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: "reducing the computational complexity of multicasting in large scale antenna systems"
  Abstract: In this paper, we study the physical layer multicasting to multiple co-channel groups in large-scale antenna systems. The users within each group are interested in a common message and different groups have distinct messages. In particular, we aim at designing the precoding vectors solving the so-called quality of service (QoS) and weighted max-min fairness (MMF) problems, assuming that the channel state information is available at the base station (BS). To solve both problems, the baseline approach exploits the semidefinite relaxation (SDR) technique. Considering a BS with $N$ antennas, the SDR complexity is more than $\mathcal{O}(N^{6})$, which prevents its application in large-scale antenna systems. To overcome this issue, we present two new classes of algorithms that, not only have significantly lower computational complexity than existing solutions, but also largely outperform the SDR based methods. Moreover, we present a novel duality between transformed versions of the QoS and the weighted MMF problems. The duality explicitly determines the solution to the weighted MMF problem given the solution to the QoS problem, and vice versa. Numerical results are used to validate the effectiveness of the proposed solutions and to make comparisons with existing alternatives under different operating conditions.

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"
    - "multigroup multicast precoding in massive mimo"
    - "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 "large system analysis of power normalization techniques in massive mimo"):
  with members:
    - "massive mimo has unlimited capacity"
    - "energy efficient downlink transmission for multicell massive das with pilot contamination"
    - "joint power allocation and user association optimization for massive mimo systems"
    - "convergence analysis and assurance for gaussian message passing iterative detector in massive mu mimo systems"
    - "pilot contamination is not a fundamental asymptotic limitation in massive mimo"
    - "massive mimo ten myths and one critical question"
    - "performance analysis of massive mimo for cell boundary users"
    - "power allocation schemes for multicell massive mimo systems"

Connected through hyperedge HE-3 (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"
    - "multigroup multicast precoding in massive mimo"
    - "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)