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: "convergence analysis and assurance for gaussian message passing iterative detector in massive mu mimo systems"
  Abstract: This paper considers a low-complexity Gaussian message passing iterative detection (GMPID) algorithm for a massive multiuser multiple-input multiple-output (MU-MIMO) system, in which a base station with    $M$    antennas serves    $K$    Gaussian sources simultaneously. Both    $K$    and    $M$    are very large numbers, and we consider the cases that    $K  . The GMPID is a message passing algorithm operating on a fully connected loopy graph, which is well understood to be non-convergent in some cases. As it is hard to analyze the GMPID directly, the large-scale property of the massive MU-MIMO is used to simplify the analysis. First, we prove that the variances of the GMPID definitely converge to the mean square error of minimum mean square error (mmse) detection. Second, we derive two sufficient conditions that make the means of the GMPID converge to those of the mmse detection. However, the means of GMPID may not converge when    $ K/M\geq (\sqrt {2}-1)^{2}$   . Therefore, a modified GMPID called scale-and-add GMPID, which converges to the mmse detection in mean and variance for any    $K  , and has a faster convergence speed than the GMPID, but has no higher complexity than the GMPID, is proposed. Finally, numerical results are provided to verify the validity and accuracy of the theoretical results.

Connected through hyperedge HE-1 (induced by source paper "generalized approximate message passing for massive mimo mmwave channel estimation with laplacian prior"):
  with members:
    - "sparse activity detection for massive connectivity"
    - "a lse and sparse message passing based channel estimation for mmwave mimo systems"
    - "bayes optimal joint channel and data estimation for massive mimo with low precision adcs"
    - "an overview of signal processing techniques for millimeter wave mimo systems"
    - "channel estimation for hybrid architecture based wideband millimeter wave systems"
    - "low rank tensor decomposition aided channel estimation for millimeter wave mimo ofdm systems"
    - "iterative channel estimation using lse and sparse message passing for mmwave mimo systems"
    - "channel estimation in broadband millimeter wave mimo systems with few bit adcs"

Connected through hyperedge HE-2 (induced by source paper "a new insight into gamp and amp"):
  with members:
    - "capacity achieving mimo noma iterative lmmse detection"
    - "capacity optimality of amp in coded systems"
    - "a unified bayesian inference framework for generalized linear models"
    - "bilinear adaptive generalized vector approximate message passing"
    - "gaussian message passing for overloaded massive mimo noma"
    - "massive connectivity with massive mimo part i device activity detection and channel estimation"
    - "beam on graph simultaneous channel estimation for mmwave mimo systems with multiple users"
    - "rigorous dynamics of expectation propagation based signal recovery from unitarily invariant measurements"

Connected through hyperedge HE-3 (induced by source paper "fixed symbol aided random access scheme for machine to machine communications"):
  with members:
    - "deep learning methods for improved decoding of linear codes"
    - "sparse message passing based preamble estimation for crowded m2m communications"
    - "massive connectivity with massive mimo part ii achievable rate characterization"
    - "massive connectivity with massive mimo part i device activity detection and channel estimation"
    - "irregular repetition slotted aloha over the rayleigh block fading channel with capture"
    - "iterative channel estimation using lse and sparse message passing for mmwave mimo systems"
    - "gaussian message passing iterative detection for mimo noma systems with massive access"
    - "coded slotted aloha a graph based method for uncoordinated multiple access"

Connected through hyperedge HE-4 (induced by source paper "dnn aided block sparse bayesian learning for user activity detection and channel estimation in grant free non orthogonal random access"):
  with members:
    - "a vision of 6g wireless systems applications trends technologies and open research problems"
    - "fixed symbol aided random access scheme for machine to machine communications"
    - "deep learning methods for improved decoding of linear codes"
    - "asymptotically optimal estimation algorithm for the sparse signal with arbitrary distributions"
    - "massive connectivity with massive mimo part ii achievable rate characterization"
    - "massive connectivity with massive mimo part i device activity detection and channel estimation"
    - "iterative channel estimation using lse and sparse message passing for mmwave mimo systems"
    - "coded slotted aloha a graph based method for uncoordinated multiple access"

Connected through hyperedge HE-5 (induced by source paper "dnn aided message passing based block sparse bayesian learning for joint user activity detection and channel estimation"):
  with members:
    - "asymptotically optimal estimation algorithm for the sparse signal with arbitrary distributions"
    - "massive connectivity with massive mimo part i device activity detection and channel estimation"
    - "iterative channel estimation using lse and sparse message passing for mmwave mimo systems"

Connected through hyperedge HE-6 (induced by source paper "probabilistic mimo symbol detection with expectation consistency approximate inference"):
  with members:
    - "capacity achieving iterative lmmse detection for mimo noma systems"
    - "gaussian message passing iterative detection for mimo noma systems with massive access"
    - "spatially coupled ldpc codes constructed from protographs"
    - "optimality of large mimo detection via approximate message passing"
    - "fifty years of mimo detection the road to large scale mimos"
    - "spatially coupled sparse codes on graphs theory and practice"
    - "channel hardening exploiting message passing chemp receiver in large scale mimo systems"
    - "expectation propagation for approximate bayesian inference"

Connected through hyperedge HE-7 (induced by source paper "gaussian message passing for overloaded massive mimo noma"):
  with members:
    - "mu mimo mac protocols for wireless local area networks a survey"
    - "capacity achieving iterative lmmse detection for mimo noma systems"
    - "gaussian message passing iterative detection for mimo noma systems with massive access"
    - "adaptive damping and mean removal for the generalized approximate message passing algorithm"
    - "a general mimo framework for noma downlink and uplink transmission based on signal alignment"
    - "s amp for non linear observation models"
    - "scaling up mimo opportunities and challenges with very large arrays"
    - "energy efficient sensing and communication of parallel gaussian sources"

Connected through hyperedge HE-8 (induced by source paper "asymptotically optimal estimation algorithm for the sparse signal with arbitrary distributions"):
  with members:
    - "a lse and sparse message passing based channel estimation for mmwave mimo systems"
    - "an overview of signal processing techniques for millimeter wave mimo systems"
    - "channel estimation in broadband millimeter wave mimo systems with few bit adcs"
    - "turbo compressed sensing with partial dft sensing matrix"
    - "channel estimation and hybrid precoding for millimeter wave cellular systems"
    - "approximate mmse estimator for linear dynamic systems with gaussian mixture noise"
    - "expectation maximization gaussian mixture approximate message passing"
    - "on the achievability of cramer rao bound in noisy compressed sensing"

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)