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: "optimal sequential frame synchronization"
  Abstract: We consider the `one-shot frame synchronization problem' where a decoder wants to locate a sync pattern at the output of a channel on the basis of sequential observations. We assume that the sync pattern of length N starts being emitted at a random time within some interval of size A, that characterizes the asynchronism level between the transmitter and the receiver. We show that a sequential decoder can optimally locate the sync pattern, i.e., exactly, without delay, and with probability approaching one as N tends to infinity, if and only if the asynchronism level grows as O(exp(N*k)), with k below the `synchronization threshold,' a constant that admits a simple expression depending on the channel. This constant is the same as the one that characterizes the limit for reliable asynchronous communication, as was recently reported by the authors. If k exceeds the synchronization threshold, any decoder, sequential or non-sequential, locates the sync pattern with an error that tends to one as N tends to infinity. Hence, a sequential decoder can locate a sync pattern as well as the (non-sequential) maximum likelihood decoder that operates on the basis of output sequences of maximum length A+N-1, but with much fewer observations.

Connected through hyperedge HE-1 (induced by source paper "the strongly asynchronous massive access channel"):
  with members:
    - "on the capacity of the slotted strongly asynchronous channel with a bursty user"
    - "capacity of gaussian many access channels"
    - "asymptotically optimal matching of multiple sequences to source distributions and training sequences"
    - "energy and sampling constrained asynchronous communication"
    - "asynchronous communication capacity bounds and suboptimality of training"

Connected through hyperedge HE-2 (induced by source paper "second order asymptotics for communication under strong asynchronism"):
  with members:
    - "sampling constrained asynchronous communication how to sleep efficiently"
    - "channel detection in coded communication"
    - "asynchronous communication capacity bounds and suboptimality of training"
    - "asynchronous capacity per unit cost"
    - "communication under strong asynchronism"

Connected through hyperedge HE-3 (induced by source paper "on the capacity of the slotted strongly asynchronous channel with a bursty user"):
  with members:
    - "energy and sampling constrained asynchronous communication"
    - "asynchronous communication capacity bounds and suboptimality of training"
    - "asynchronous capacity per unit cost"

Connected through hyperedge HE-4 (induced by source paper "asynchronous transmission over gaussian interference channels with stochastic data arrival"):
  with members:
    - "a relay can increase degrees of freedom in bursty mimo interference networks"
    - "random access an information theoretic perspective"
    - "gaussian interference channel capacity to within one bit"

Connected through hyperedge HE-5 (induced by source paper "a general characterization of sync word for asynchronous communication"):
  with members:
    - "communication under strong asynchronism"

Connected through hyperedge HE-6 (induced by source paper "sampling constrained asynchronous communication how to sleep efficiently"):
  with members:
    - "energy and sampling constrained asynchronous communication"
    - "asynchronous communication capacity bounds and suboptimality of training"
    - "asynchronous capacity per unit cost"
    - "communication under strong asynchronism"

Connected through hyperedge HE-7 (induced by source paper "asynchronous communication over a fading channel and additive noise"):
  with members:
    - "communication under strong asynchronism"

Connected through hyperedge HE-8 (induced by source paper "energy and sampling constrained asynchronous communication"):
  with members:
    - "energy efficient communication in the presence of synchronization errors"
    - "asynchronous communication capacity bounds and suboptimality of training"
    - "asynchronous capacity per unit cost"
    - "communication under strong asynchronism"

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)