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 "channel sensing and communication over a time correlated channel with an energy harvesting transmitter"):
  Abstract: An energy harvesting (EH) transmitter communicating over a time-correlated wireless channel is considered. The transmitter is capable of sensing the current channel state, albeit at the cost of both energy and transmission time. The EH transmitter aims to maximize its long-term throughput by choosing one of the following actions: 1) defer its transmission to save energy for future use; 2) transmit reliably at a low rate; 3) transmit at a high rate; and 4) sense the channel to reveal the channel state at a cost of energy and transmission time, and then decide to defer or to transmit. The problem is formulated as a partially observable Markov decision process with a belief on the channel state. The optimal policy is shown to exhibit a threshold behavior on the belief state, with battery-dependent threshold values. The optimal threshold values and performance are characterized numerically via the value iteration algorithm as well as a policy search algorithm that exploits the threshold structure of the optimal policy. Our results demonstrate that, despite the associated time and energy cost, sensing the channel intelligently to track the channel state improves the achievable long-term throughput significantly as compared to the performance of those protocols lacking this ability as well as the one that always senses the channel.

Includes members:
  Member "energy harvesting wireless networks with correlated energy sources":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "communication over a time correlated channel with an energy harvesting transmitter")
  Member "distributed opportunistic scheduling for energy harvesting based wireless networks a two stage probing approach":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "communication over a time correlated channel with an energy harvesting transmitter")
  Member "optimization of energy harvesting miso communication system with feedback":
    also connected through other hyperedges:
      (none)
  Member "multi access communications with energy harvesting a multi armed bandit model and the optimality of the myopic policy":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "distributed power control for large energy harvesting networks a multi agent deep reinforcement learning approach")
  Member "universally near optimal online power control for energy harvesting nodes":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "a maximin optimal online power control policy for energy harvesting communications")
  Member "stability analysis of slotted aloha with opportunistic rf energy harvesting":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "proportional fairness in aloha networks with rf energy harvesting")
  Member "data driven stochastic models and policies for energy harvesting sensor communications":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "communication over a time correlated channel with an energy harvesting transmitter")
  Member "a learning theoretic approach to energy harvesting communication system optimization":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "a survey on machine learning based performance improvement of wireless networks phy mac and network layer")

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)