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: "low speed adc sampling based high resolution compressive channel estimation"
  Abstract: Broadband channel is often characterized by a sparse multipath channel where dominant multipath taps are widely separated in time, thereby resulting in a large delay spread. Traditionally, accurate channel estimation is done by sampling received signal by analog-to-digital converter (ADC) at Nyquist rate (high-speed ADC sampling) and then estimate all channel taps with high-resolution. However, traditional linear estimation methods have two mainly disadvantages: 1) demand of the high-speed ADC sampling rate which already exceeds the capability of current ADC and also the high-speed ADC is very expensive for regular wireless communications; 2) neglect the inherent channel sparsity and the low spectral efficiency wireless communication is unavoidable. To solve these challenges, in this paper, we propose a high-resolution compressive channel estimation method by using low-speed ADC sampling. Our proposed method can achieve close performance comparing with traditional sparse channel estimation methods. At the same time, the proposed method has following advantages: 1) reduce communication cost by utilizing cheap low-speed ADC; 2) improve spectral efficiency by extracting potential training signal resource. Numerical simulations confirm our proposed method using low-speed ADC sampling.

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)