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: "super resolution sparse mimo ofdm channel estimation based on spatial and temporal correlations"
  Abstract: This letter proposes a parametric sparse multiple input multiple output (MIMO)-OFDM channel estimation scheme based on the finite rate of innovation (FRI) theory, whereby super-resolution estimates of path delays with arbitrary values can be achieved. Meanwhile, both the spatial and temporal correlations of wireless MIMO channels are exploited to improve the accuracy of the channel estimation. For outdoor communication scenarios, where wireless channels are sparse in nature, path delays of different transmit-receive antenna pairs share a common sparse pattern due to the spatial correlation of MIMO channels. Meanwhile, the channel sparse pattern is nearly unchanged during several adjacent OFDM symbols due to the temporal correlation of MIMO channels. By simultaneously exploiting those MIMO channel characteristics, the proposed scheme performs better than existing state-of-the-art schemes. Furthermore, by joint processing of signals associated with different antennas, the pilot overhead can be reduced under the framework of the FRI theory.

Connected through hyperedge HE-1 (induced by source paper "robustness of two dimensional line spectral estimation against spiky noise"):
  with members:
    - "two dimensional super resolution via convex relaxation"
    - "off the grid two dimensional line spectral estimation with prior information"
    - "generalized line spectral estimation via convex optimization"
    - "robust spectral compressed sensing via structured matrix completion"
    - "spectral super resolution with prior knowledge"
    - "atomic norm denoising with applications to line spectral estimation"
    - "super resolution from noisy data"
    - "towards a mathematical theory of super resolution"

Connected through hyperedge HE-2 (induced by source paper "structured compressive sensing based spatio temporal joint channel estimation for fdd massive mimo"):
  with members:
    - "joint csit acquisition based on low rank matrix completion for fdd massive mimo systems"
    - "asymptotic orthogonality analysis of time domain sparse massive mimo channels"
    - "spatially common sparsity based adaptive channel estimation and feedback for fdd massive mimo"
    - "priori information aided iterative hard threshold a low complexity high accuracy compressive sensing based channel estimation for tds ofdm"
    - "structured compressive sensing based superimposed pilot design in downlink large scale mimo systems"
    - "massive mimo systems with non ideal hardware energy efficiency estimation and capacity limits"
    - "massive mimo for next generation wireless systems"
    - "downlink training techniques for fdd massive mimo systems open loop and closed loop training with memory"

Connected through hyperedge HE-3 (induced by source paper "a low complexity transceiver design in sparse multipath massive mimo channels"):
  with members:
    - "spatially common sparsity based adaptive channel estimation and feedback for fdd massive mimo"
    - "massive mimo for next generation wireless systems"

Connected through hyperedge HE-4 (induced by source paper "large system analysis of cognitive radio network via partially projected regularized zero forcing precoding"):
  with members:
    - "joint beamforming and power control in coordinated multicell max min duality effective network and large system transition"
    - "multi pair amplify and forward relaying with very large antenna arrays"
    - "large system analysis of cooperative multi cell downlink transmission via regularized channel inversion with imperfect csit"
    - "optimal power allocation and user loading for multiuser miso channels with regularized channel inversion"
    - "on capacity of large scale mimo multiple access channels with distributed sets of correlated antennas"
    - "large system analysis of linear precoding in miso broadcast channels with confidential messages"
    - "message passing algorithm for distributed downlink regularized zero forcing beamforming with cooperative base stations"
    - "random beamforming over quasi static and fading channels a deterministic equivalent approach"

Connected through hyperedge HE-5 (induced by source paper "asymptotic orthogonality analysis of time domain sparse massive mimo channels"):
  with members:
    - "space constrained massive mimo hitting the wall of favorable propagation"
    - "scaling up mimo opportunities and challenges with very large arrays"
    - "estimation of sparse mimo channels with common support"

Connected through hyperedge HE-6 (induced by source paper "robust preamble design for synchronization signaling transmission and channel estimation"):
  with members:
    - "priori information aided iterative hard threshold a low complexity high accuracy compressive sensing based channel estimation for tds ofdm"
    - "structured compressive sensing based superimposed pilot design in downlink large scale mimo systems"
    - "frequency domain response based timing synchronization a near optimal sampling phase criterion for tds ofdm"

Connected through hyperedge HE-7 (induced by source paper "improved adaptive sparse channel estimation using re weighted l1 norm normalized least mean fourth algorithm"):
  with members:
    - "rza nlmf algorithm based adaptive sparse sensing for realizing compressive sensing"

Connected through hyperedge HE-8 (induced by source paper "regularization parameter selection method for sign lms with reweighted l1 norm constriant algorithm"):
  with members:
    - "compressive estimation of doubly selective channels in multicarrier systems leakage effects and sparsity enhancing processing"

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)