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: "computationally efficient robust beamforming for sinr balancing in multicell downlink with applications to large antenna array systems"
  Abstract: We address the problem of the downlink beamformer design for signal-to-interference-plus-noise ratio balancing in a multiuser multicell environment with imperfectly estimated channels at base stations. We first present a semidefinite program (SDP)-based approximate solution to the problem. Then, as our main contribution, by exploiting some properties of the robust counterpart of the optimization problem, we arrive at a second-order cone program (SOCP)-based approximation of the balancing problem. The advantages of the proposed SOCP-based design are twofold. First, it greatly reduces the computational complexity compared to the SDP-based method. Second, it applies to a wide range of uncertainty models. As a case study, we investigate the performance of proposed formulations when the base station is equipped with a massive antenna array. Numerical experiments are carried out to confirm that the proposed robust designs achieve favorable results in scenarios of practical interest.

Connected through hyperedge HE-1 (induced by source paper "interference exploitation precoding for multi level modulations closed form solutions"):
  with members:
    - "interference exploitation in full duplex communications trading interference power for both uplink and downlink power savings"
    - "symbol level multiuser miso precoding for multi level adaptive modulation"
    - "constructive multiuser interference in symbol level precoding for the miso downlink channel"
    - "exploiting known interference as green signal power for downlink beamforming optimization"
    - "rethinking the role of interference in wireless networks"
    - "quantized csi based tomlinson harashima precoding in multiuser mimo systems"

Connected through hyperedge HE-2 (induced by source paper "interference exploitation precoding made practical closed form solutions with optimal performance"):
  with members:
    - "transmit precoding for interference exploitation in the underlay cognitive radio z channel"
    - "symbol level multiuser miso precoding for multi level adaptive modulation"
    - "constructive multiuser interference in symbol level precoding for the miso downlink channel"
    - "exploiting known interference as green signal power for downlink beamforming optimization"
    - "rethinking the role of interference in wireless networks"
    - "quantized csi based tomlinson harashima precoding in multiuser mimo systems"

Connected through hyperedge HE-3 (induced by source paper "performance analysis of zf receivers with imperfect csi for uplink massive mimo systems"):
  with members:
    - "massive mimo for next generation wireless systems"
    - "scaling up mimo opportunities and challenges with very large arrays"
    - "a coordinated approach to channel estimation in large scale multiple antenna systems"
    - "achieving massive mimo spectral efficiency with a not so large number of antennas"
    - "energy and spectral efficiency of very large multiuser mimo systems"
    - "pilot contamination and precoding in multi cell tdd systems"

Connected through hyperedge HE-4 (induced by source paper "hybrid block diagonalization for massive multiuser mimo systems"):
  with members:
    - "limited feedback hybrid precoding for multi user millimeter wave systems"
    - "massive mimo for next generation wireless systems"
    - "what will 5g be"
    - "spatially sparse precoding in millimeter wave mimo systems"
    - "low complexity hybrid precoding in massive multiuser mimo systems"
    - "scaling up mimo opportunities and challenges with very large arrays"

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)