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 "capacity of the energy harvesting channel with a finite battery"):
  Abstract: We consider an energy harvesting channel, in which the transmitter is powered by an exogenous stochastic energy harvesting process $E_t$, such that $0\leq E_t\leq\bar{E}$, which can be stored in a battery of finite size $\bar{B}$. We provide a simple and insightful formula for the approximate capacity of this channel with bounded guarantee on the approximation gap independent of system parameters. This approximate characterization of the capacity identifies two qualitatively different operating regimes for this channel: in the large battery regime, when $\bar{B}\geq \bar{E}$, the capacity is approximately equal to that of an AWGN channel with an average power constraint equal to the average energy harvesting rate, i.e. it depends only on the mean of $E_t$ and is (almost) independent of the distribution of $E_t$ and the exact value of $\bar{B}$. In particular, this suggests that a battery size $\bar{B}\approx\bar{E}$ is approximately sufficient to extract the infinite battery capacity of the system. In the small battery regime, when $\bar{B}<\bar{E}$, we clarify the dependence of the capacity on the distribution of $E_t$ and the value of $\bar{B}$. There are three steps to proving this result which can be of interest in their own right: 1) we characterize the capacity of this channel as an $n$-letter mutual information rate under various assumptions on the availability of energy arrival information; 2) we characterize the approximately optimal online power control policy that maximizes the long-term average throughput of the system; 3) we show that the information-theoretic capacity of this channel is equal, within a constant gap, to its long-term average throughput. This last result provides a connection between the information- and communication-theoretic formulations of the energy-harvesting communication problem that have been so far studied in isolation.

Includes members:
  Member "can feedback increase the capacity of the energy harvesting channel":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "feedback capacity and coding for the bibo channel with a no repeated ones input constraint")
  Member "capacity of the awgn channel with random battery recharges":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "capacity of remotely powered communication")
  Member "universally near optimal online power control for energy harvesting nodes":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "a maximin optimal online power control policy for energy harvesting communications")
  Member "near optimal energy control and approximate capacity of energy harvesting communication":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "a maximin optimal online power control policy for energy harvesting communications")
  Member "on online energy harvesting in multiple access communication systems":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "age minimal transmission for energy harvesting sensors with finite batteries online policies")
  Member "a learning theoretic approach to energy harvesting communication system optimization":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "a survey on machine learning based performance improvement of wireless networks phy mac and network layer")
  Member "binary energy harvesting channel with finite energy storage":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "joint transfer of energy and information in a two hop relay channel")
  Member "capacity of fading gaussian channel with an energy harvesting sensor node":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "on the energy and data storage management in energy harvesting wireless communications")

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)