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: "delayed channel state information incremental redundancy with backtrack retransmission"
  Abstract: In many practical wireless systems, the Signal-to-Interference-and-Noise Ratio (SINR) that is applicable to a certain transmission, referred to as Channel State Information (CSI), can only be learned after the transmission has taken place and is thereby outdated (delayed). For example, this occurs under intermittent interference. We devise the backward retransmission (BRQ) scheme, which uses the delayed CSIT to send the optimal amount of incremental redundancy (IR). BRQ uses fixed-length packets, fixed-rate R transmission codebook, and operates as Markov block coding, where the correlation between the adjacent packets depends on the amount of IR parity bits. When the delayed CSIT is full and R grows asymptotically, the average throughput of BRQ becomes equal to the value achieved with prior CSIT and a fixed-power transmitter; however, at the expense of increased delay. The second contribution is a method for employing BRQ when a limited number of feedback bits is available to report the delayed CSIT. The main novelty is the idea to assemble multiple feedback opportunities and report multiple SINRs through vector quantization. This challenges the conventional wisdom in ARQ protocols where feedback bits are used to only quantize the CSIT of the immediate previous transmission.

Connected through hyperedge HE-1 (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"
    - "adaptive cross packet harq"
    - "performance of hybrid arq in block fading channels a fixed outage probability analysis"

Connected through hyperedge HE-2 (induced by source paper "generalized harq protocols with delayed channel state information and average latency constraints"):
  with members:
    - "block fading channels with delayed csit at finite blocklength"
    - "the streaming dmt of fading channels"
    - "variable rate retransmissions for incremental redundancy hybrid arq"
    - "on the benefits of partial channel state information for repetition protocols in block fading channels"
    - "completely stale transmitter channel state information is still very useful"

Connected through hyperedge HE-3 (induced by source paper "adaptive cross packet harq"):
  with members:
    - "how to boost the throughput of harq with off the shelf codes"
    - "harq and amc friends or foes"
    - "rate adaptation for secure harq protocols"
    - "harq buffer management an information theoretic view"
    - "block fading channels with delayed csit at finite blocklength"
    - "on the benefits of partial channel state information for repetition protocols in block fading channels"
    - "mimo arq with multi bit feedback outage analysis"
    - "performance of hybrid arq in block fading channels a fixed outage probability analysis"

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"
    - "adaptive cross packet harq"
    - "harq buffer management an information theoretic view"
    - "inter frame coding for broadcast communication"
    - "block fading channels with delayed csit at finite blocklength"

Connected through hyperedge HE-5 (induced by source paper "block fading channels with delayed csit at finite blocklength"):
  with members:
    - "quasi static simo fading channels 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)