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: "communication under strong asynchronism"
  Abstract: We consider asynchronous communication over point-to-point discrete memoryless channels. The transmitter starts sending one block codeword at an instant that is uniformly distributed within a certain time period, which represents the level of asynchronism. The receiver, by means of a sequential decoder, must isolate the message without knowing when the codeword transmission starts but being cognizant of the asynchronism level A. We are interested in how quickly can the receiver isolate the sent message, particularly in the regime where A is exponentially larger than the codeword length N, which we refer to as `strong asynchronism.' #R##N#This model of sparse communication may represent the situation of a sensor that remains idle most of the time and, only occasionally, transmits information to a remote base station which needs to quickly take action. #R##N#The first result shows that vanishing error probability can be guaranteed as N tends to infinity while A grows as Exp(N*k) if and only if k does not exceed the `synchronization threshold,' a constant that admits a simple closed form expression, and is at least as large as the capacity of the synchronized channel. The second result is the characterization of a set of achievable strictly positive rates in the regime where A is exponential in N, and where the rate is defined with respect to the expected delay between the time information starts being emitted until the time the receiver makes a decision. #R##N#As an application of the first result we consider antipodal signaling over a Gaussian channel and derive a simple necessary condition between A, N, and SNR for achieving reliable communication.

Connected through hyperedge HE-1 (induced by source paper "on the reliability function of distributed hypothesis testing under optimal detection"):
  with members:
    - "on hypothesis testing against independence with multiple decision centers"
    - "on binary distributed hypothesis testing"
    - "distributed hypothesis testing over noisy channels"
    - "hypothesis testing over the two hop relay network"
    - "a large deviations approach to secure lossy compression"
    - "distributed binary detection with lossy data compression"
    - "neyman pearson test for zero rate multiterminal hypothesis testing"
    - "collaborative distributed hypothesis testing"

Connected through hyperedge HE-2 (induced by source paper "short packet structure for ultra reliable machine type communication tradeoff between detection and decoding"):
  with members:
    - "short codes with mismatched channel state information a case study"
    - "wireless access for ultra reliable low latency communication urllc principles and building blocks"
    - "low latency ultra reliable 5g communications finite blocklength bounds and coding schemes"

Connected through hyperedge HE-3 (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"
    - "optimal sequential frame synchronization"

Connected through hyperedge HE-4 (induced by source paper "a general characterization of sync word for asynchronous communication"):
  with members:
    - "optimal sequential frame synchronization"

Connected through hyperedge HE-5 (induced by source paper "channel detection in coded communication"):
  with members:
    - "quickest transient change detection under a sampling constraint"
    - "sampling constrained asynchronous communication how to sleep efficiently"
    - "on zero rate error exponents of finite state channels with input dependent states"
    - "simplified erasure list decoding"
    - "list decoding random coding exponents and expurgated exponents"
    - "asymptotically optimal decision rules for joint detection and source coding"
    - "exact random coding error exponents of optimal bin index decoding"
    - "erasure list random coding error exponents are not universally achievable"

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"
    - "optimal sequential frame synchronization"

Connected through hyperedge HE-7 (induced by source paper "asynchronous communication over a fading channel and additive noise"):
  with members:
    - "optimal sequential frame synchronization"

Connected through hyperedge HE-8 (induced by source paper "time asynchronous gaussian multiple access relay channel with correlated sources"):
  with members:
    - "asynchronous transmission over single user state dependent channels"
    - "on joint source channel coding for correlated sources over multiple access relay channels"
    - "source channel coding theorems for the multiple access relay channel"
    - "optimality and approximate optimality of source channel separation in networks"

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)