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 "dynamic resource allocation for multiple antenna wireless power transfer"):
  Abstract: We consider a point-to-point multiple-input-single-output (MISO) system where a receiver harvests energy from a transmitter. To achieve high-efficiency wireless power transfer (WPT), the transmitter performs energy beamforming by using an instantaneous channel state information (CSI). The CSI is estimated at the receiver by training via a preamble and fed back to the transmitter. In this paper, we address the key challenge of balancing the time resource used for channel estimation and WPT to maximize the harvested energy and also investigate the allocation of energy resource used for WPT. First, we consider the general scenario where the preamble length is allowed to vary dynamically depending on channel conditions. The optimal preamble length is obtained online by solving a dynamic programming (DP) problem. The DP problem is proved to reduce to an optimal stopping problem. The optimal policy is then shown to depend only on the channel estimate power. Next, we consider the scenario in which the preamble length is fixed by an offline optimization. Furthermore, we derive the optimal power allocation schemes. For the dynamic-length-preamble scenario, the power is allocated according to both the optimal preamble length and the channel estimate power, while for the fixed-length-preamble scenario, the power is allocated according to only the channel estimate power. By numerical simulations, our results show that with optimal power allocation, the energy harvested by using the optimized fixed-length preamble is close to that harvested by using a dynamic-length preamble, hence allowing a low-complexity yet close-to-optimal WPT system to be implemented in practice.

Includes members:
  Member "throughput optimization for massive mimo systems powered by wireless energy transfer":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "wirelessly powered sensor networks power allocation for channel estimation and energy beamforming")
  Member "robust beamforming for secure communication in systems with wireless information and power transfer":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "angle aware user cooperation for secure massive mimo in rician fading channel")
  Member "energy beamforming with one bit feedback":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "wirelessly powered sensor networks power allocation for channel estimation and energy beamforming")
  Member "full duplex wireless powered communication network with energy causality":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "relay selection scheduling and power control in wireless powered cooperative communication networks")
  Member "throughput maximization in wireless powered communication networks":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "on maximizing information reliability in wireless powered cooperative networks")
  Member "simultaneous information and power transfer for broadband wireless systems":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "transmission delay minimization in wireless powered communication systems")
  Member "wireless compressive sensing for energy harvesting sensor nodes":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "accelerating federated learning via momentum gradient descent")
  Member "wireless information transfer with opportunistic energy harvesting":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "design of an miso swipt aided code index modulated multi carrier m dcsk system for e health iot")

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)