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: "iterative channel estimation using lse and sparse message passing for mmwave mimo systems"
  Abstract: We propose an iterative channel estimation algorithm based on the Least Square Estimation (LSE) and Sparse Message Passing (SMP) algorithm for the Millimeter Wave (mmWave) MIMO systems. The channel coefficients of the mmWave MIMO are approximately modeled as a Bernoulli-Gaussian distribution since there are relatively fewer paths in the mmWave channel, i.e., the channel matrix is sparse and only has a few non-zero entries. By leveraging the advantage of sparseness, we proposed an algorithm that iteratively detects the exact location and value of non-zero entries of the sparse channel matrix. The SMP is used to detect the exact location of non-zero entries of the channel matrix, while the LSE is used for estimating its value at each iteration. We also analyze the Cramer-Rao Lower Bound (CLRB), and show that the proposed algorithm is a minimum variance unbiased estimator. Furthermore, we employ the Gaussian approximation for message densities under density evolution to simplify the analysis of the algorithm, which provides a simple method to predict the performance of the proposed algorithm. Numerical experiments show that the proposed algorithm has much better performance than the existing sparse estimators, especially when the channel is sparse. In addition, our proposed algorithm converges to the CRLB of the genie-aided estimation of sparse channels in just 5 turbo iterations.

Connected through hyperedge HE-1 (induced by source paper "principal component analysis based broadband hybrid precoding for millimeter wave massive mimo systems"):
  with members:
    - "closed loop sparse channel estimation for wideband millimeter wave full dimensional mimo systems"
    - "periodic analog channel estimation aided beamforming for massive mimo systems"
    - "device to device communications enabled energy efficient multicast scheduling in mmwave small cells"
    - "energy efficient multi user miso communication using low resolution large intelligent surfaces"
    - "wideband hybrid precoding for next generation backhaul fronthaul based on mmwave fd mimo"
    - "hybrid beamforming with selection for multiuser massive mimo systems"
    - "massive mimo channel estimation for millimeter wave systems via matrix completion"
    - "stochastic successive convex optimization for two timescale hybrid precoding in massive mimo"

Connected through hyperedge HE-2 (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"
    - "convergence analysis and assurance for gaussian message passing iterative detector in massive mu mimo systems"
    - "low rank tensor decomposition aided channel estimation for millimeter wave mimo ofdm systems"
    - "channel estimation in broadband millimeter wave mimo systems with few bit adcs"

Connected through hyperedge HE-3 (induced by source paper "deep learning for ul dl channel calibration in generic massive mimo systems"):
  with members:
    - "energy efficient multi user miso communication using low resolution large intelligent surfaces"
    - "achievable rate maximization by passive intelligent mirrors"
    - "asymptotically optimal estimation algorithm for the sparse signal with arbitrary distributions"
    - "a framework for over the air reciprocity calibration for tdd massive mimo systems"
    - "neural offset min sum decoding"
    - "reciprocity calibration for massive mimo proposal modeling and validation"
    - "learning to communicate channel auto encoders domain specific regularizers and attention"
    - "effective approaches to attention based neural machine translation"

Connected through hyperedge HE-4 (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"
    - "convergence analysis and assurance for gaussian message passing iterative detector in massive mu 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-5 (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"
    - "convergence analysis and assurance for gaussian message passing iterative detector in massive mu mimo systems"
    - "coded slotted aloha a graph based method for uncoordinated multiple access"

Connected through hyperedge HE-6 (induced by source paper "cascaded channel estimation for large intelligent metasurface assisted massive mimo"):
  with members:
    - "enabling large intelligent surfaces with compressive sensing and deep learning"
    - "intelligent reflecting surface enhanced wireless network via joint active and passive beamforming"
    - "beyond massive mimo the potential of data transmission with large intelligent surfaces"
    - "super resolution blind channel and signal estimation for massive mimo with arbitrary array geometry"
    - "reconfigurable intelligent surfaces for energy efficiency in wireless communication"
    - "structured compressive sensing based spatio temporal joint channel estimation for fdd massive mimo"
    - "spatially common sparsity based adaptive channel estimation and feedback for fdd massive mimo"
    - "bilinear generalized approximate message passing part i derivation"

Connected through hyperedge HE-7 (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"
    - "convergence analysis and assurance for gaussian message passing iterative detector in massive mu mimo systems"

Connected through hyperedge HE-8 (induced by source paper "decentralized consensus optimization based on parallel random walk"):
  with members:
    - "massive mimo channel estimation for millimeter wave systems via matrix completion"
    - "asynchronous distributed admm for large scale optimization part i algorithm and convergence analysis"

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)