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Center node: "the impact of outdated csi on the finite blocklength performance of relaying"
  Abstract: Under the assumption of outdated channel state information (CSI) at the source, we study the blocklength-limited throughput (BL-throughput) of a two-hop relaying network. We introduce SNR weights to let the source choose a relatively lower coding rate based on the weighted outdated SNR. Both a fixed weight scheme and a dynamic weight scheme are studied. We derive the expected BL-throughput of a transmission period based on the corresponding outdated CSI and compare it with the ergodic BL-throughput over channel fading. In particular, we prove that under the dynamic SNR weight scheme the BL-throughput of an upcoming transmission is concave in the coding rate and quasi-concave in the SNR weights. In addition, under the fixed SNR weight scheme we show that the average BL-throughput over time is quasi-concave in these weights. Through numerical investigations, we show the appropriateness of our theoretical model. In addition, we study the performance difference between the dynamic and the fixed weight schemes. We show numerically that relaying outperforms direct transmission under the finite blocklength regime for cases where both systems have similar performance with respect to Shannon capacity. These results indicate that as the blocklength decreases, relaying has a increasing performance advantage over direct transmission despite its inherent reduction in the transmit times.

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)