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: "scaling up mimo opportunities and challenges with very large arrays"
  Abstract: Multiple-input multiple-output (MIMO) technology is maturing and is being incorporated into emerging wireless broadband standards like long-term evolution (LTE) [1]. For example, the LTE standard allows for up to eight antenna ports at the base station. Basically, the more antennas the transmitter/receiver is equipped with, and the more degrees of freedom that the propagation channel can provide, the better the performance in terms of data rate or link reliability. More precisely, on a quasi static channel where a code word spans across only one time and frequency coherence interval, the reliability of a point-to-point MIMO link scales according to Prob(link outage) ` SNR-ntnr where nt and nr are the numbers of transmit and receive antennas, respectively, and signal-to-noise ratio is denoted by SNR. On a channel that varies rapidly as a function of time and frequency, and where circumstances permit coding across many channel coherence intervals, the achievable rate scales as min(nt, nr) log(1 + SNR). The gains in multiuser systems are even more impressive, because such systems offer the possibility to transmit simultaneously to several users and the flexibility to select what users to schedule for reception at any given point in time [2].

Connected through hyperedge HE-1 (induced by source paper "downlink secrecy rate of one bit massive mimo system with active eavesdropping"):
  with members:
    - "robust designs of beamforming and power splitting for distributed antenna systems with wireless energy harvesting"
    - "secure massive mimo communication with low resolution dacs"
    - "on the uplink achievable rate for massive mimo with 1 bit adc and superimposed pilots"
    - "data aided secure massive mimo transmission with active eavesdropping"
    - "secure massive mimo systems with limited rf chains"
    - "secure transmission with large numbers of antennas and finite alphabet inputs"
    - "jamming resistant receivers for the massive mimo uplink"
    - "beamforming and power splitting designs for an aided secure multi user mimo swipt systems"

Connected through hyperedge HE-2 (induced by source paper "deep learning for massive mimo channel state acquisition and feedback"):
  with members:
    - "deep learning for massive mimo with 1 bit adcs when more antennas need fewer pilots"
    - "deep learning based channel estimation for massive mimo with mixed resolution adcs"
    - "cnn based analog csi feedback in fdd mimo ofdm systems"
    - "deep learning for tdd and fdd massive mimo mapping channels in space and frequency"
    - "deepmimo a generic deep learning dataset for millimeter wave and massive mimo applications"
    - "multi resolution csi feedback with deep learning in massive mimo system"
    - "deep convolutional compression for massive mimo csi feedback"
    - "machine learning in the air"

Connected through hyperedge HE-3 (induced by source paper "massive mimo asymptotics for ray based propagation channels"):
  with members:
    - "mimo channel hardening a physical model based analysis"
    - "channel hardening in massive mimo a measurement based analysis"
    - "energy efficiency and asymptotic performance evaluation of beamforming structures in doubly massive mimo mmwave systems"
    - "a random access protocol for pilot allocation in crowded massive mimo systems"
    - "uplink analysis of large mu mimo systems with space constrained arrays in ricean fading"
    - "no downlink pilots are needed in tdd massive mimo"
    - "massive mimo ten myths and one critical question"
    - "asymptotic orthogonality analysis of time domain sparse massive mimo channels"

Connected through hyperedge HE-4 (induced by source paper "study of coarse quantization aware block diagonalization algorithms for mimo systems with low resolution"):
  with members:
    - "throughput analysis of massive mimo uplink with low resolution adcs"
    - "branch and bound precoding for multiuser mimo systems with 1 bit quantization"
    - "widely linear precoding for large scale mimo with iqi algorithms and performance analysis"
    - "linear precoding with low resolution dacs for massive mu mimo ofdm downlink"
    - "iterative detection and decoding algorithms for mimo systems in block fading channels using ldpc codes"
    - "robust adaptive beamforming based on low rank and cross correlation techniques"
    - "quantized precoding for massive mu mimo"
    - "adaptive reduced rank receive processing based on minimum symbol error rate criterion for large scale multiple antenna systems"

Connected through hyperedge HE-5 (induced by source paper "covariance aided csi acquisition with non orthogonal pilots in massive mimo a large system performance analysis"):
  with members:
    - "massive mimo has unlimited capacity"
    - "pilot length optimization for spatially correlated multi user mimo channel estimation"
    - "snops short non orthogonal pilot sequences for downlink channel state estimation in fdd massive mimo"
    - "pilot reuse for massive mimo transmission over spatially correlated rayleigh fading channels"
    - "dealing with interference in distributed large scale mimo systems a statistical approach"
    - "achievable rates of fdd massive mimo systems with spatial channel correlation"
    - "massive mimo for next generation wireless systems"
    - "five disruptive technology directions for 5g"

Connected through hyperedge HE-6 (induced by source paper "statistical beamforming for fdd downlink massive mimo via spatial information extraction and beam selection"):
  with members:
    - "semi blind channel and signal estimation for uplink massive mimo with channel sparsity"
    - "multi band covariance interpolation with applications in massive mimo"
    - "structured turbo compressed sensing for downlink massive mimo ofdm channel estimation"
    - "fdd massive mimo via ul dl channel covariance extrapolation and active channel sparsification"
    - "channel estimation for tdd fdd massive mimo systems with channel covariance computing"
    - "dictionary learning based sparse channel representation and estimation for fdd massive mimo systems"
    - "pilot reuse for massive mimo transmission over spatially correlated rayleigh fading channels"
    - "massive mimo for next generation wireless systems"

Connected through hyperedge HE-7 (induced by source paper "reconfigurable intelligent surface assisted multiuser miso systems exploiting deep reinforcement learning"):
  with members:
    - "beamforming design for large scale antenna arrays using deep learning"
    - "indoor signal focusing with deep learning designed reconfigurable intelligent surfaces"
    - "learning to optimize training deep neural networks for interference management"
    - "achievable rate maximization by passive intelligent mirrors"
    - "intelligent reflecting surface enhanced wireless network via joint active and passive beamforming"
    - "beyond massive mimo the potential of positioning with large intelligent surfaces"
    - "beyond massive mimo the potential of data transmission with large intelligent surfaces"
    - "applications of deep reinforcement learning in communications and networking a survey"

Connected through hyperedge HE-8 (induced by source paper "on low complexity lattice reduction algorithms for large scale mimo detection the blessing of sequential reduction"):
  with members:
    - "on the kz reduction"
    - "boosted kz and lll algorithms"
    - "gfclll a greedy selection based approach for fixed complexity lll reduction"
    - "on the geometric ergodicity of metropolis hastings algorithms for lattice gaussian sampling"
    - "success probability of the babai estimators for box constrained integer linear models"
    - "on the proximity factors of lattice reduction aided decoding"
    - "decoding by sampling a randomized lattice algorithm for bounded distance decoding"
    - "communication over mimo broadcast channels using lattice basis reduction"

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)