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: "statistical mechanical analysis of the linear vector channel in digital communication"
  Abstract: A statistical mechanical framework to analyze linear vector channel models in digital wireless communication is proposed for a large system. The framework is a generalization of that proposed for code-division multiple-access systems in Takeda et al (2006 Europhys. Lett. 76 1193) and enables the analysis of the system in which the elements of the channel transfer matrix are statistically correlated with each other. The significance of the proposed scheme is demonstrated by assessing the performance of an existing model of multi-input multi-output communication systems.

Connected through hyperedge HE-1 (induced by source paper "large system analysis of correlated mimo multiple access channels with arbitrary signaling in the presence of interference"):
  with members:
    - "massive mimo for next generation wireless systems"
    - "blind pilot decontamination"
    - "scaling up mimo opportunities and challenges with very large arrays"
    - "on capacity of large scale mimo multiple access channels with distributed sets of correlated antennas"
    - "achieving massive mimo spectral efficiency with a not so large number of antennas"
    - "a deterministic equivalent for the analysis of correlated mimo multiple access channels"
    - "mimo networks the effects of interference"
    - "hessian and concavity of mutual information differential entropy and entropy power in linear vector gaussian channels"

Connected through hyperedge HE-2 (induced by source paper "statistical mechanical analysis of a typical reconstruction limit of compressed sensing"):
  with members:
    - "asymptotic analysis of map estimation via the replica method and applications to compressed sensing"
    - "statistical mechanical analysis of compressed sensing utilizing correlated compression matrix"
    - "a typical reconstruction limit of compressed sensing based on lp norm minimization"
    - "analysis of cdma systems that are characterized by eigenvalue spectrum"

Connected through hyperedge HE-3 (induced by source paper "statistical mechanical analysis of the kronecker channel model for multiple input multiple output wireless communication"):
  with members:
    - "an efficient cdma decoder for correlated information sources"
    - "vector precoding for wireless mimo systems and its replica analysis"
    - "analysis of cdma systems that are characterized by eigenvalue spectrum"
    - "randomly spread cdma asymptotics via statistical physics"
    - "improved message passing for inference in densely connected systems"

Connected through hyperedge HE-4 (induced by source paper "an integral formula for large random rectangular matrices and its application to analysis of linear vector channels"):
  with members:
    - "inference from correlated patterns a unified theory for perceptron learning and linear vector channels"
    - "randomly spread cdma asymptotics via statistical physics"
    - "improved message passing for inference in densely connected 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)