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: "comparison of ofdm and sc dfe capacities without channel knowledge at the transmitter"
  Abstract: This letter provides a capacity analysis between OFDM and the ideal SC-DFE when no channel knowledge is available at the transmitter. Through some algebraic manipulation of the OFDM and SC-DFE capacities and using the concavity property of the manipulated capacity function and Jensen's inequality, we are able to prove that the SC-DFE capacity is always superior to that of an OFDM scheme for 4- and 16-QAM for any given channel. For higher-order modulations, however, the results indicate that OFDM may only surpass the ideal SC-DFE capacity by a small amount in some specific scenarios.

Connected through hyperedge HE-1 (induced by source paper "comparison of the achievable rates in ofdm and single carrier modulation with i i d inputs"):
  with members:
    - "lower bounds and approximations for the information rate of the isi channel"
    - "high snr asymptotics of mutual information for discrete constellations with applications to bicm"
    - "easily computed lower bounds on the information rate of intersymbol interference channels"
    - "spatially coupled codes and threshold saturation on intersymbol interference channels"
    - "estimation in gaussian noise properties of the minimum mean square error"
    - "hessian and concavity of mutual information differential entropy and entropy power in linear vector gaussian channels"
    - "mutual information and minimum mean square error in gaussian channels"

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)