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: "massive mimo with multi cell mmse processing exploiting all pilots for interference suppression"
  Abstract: In this paper, a new state-of-the-art multi-cell MMSE scheme is proposed for massive MIMO networks, which includes an uplink MMSE detector and a downlink MMSE precoder. The main novelty is that it exploits all available pilots for interference suppression. Specifically, let $K$ and $B$ denote the number of users per cell and the number of orthogonal pilot sequences in the network, respectively, where $\beta = B/K$ is the pilot reuse factor. Then our multi-cell MMSE scheme utilizes all $B$ channel directions, that can be estimated locally at each base station, to actively suppress both intra-cell and inter-cell interference. The proposed scheme is particularly practical and general, since power control for the pilot and payload, imperfect channel estimation and arbitrary pilot allocation are all accounted for. Simulations show that significant spectral efficiency (SE) gains are obtained over the single-cell MMSE scheme and the multi-cell ZF, particularly for large $\beta$ and/or $K$. Furthermore, large-scale approximations of the uplink and downlink SINRs are derived, which are asymptotically tight in the large-system limit. The approximations are easy to compute and very accurate even for small system dimensions. Using these SINR approximations, a low-complexity power control algorithm is also proposed to maximize the sum SE.

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 "large system analysis of massive mimo with optimal m mmse processing"):
  with members:
    - "covariance matrix estimation for massive mimo"
    - "fundamental asymptotic behavior of two user distributed massive mimo"
    - "a bilinear equalizer for massive mimo systems"
    - "covariance matrix estimation in massive mimo"
    - "massive mimo has unlimited capacity"
    - "large system analysis of power normalization techniques in massive mimo"
    - "massive mimo with imperfect channel covariance information"
    - "massive mimo in real propagation environments do all antennas contribute equally"

Connected through hyperedge HE-3 (induced by source paper "addressing the curse of mobility in massive mimo with prony based angular delay domain channel predictions"):
  with members:
    - "massive mimo has unlimited capacity"
    - "robust pilot decontamination based on joint angle and power domain discrimination"
    - "sum rate and power scaling of massive mimo systems with channel aging"
    - "blind pilot decontamination"
    - "the degrees of freedom region of temporally correlated mimo networks with delayed csit"
    - "effects of channel aging in massive mimo systems"
    - "a coordinated approach to channel estimation in large scale multiple antenna systems"
    - "energy and spectral efficiency of very large multiuser mimo systems"

Connected through hyperedge HE-4 (induced by source paper "efficient dsp and circuit architectures for massive mimo state of the art and future directions"):
  with members:
    - "beyond massive mimo the potential of data transmission with large intelligent surfaces"
    - "out of band radiation from antenna arrays clarified"
    - "spatial characteristics of distortion radiated from antenna arrays with transceiver nonlinearities"
    - "decentralized baseband processing for massive mu mimo systems"
    - "performance characterization of a real time massive mimo system with los mobile channels"
    - "channel estimation and performance analysis of one bit massive mimo systems"
    - "on out of band emissions of quantized precoding in massive mu mimo ofdm"
    - "achievable uplink rates for massive mimo with coarse quantization"

Connected through hyperedge HE-5 (induced by source paper "theoretical performance limits of massive mimo with uncorrelated rician fading channels"):
  with members:
    - "massive mimo with spatially correlated rician fading channels"
    - "massive mimo has unlimited capacity"
    - "performance analysis of mixed adc massive mimo systems over rician fading channels"
    - "on the spectral efficiency of massive mimo systems with low resolution adcs"
    - "pilot contamination is not a fundamental asymptotic limitation in massive mimo"
    - "asymptotic analysis of multicell massive mimo over rician fading channels"
    - "achievable rate of rician large scale mimo channels with transceiver hardware impairments"
    - "massive mimo ten myths and one critical question"

Connected through hyperedge HE-6 (induced by source paper "massive mimo has unlimited capacity"):
  with members:
    - "massive mimo pilot decontamination and channel interpolation via wideband sparse channel estimation"
    - "massive mimo with imperfect channel covariance information"
    - "robust pilot decontamination based on joint angle and power domain discrimination"
    - "pilot contamination is not a fundamental asymptotic limitation in massive mimo"
    - "massive mimo in real propagation environments do all antennas contribute equally"
    - "massive mimo performance evaluation based on measured propagation data"
    - "pilot reuse for massive mimo transmission over spatially correlated rayleigh fading channels"
    - "optimal multiuser transmit beamforming a difficult problem with a simple solution structure"

Connected through hyperedge HE-7 (induced by source paper "user association and load balancing for massive mimo through deep learning"):
  with members:
    - "massive mimo has unlimited capacity"
    - "joint power allocation and user association optimization for massive mimo systems"
    - "wireless power transfer in massive mimo aided hetnets with user association"
    - "user association and interference management in massive mimo hetnets"
    - "adam a method for stochastic optimization"
    - "optimal user cell association for massive mimo wireless networks"

Connected through hyperedge HE-8 (induced by source paper "joint pilot design and uplink power allocation in multi cell massive mimo systems"):
  with members:
    - "pilot power allocation through user grouping in multi cell massive mimo systems"
    - "optimal pilot and payload power control in single cell massive mimo systems"
    - "joint power allocation and user association optimization for massive mimo systems"
    - "robust pilot decontamination based on joint angle and power domain discrimination"
    - "channel acquisition for massive mimo ofdm with adjustable phase shift pilots"
    - "massive mimo ten myths and one critical question"
    - "graph coloring based pilot allocation to mitigate pilot contamination for multi cell massive mimo systems"
    - "massive mimo performance evaluation based on measured propagation data"

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)