human: Given a hyperedge-centered hypergraph: <hypergraph>, where the center hyperedge is induced by one source paper and its member nodes are the cited papers.

Details of the hypergraph:
Center hyperedge (induced by source paper "optimal spectrum sharing with arq based legacy users via chain decoding"):
  Abstract: This paper investigates the design of access policies in spectrum sharing networks by exploiting the retransmission protocol of legacy primary users (PUs) to improve the spectral efficiency via opportunistic retransmissions at secondary users (SUs) and chain decoding [1]. The optimal access policy which maximizes the SU throughput under a maximum interference constraint to the PU and its performance are found in closed form. It is shown that the optimal policy randomizes among three modes: 1) Idle: the SU remains idle over the retransmission window of the PU, to avoid interfering; 2) Interference cancellation: the SU transmits only after decoding the PU packet, to improve its own throughput via interference cancellation; 3) Always transmit: the SU transmits over the retransmission window of the PU to maximize the future potential of interference cancellation via chain decoding. This structure is exploited to design a stochastic gradient descent algorithm to facilitate learning and adaptation in settings where the model parameters are unknown or vary over time, based on ARQ feedback from the PU and CSI measurements at the SU receiver. It is shown numerically that, for a 10\% interference constraint, the optimal access policy yields 15\% improvement over a state-of-the-art scheme without selective SU retransmissions, and up to $2\times$ gain over a scheme using a non-adaptive access policy instead of the optimal one.

Includes members:
  Member "deep neural network architectures for modulation classification":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "a survey on machine learning based performance improvement of wireless networks phy mac and network layer")
  Member "on stable throughput of cognitive radio networks with cooperating secondary users":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "stable throughput of cooperative cognitive networks with energy harvesting finite relay buffer and finite battery capacity")
  Member "cross layer estimation and control for cognitive radio exploiting sparse network dynamics":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "thirty years of machine learning the road to pareto optimal next generation wireless networks")
  Member "cognitive access policies under a primary arq process via forward backward interference cancellation":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "cognitive access transmission policies under a primary arq process via chain decoding")
  Member "blind known interference cancellation":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "approaching single hop performance in multihop networks end to end known interference cancelation e2e kic")
  Member "cognitive interference management in retransmission based wireless networks":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "cross layer estimation and control for cognitive radio exploiting sparse network dynamics")
  Member "on active learning and supervised transmission of spectrum sharing based cognitive radios by exploiting hidden primary radio feedback":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "neural network cognitive engine for autonomous and distributed underlay dynamic spectrum access")
  Member "cognitive radio an information theoretic perspective":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "cognitive radio networks an information theoretic perspective")

Question: Please tell me which class the source paper 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)