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: "optimal pilot and payload power control in single cell massive mimo systems"
  Abstract: This paper considers the jointly optimal pilot and data power allocation in single-cell uplink massive multiple-input-multiple-output systems. Using the spectral efficiency (SE) as performance metric and setting a total energy budget per coherence interval, the power control is formulated as optimization problems for two different objective functions: the weighted minimum SE among the users and the weighted sum SE. A closed form solution for the optimal length of the pilot sequence is derived. The optimal power control policy for the former problem is found by solving a simple equation with a single variable. Utilizing the special structure arising from imperfect channel estimation, a convex reformulation is found to solve the latter problem to global optimality in polynomial time. The gain of the optimal joint power control is theoretically justified, and is proved to be large in the low-SNR regime. Simulation results also show the advantage of optimizing the power control over both pilot and data power, as compared to the cases of using full power and of only optimizing the data powers as done in previous work.

Connected through hyperedge HE-1 (induced by source paper "power control in cellular massive mimo with varying user activity a deep learning solution"):
  with members:
    - "sum spectral efficiency maximization in massive mimo systems benefits from deep learning"
    - "optimized power control for massive mimo with underlaid d2d communications"
    - "joint transmit and circuit power minimization in massive mimo with downlink sinr constraints when to turn on massive mimo"
    - "large scale fading decoding in cellular massive mimo systems with spatially correlated channels"
    - "learning to optimize training deep neural networks for interference management"
    - "model aided wireless artificial intelligence embedding expert knowledge in deep neural networks towards wireless systems optimization"
    - "residual dense network for image super resolution"
    - "an introduction to deep learning for the physical layer"

Connected through hyperedge HE-2 (induced by source paper "joint user selection power allocation and precoding design with imperfect csit for multi cell mu mimo downlink systems"):
  with members:
    - "on the capacity of cloud radio access networks with oblivious relaying"
    - "on the ergodic rate lower bounds with applications to massive mimo"
    - "massive mimo with imperfect channel covariance information"
    - "sum rate maximization for linearly precoded downlink multiuser miso systems with partial csit a rate splitting approach"
    - "robust transmission in downlink multiuser miso systems a rate splitting approach"
    - "cell free massive mimo versus small cells"
    - "a rate splitting strategy for massive mimo with imperfect csit"
    - "limited feedback hybrid precoding for multi user millimeter wave systems"

Connected through hyperedge HE-3 (induced by source paper "dynamic resource allocation in co located and cell free massive mimo"):
  with members:
    - "dynamic scheduling and power control in uplink massive mimo with random data arrivals"
    - "ubiquitous cell free massive mimo communications"
    - "large scale fading decoding in cellular massive mimo systems with spatially correlated channels"
    - "making cell free massive mimo competitive with mmse processing and centralized implementation"
    - "dynamic power control for packets with deadlines"
    - "performance of cell free massive mimo systems with mmse and lsfd receivers"
    - "channel hardening and favorable propagation in cell free massive mimo with stochastic geometry"
    - "ultra reliable and low latency communication in mmwave enabled massive mimo networks"

Connected through hyperedge HE-4 (induced by source paper "techniques for system information broadcast in cell free massive mimo"):
  with members:
    - "ubiquitous cell free massive mimo communications"
    - "on the total energy efficiency of cell free massive mimo"
    - "modeling and analysis of cellular networks using stochastic geometry a tutorial"
    - "channel hardening and favorable propagation in cell free massive mimo with stochastic geometry"
    - "performance of in band transmission of system information in massive mimo systems"
    - "energy efficiency in cell free massive mimo with zero forcing precoding design"
    - "cell free massive mimo versus small cells"
    - "stochastic geometry modeling of cellular networks analysis simulation and experimental validation"

Connected through hyperedge HE-5 (induced by source paper "spatial characterization of holographic mimo channels"):
  with members:
    - "degrees of freedom of holographic mimo channels"
    - "large system analysis of massive mimo with optimal m mmse processing"
    - "beyond massive mimo the potential of data transmission with large intelligent surfaces"
    - "massive mimo has unlimited capacity"
    - "space constrained massive mimo hitting the wall of favorable propagation"
    - "a generalized spatial correlation model for 3d mimo channels based on the fourier coefficients of power spectrums"
    - "on landau s eigenvalue theorem and information cut sets"
    - "optimal design of energy efficient multi user mimo systems is massive mimo the answer"

Connected through hyperedge HE-6 (induced by source paper "spatially stationary model for holographic mimo small scale fading"):
  with members:
    - "degrees of freedom of holographic mimo channels"
    - "beyond massive mimo the potential of data transmission with large intelligent surfaces"
    - "massive mimo has unlimited capacity"
    - "ns 3 implementation of the 3gpp mimo channel model for frequency spectrum above 6 ghz"
    - "a generalized spatial correlation model for 3d mimo channels based on the fourier coefficients of power spectrums"
    - "on landau s eigenvalue theorem and information cut sets"
    - "optimal design of energy efficient multi user mimo systems is massive mimo the answer"
    - "energy and spectral efficiency of very large multiuser mimo systems"

Connected through hyperedge HE-7 (induced by source paper "sum spectral efficiency maximization in massive mimo systems benefits from deep learning"):
  with members:
    - "large scale fading decoding in cellular massive mimo systems with spatially correlated channels"
    - "learning to optimize training deep neural networks for interference management"
    - "model aided wireless artificial intelligence embedding expert knowledge in deep neural networks towards wireless systems optimization"
    - "residual dense network for image super resolution"
    - "densely connected convolutional networks"
    - "deep residual learning for image recognition"
    - "adam a method for stochastic optimization"
    - "matconvnet convolutional neural networks for matlab"

Connected through hyperedge HE-8 (induced by source paper "power control for massive mimo systems with nonorthogonal pilots"):
  with members:
    - "large scale fading decoding in cellular massive mimo systems with spatially correlated channels"
    - "pilot contamination mitigation with reduced rf chains"
    - "massive mimo has unlimited capacity"
    - "joint pilot design and uplink power allocation in multi cell massive mimo systems"
    - "a parallel decomposition method for nonconvex stochastic multi agent optimization problems"
    - "distributed massive mimo in cellular networks impact of imperfect hardware and number of oscillators"

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)