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: "accurate sampling timing acquisition for baseband ofdm power line communication in non gaussian noise"
  Abstract: In this paper, a novel technique is proposed to address the joint sampling timing acquisition for baseband and broadband power-line communication (BB-PLC) systems using Orthogonal-Frequency-Division-Multiplexing (OFDM), including the sampling phase offset (SPO) and the sampling clock offset (SCO). Under pairwise correlation and joint Gaussian assumption of received signals in frequency domain, an approximated form of the log-likelihood function is derived. Instead of a high complexity two-dimension grid-search on the likelihood function, a five-step method is employed for accurate estimations. Several variants are presented in the same framework with different complexities. Unlike conventional pilot-assisted schemes using the extra phase rotations within one OFDM block, the proposed technique turns to the phase rotations between adjacent OFDM blocks. Analytical expressions of the variances and biases are derived. Extensive simulation results indicate significant performance improvements over conventional schemes. Additionally, effects of several noise models including non-Gaussianity, cyclo-stationarity, and temporal correlation are analyzed and simulated. Robustness of the proposed technique against violation of the joint Gaussian assumption is also verified by simulations.

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)