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: "massive mimo as a big data system random matrix models and testbed"
  Abstract: The paper has two parts. The first one deals with how to use large random matrices as building blocks to model the massive data arising from the massive (or large-scale) MIMO system. As a result, we apply this model for distributed spectrum sensing and network monitoring. The part boils down to the streaming, distributed massive data, for which a new algorithm is obtained and its performance is derived using the central limit theorem that is recently obtained in the literature. The second part deals with the large-scale testbed using software-defined radios (particularly USRP) that takes us more than four years to develop this 70-node network testbed. To demonstrate the power of the software defined radio, we reconfigure our testbed quickly into a testbed for massive MIMO. The massive data of this testbed is of central interest in this paper. It is for the first time for us to model the experimental data arising from this testbed. To our best knowledge, we are not aware of other similar work.

Connected through hyperedge HE-1 (induced by source paper "positive definite estimation of large covariance matrix using generalized nonconvex penalties"):
  with members:
    - "sub nyquist sampling for power spectrum sensing in cognitive radios a unified approach"
    - "recovery of sparse matrices via matrix sketching"
    - "sketching sparse matrices"

Connected through hyperedge HE-2 (induced by source paper "uplink one tone filtered multitone modulation transmission for machine type communications"):
  with members:
    - "asymptotic analysis of a glrt test for detection with large sensor arrays"

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)