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: "anytime coding on the infinite bandwidth awgn channel a sequential semi orthogonal optimal code"
  Abstract: It is well known that orthogonal coding can be used to approach the Shannon capacity of the power-constrained AWGN channel without a bandwidth constraint. This correspondence describes a semi-orthogonal variation of pulse position modulation that is sequential in nature -- bits can be ``streamed across'' without having to buffer up blocks of bits at the transmitter. ML decoding results in an exponentially small probability of error as a function of tolerated receiver delay and thus eventually a zero probability of error on every transmitted bit. In the high-rate regime, a matching upper bound is given on the delay error exponent. We close with some comments on the case with feedback and the connections to the capacity per unit cost problem.

Connected through hyperedge HE-1 (induced by source paper "the streaming dmt of fading channels"):
  with members:
    - "erasure coding for real time streaming"
    - "streaming codes for channels with burst and isolated erasures"
    - "linear error correcting codes with anytime reliability"
    - "diversity embedded streaming erasure codes de sco constructions and optimality"
    - "on successive refinement of diversity for fading isi channels"
    - "distortion minimization in gaussian layered broadcast coding with successive refinement"
    - "high snr analysis of outage limited communications with bursty and delay limited information"
    - "on the distortion snr exponent of some layered transmission schemes"

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)