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: "sum rate maximization in sub 28 ghz millimeter wave mimo interfering networks"
  Abstract: MIMO systems in the lower part of the millimeter-wave spectrum band (i.e., below 28 GHz) do not exhibit enough directivity and selectively, as their counterparts in higher bands of the spectrum (i.e., above 60 GHz), and thus still suffer from the detrimental effect of interference, on the system sum-rate. As such systems exhibit large numbers of antennas and short coherence times for the channel, traditional methods of distributed coordination are ill-suited, and the resulting communication overhead would offset the gains of coordination. In this work, we propose algorithms for tackling the sum-rate maximization problem, that are designed to address the above limitations. We derive a lower bound on the sum-rate, a so-called DLT bound (i.e., a difference of log and trace), shed light on its tightness, and highlight its decoupled nature at both the transmitters and receivers. Moreover, we derive the solution to each of the subproblems, that we dub non-homogeneous waterfilling (a variation on the MIMO waterfilling solution), and underline an inherent desirable feature: its ability to turn-off streams exhibiting low-SINR, and contribute to greatly speeding up the convergence of the proposed algorithm. We then show the convergence of the resulting algorithm, max-DLT, to a stationary point of the DLT bound. Finally, we rely on extensive simulations of various network configurations, to establish the fast-converging nature of our proposed schemes, and thus their suitability for addressing the short coherence interval, as well as the increased system dimensions, arising when managing interference in lower bands of the millimeter wave spectrum. Moreover, our results also suggest that interference management still brings about significant performance gains, especially in dense deployments.

Connected through hyperedge HE-1 (induced by source paper "a hybrid model based and data driven approach to spectrum sharing in mmwave cellular networks"):
  with members:
    - "how to escape saddle points efficiently"
    - "modeling infrastructure sharing in mmwave networks with shared spectrum licenses"
    - "alternating minimization algorithms for hybrid precoding in millimeter wave mimo systems"
    - "subspace estimation and decomposition for large millimeter wave mimo systems"
    - "spectrum sharing in mmwave cellular networks via cell association coordination and beamforming"
    - "stochastic geometry modeling and analysis of multi tier millimeter wave cellular networks"
    - "the transitional behavior of interference in millimeter wave networks and its impact on medium access control"
    - "adam a method for stochastic optimization"

Connected through hyperedge HE-2 (induced by source paper "low overhead coordination in sub 28 millimeter wave networks"):
  with members:
    - "millimeter wave cellular networks a mac layer perspective"
    - "what will 5g be"
    - "millimeter wave beamforming for wireless backhaul and access in small cell networks"
    - "on the degrees of freedom achievable through interference alignment in a mimo interference channel"
    - "cooperative algorithms for mimo interference channels"

Connected through hyperedge HE-3 (induced by source paper "distributed coordinated transmission with forward backward training for 5g radio access"):
  with members:
    - "pilot contamination and precoding in multi cell tdd systems"

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)