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: "on the impact of optimal modulation and fec overhead on future optical networks"
  Abstract: The potential of optimum selection of modulation and forward error correction (FEC) overhead (OH) in future wavelength-routed nonlinear optical mesh networks is studied from an information theory perspective. Different network topologies are studied as well as both ideal soft-decision (SD) and hard-decision (HD) FEC based on demap-and-decode (bit wise) receivers. When compared to the somewhat standard assumption of QPSK with 7% OH, the results show large gains in network throughput. When compared to SD-FEC, HD-FEC is shown to cause network throughput losses of   $12$  %,    $15$  %, and    $20$  % for a national, continental, and transcontinental topology, respectively. Furthermore, it is shown that for national and continental network topologies, using one modulation format and only two OHs achieves at least   $75\%$   of the maximum theoretical throughput. This is in contrast with the infinite number of OHs required in the ideal case. The obtained optimal OHs are between   $5$  % and   $80\%$  , highlighting the advantage of using FEC with high OHs.

Connected through hyperedge HE-1 (induced by source paper "an experimental comparison of coded modulation strategies for 100 gb s transceivers"):
  with members:
    - "performance prediction of nonbinary forward error correction in optical transmission experiments"
    - "impact of 4d channel distribution on the achievable rates in coherent optical communication experiments"

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)