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 "multiuser joint energy bandwidth allocation with energy harvesting part ii multiple broadcast channels proportional fairness"):
  Abstract: AbstractIn this paper, we consider the energy-bandwidth allocationfor a network with multiple broadcastchannels, where the transmitters access the network orthogonally on the assigned frequency band andeach transmitter communicates with multiple receivers orthogonally or non-orthogonally.We assume thatthe energy harvesting state and channel gain of each transmitter can be predicted for K slots a priori.To maximize the weighted throughput, we formulate an optimization problem with O(MK)constraints,where M is the number of the receivers, and decompose it into the energy and bandwidth allocationsubproblems. In order to use the iterative algorithm proposed in [1] to solve the problem, we proposeefﬁcient algorithms to solve the two subproblems, so that th e optimal energy-bandwidth allocation canbe obtained with an overall complexity of O(MK 2 ), even though the problem is non-convex whenthe broadcast channel is non-orthogonal. For the orthogonal broadcast channel, we further formulate aproportionally-fair (PF) throughput maximization problem and derive the equivalence conditions suchthat the optimal solution can be obtained by solving a weighted throughput maximization problem.Further, the algorithm to obtain the proper weights is proposed. Simulation results show that theproposed algorithm can make efﬁcient use of the harvested en ergy and the available bandwidth, andachieve signiﬁcantly better performancethan some heurist ic policies for energy and bandwidth allocation.Moreover, it is seen that with energy-harvesting transmitters, non-orthogonal broadcast offers limitedgain over orthogonal broadcast.Index TermsConvex optimization, energy-bandwidth allocation, energy harvesting, non-orthogonal broadcast,orthogonal broadcast, proportionally fair scheduling.

Includes members:
  Member "iterative dynamic water filling for fading multiple access channels with energy harvesting":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "design of an miso swipt aided code index modulated multi carrier m dcsk system for e health iot")
  Member "multiuser joint energy bandwidth allocation with energy harvesting part i optimum algorithm multiple point to point channels":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "grid energy consumption and qos tradeoff in hybrid energy supply wireless networks")
  Member "broadcasting with an energy harvesting rechargeable transmitter":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "age of information minimization for an energy harvesting source with updating erasures with and without feedback")
  Member "sum rate optimal power policies for energy harvesting transmitters in an interference channel":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "age minimal online policies for energy harvesting sensors with random battery recharges")

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)