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: "adaptive cross packet harq"
  Abstract: In this work, we investigate a coding strategy devised to increase the throughput in hybrid ARQ (HARQ) transmission over block fading channel. In our approach, the transmitter jointly encodes a variable number of bits for each round of HARQ. The parameters (rates) of this joint coding can vary and may be based on the negative acknowledgment (NACK) provided by the receiver or, on the past (outdated) information about the channel states. These new degrees of freedom allow us to improve the match between the codebook and the channel states experienced by the receiver. The results indicate that significant gains can be obtained using the proposed coding strategy, particularly notable when the conventional HARQ fails to offer throughput improvement even if the number of transmission rounds is increased. The new cross-packet HARQ is also implemented using turbo codes where we show that the theoretically predicted throughput gains materialize in practice, and we discuss the implementation challenges.

Connected through hyperedge HE-1 (induced by source paper "effective capacity for renewal service processes with applications to harq systems"):
  with members:
    - "effective capacity in wireless networks a comprehensive survey"
    - "asymptotic outage analysis of harq ir over time correlated nakagami m fading channels"
    - "effective capacity of retransmission schemes a recurrence relation approach"
    - "energy efficiency of hybrid arq under statistical queuing constraints"
    - "ultra reliable communication in 5g wireless systems"
    - "effective capacity of delay constrained cognitive radio links exploiting primary feedback"

Connected through hyperedge HE-2 (induced by source paper "amc and harq how to increase the throughput"):
  with members:
    - "generalized harq protocols with delayed channel state information and average latency constraints"
    - "how to boost the throughput of harq with off the shelf codes"
    - "harq and amc friends or foes"
    - "delayed channel state information incremental redundancy with backtrack retransmission"
    - "performance of hybrid arq in block fading channels a fixed outage probability analysis"

Connected through hyperedge HE-3 (induced by source paper "rate adaptation for secure harq protocols"):
  with members:
    - "fundamental limits of communication with low probability of detection"
    - "covert communication over noisy channels a resolvability perspective"
    - "harq buffer management an information theoretic view"
    - "semantic security capacity for wiretap channels of type ii"
    - "block fading channels with delayed csit at finite blocklength"
    - "effective secrecy reliability confusion and stealth"
    - "coding with scrambling concatenation and harq for the awgn wire tap channel a security gap analysis"
    - "rethinking the secrecy outage formulation a secure transmission design perspective"

Connected through hyperedge HE-4 (induced by source paper "how to boost the throughput of harq with off the shelf codes"):
  with members:
    - "harq and amc friends or foes"
    - "harq buffer management an information theoretic view"
    - "inter frame coding for broadcast communication"
    - "delayed channel state information incremental redundancy with backtrack retransmission"
    - "block fading channels with delayed csit at finite blocklength"

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)