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: "on the performance of mismatched data detection in large mimo systems"
  Abstract: We investigate the performance of mismatched data detection in large multiple-input multiple-output (MIMO) systems, where the prior distribution of the transmit signal used in the data detector differs from the true prior. To minimize the performance loss caused by this prior mismatch, we include a tuning stage into our recently-proposed large MIMO approximate message passing (LAMA) algorithm, which allows us to develop mismatched LAMA algorithms with optimal as well as sub-optimal tuning. We show that carefully-selected priors often enable simpler and computationally more efficient algorithms compared to LAMA with the true prior while achieving near-optimal performance. A performance analysis of our algorithms for a Gaussian prior and a uniform prior within a hypercube covering the QAM constellation recovers classical and recent results on linear and non-linear MIMO data detection, respectively.

Connected through hyperedge HE-1 (induced by source paper "decentralized equalization with feedforward architectures for massive mu mimo"):
  with members:
    - "gaussian message passing for overloaded massive mimo noma"
    - "feedforward architectures for decentralized precoding in massive mu mimo systems"
    - "efficient dsp and circuit architectures for massive mimo state of the art and future directions"
    - "decentralized baseband processing for massive mu mimo systems"
    - "optimally tuned nonparametric linear equalization for massive mu mimo systems"
    - "on the achievable rates of decentralized equalization in massive mu mimo systems"
    - "performance trade offs in multi processor approximate message passing"
    - "the world s first real time testbed for massive mimo design implementation and validation"

Connected through hyperedge HE-2 (induced by source paper "optimal data detection in large mimo"):
  with members:
    - "precise error analysis of regularized m estimators in high dimensions"
    - "ber analysis of the box relaxation for bpsk signal recovery"
    - "compressive phase retrieval via generalized approximate message passing"
    - "does ell_p minimization outperform ell_1 minimization"
    - "large scale mimo detection for 3gpp lte algorithms and fpga implementations"
    - "massive mimo for next generation wireless systems"
    - "what will 5g be"
    - "from denoising to compressed sensing"

Connected through hyperedge HE-3 (induced by source paper "hybrid vector perturbation precoding the blessing of approximate message passing"):
  with members:
    - "boosted kz and lll algorithms"
    - "hybrid approximate message passing"
    - "channel pre inversion and max sinr vector perturbation for large scale broadcast channels"
    - "convergence analysis and assurance for gaussian message passing iterative detector in massive mu mimo systems"
    - "optimality of large mimo detection via approximate message passing"
    - "massive mimo for next generation wireless systems"
    - "expectation propagation for approximate bayesian inference"
    - "proximity factors of lattice reduction aided precoding for multiantenna broadcast"

Connected through hyperedge HE-4 (induced by source paper "vlsi design of a nonparametric equalizer for massive mu mimo"):
  with members:
    - "1 bit massive mu mimo precoding in vlsi"
    - "optimally tuned nonparametric linear equalization for massive mu mimo systems"
    - "data detection in large multi antenna wireless systems via approximate semidefinite relaxation"
    - "large scale mimo detection for 3gpp lte algorithms and fpga implementations"
    - "massive mimo systems with non ideal hardware energy efficiency estimation and capacity limits"
    - "massive mimo for next generation wireless systems"
    - "what will 5g be"
    - "massive mimo how many antennas do we need"

Connected through hyperedge HE-5 (induced by source paper "on the achievable rates of decentralized equalization in massive mu mimo systems"):
  with members:
    - "performance trade offs in multi processor approximate message passing"
    - "optimality of large mimo detection via approximate message passing"
    - "system architecture and key technologies for 5g heterogeneous cloud radio access networks"
    - "massive mimo for next generation wireless systems"
    - "what will 5g be"
    - "massive mimo how many antennas do we need"
    - "the dynamics of message passing on dense graphs with applications to compressed sensing"
    - "estimation in gaussian noise properties of the minimum mean square error"

Connected through hyperedge HE-6 (induced by source paper "decentralized baseband processing for massive mu mimo systems"):
  with members:
    - "on the achievable rates of decentralized equalization in massive mu mimo systems"
    - "ber analysis of the box relaxation for bpsk signal recovery"
    - "system architecture and key technologies for 5g heterogeneous cloud radio access networks"
    - "linear large scale mimo data detection for 5g multi carrier waveform candidates"
    - "large scale mimo detection for 3gpp lte algorithms and fpga implementations"
    - "conjugate gradient based soft output detection and precoding in massive mimo systems"
    - "massive mimo for next generation wireless systems"
    - "distributed robust multicell coordinated beamforming with imperfect csi an admm approach"

Connected through hyperedge HE-7 (induced by source paper "optimally tuned nonparametric linear equalization for massive mu mimo systems"):
  with members:
    - "massive mimo for next generation wireless systems"
    - "what will 5g be"
    - "massive mimo how many antennas do we need"
    - "mimo transmission with residual transmit rf impairments"
    - "generalized approximate message passing for estimation with random linear mixing"
    - "asymptotic performance of linear receivers in mimo fading channels"
    - "randomly spread cdma asymptotics via statistical physics"

Connected through hyperedge HE-8 (induced by source paper "approximate gram matrix interpolation for wideband massive mu mimo"):
  with members:
    - "nr wide bandwidth operations"
    - "on the achievable rates of decentralized equalization in massive mu mimo systems"
    - "large scale mimo detection for 3gpp lte algorithms and fpga implementations"
    - "conjugate gradient based soft output detection and precoding in massive mimo systems"
    - "massive mimo for next generation wireless systems"
    - "channel hardening exploiting message passing chemp receiver in large scale mimo systems"
    - "scaling up mimo opportunities and challenges with very large arrays"
    - "per antenna constant envelope precoding for large multi user mimo 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)