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 "performance analysis of wireless powered communication with finite infinite energy storage"):
  Abstract: In this paper, we consider an energy harvesting (EH) node which harvests energy from a radio frequency (RF) signal broadcasted by an access point (AP) in the downlink (DL). The node stores the harvested energy in an energy buffer and uses the stored energy to transmit data to the AP in the uplink (UL). We consider a simple transmission policy, which accounts for the fact that in practice the EH node may not have knowledge of the EH profile nor of the UL channel state information. In particular, in each time slot, the EH node transmits with either a constant desired power or a lower power if not enough energy is available in its energy buffer. For this simple policy, we use the theory of discrete-time continuous-state Markov chains to analyze the limiting distribution of the stored energy for finite- and infinite-size energy buffers. Moreover, we take into account imperfections of the energy buffer and the circuit power consumption of the EH node. For a Rayleigh fading DL channel, we provide the limiting distribution of the energy buffer content in closed form. In addition, we analyze the average error rate and the outage probability of a Rayleigh faded UL channel and show that the diversity order is not affected by the finite capacity of the energy buffer. Our results reveal that the optimal desired transmit power by the EH node is always less than the average harvested power and increases with the capacity of the energy buffer.

Includes members:
  Member "throughput maximization in wireless powered communication networks":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "on maximizing information reliability in wireless powered cooperative networks")
  Member "multi antenna wireless powered communication with energy beamforming":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "wirelessly powered sensor networks power allocation for channel estimation and energy beamforming")
  Member "wireless information and power transfer architecture design and rate energy tradeoff":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "cognitive wireless power transfer in the presence of reactive primary communication user")
  Member "transmission with energy harvesting nodes in fading wireless channels optimal policies":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "closed form analysis of non linear age of information in status updates with an energy harvesting transmitter")
  Member "optimal energy management policies for energy harvesting sensor nodes":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "achievable rate of multi antenna wsrns with eh constraint in the presence of a jammer")

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)