channel state information (CSI), both at the base station (BS) and at the user terminals (UTs). With the advent of massive multiple-input-multiple-output (MIMO), PLM has become more challenging, as the computational complexity of the precoder design is proportional to the number of BS antennas. In this paper, we address these issues by introducing computationally efficient precoders that account for practical CSI acquisition. We derive achievable spectral efficiency expressions for the proposed precoders. Then we introduce a novel problem formulation for the max-min fairness power control that accounts the CSI acquisition overhead, uplink training and downlink transmission powers. We solve this problem and find the optimal uplink and downlink power control policies in closed form. Using numerical simulations, we verify the effectiveness of our proposed schemes compared to the-state-of-the-art PLM schemes for massive MIMO systems.

Connected through hyperedge HE-1 (induced by source paper "joint unicast and multi group multicast transmission in massive mimo systems"):
  with members:
    - "large system analysis of power normalization techniques in massive mimo"
    - "hybrid precoding for multi group physical layer multicasting"
    - "max min fair transmit precoding for multi group multicasting in massive mimo"
    - "reducing the computational complexity of multicasting in large scale antenna systems"
    - "joint beamforming and broadcasting in massive mimo"
    - "hybrid precoding for physical layer multicasting"
    - "on the spectral efficiency and security enhancements of noma assisted multicast unicast streaming"
    - "massive mimo ten myths and one critical question"

Connected through hyperedge HE-2 (induced by source paper "max min fair transmit precoding for multi group multicasting in massive mimo"):
  with members:
    - "large system analysis of power normalization techniques in massive mimo"
    - "reducing the computational complexity of multicasting in large scale antenna systems"
    - "joint beamforming and broadcasting in massive mimo"
    - "no downlink pilots are needed in tdd massive mimo"
    - "massive mimo ten myths and one critical question"
    - "multicast multigroup beamforming for per antenna power constrained large scale arrays"
    - "massive mimo performance evaluation based on measured propagation data"
    - "massive mimo multicasting in noncooperative cellular networks"

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)