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: "hybrid precoding for multi group physical layer multicasting"
  Abstract: Next generation of wireless networks will likely rely on large-scale antenna systems, either in the form of massive multi-input-multi-output (MIMO) or millimeter wave (mmWave) systems. Therefore, the conventional fully-digital precoders are not suitable for physical layer multicasting as they require a dedicated radio frequency chain per antenna element. In this paper, we show that in a multi-group multicasting system with an arbitrary number of transmit antennas, $G$ multicasting groups, and an arbitrary number of users in each group, one can achieve the performance of any fully-digital precoder with just $G$ radio frequency chains using the proposed hybrid multi-group multicasting structure.

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"
    - "max min fair transmit precoding for multi group multicasting in massive mimo"
    - "multigroup multicast precoding 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"

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)