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 "robust beamforming for secure communication in systems with wireless information and power transfer"):
  Abstract: This paper considers a multiuser multiple-input single-output (MISO) downlink system with simultaneous wireless information and power transfer. In particular, we focus on secure communication in the presence of passive eavesdroppers and potential eavesdroppers (idle legitimate receivers). We study the design of a resource allocation algorithm minimizing the total transmit power for the case when the legitimate receivers are able to harvest energy from radio frequency signals. Our design advocates the dual use of both artificial noise and energy signals in providing secure communication and facilitating efficient wireless energy transfer. The algorithm design is formulated as a non-convex optimization problem. The problem formulation takes into account artificial noise and energy signal generation for protecting the transmitted information against both considered types of eavesdroppers when imperfect channel state information (CSI) of the potential eavesdroppers and no CSI of the passive eavesdroppers are available at the transmitter. Besides, the problem formulation also takes into account different quality of service (QoS) requirements: a minimum required signal-to-interference-plus-noise ratio (SINR) at the desired receiver; maximum tolerable SINRs at the potential eavesdroppers; a minimum required outage probability at the passive eavesdroppers; and minimum required heterogeneous amounts of power transferred to the idle legitimate receivers. In light of the intractability of the problem, we reformulate the considered problem by replacing a non-convex probabilistic constraint with a convex deterministic constraint. Then, a semi-definite programming (SDP) relaxation approach is adopted to obtain the optimal solution for the reformulated problem. Furthermore, we propose a suboptimal resource allocation scheme with low computational complexity for providing communication secrecy and facilitating efficient energy transfer. Simulation results demonstrate the close-to-optimal performance of the proposed schemes and significant transmit power savings by optimization of the artificial noise and energy signal generation.

Includes members:
  Member "secrecy wireless information and power transfer with miso beamforming":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "energy efficient resource allocation for secure noma enabled mobile edge computing networks")
  Member "multiuser miso beamforming for simultaneous wireless information and power transfer":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "design of an miso swipt aided code index modulated multi carrier m dcsk system for e health iot")
  Member "resource allocation for secure communication in systems with wireless information and power transfer":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "artificial noise aided secrecy information and power transfer in ofdma systems")
  Member "spatially selective artificial noise aided transmit optimization for miso multi eves secrecy rate maximization":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "secure millimeter wave cloud radio access networks relying on microwave multicast fronthaul")
  Member "wireless information and power transfer energy efficiency optimization in ofdma systems":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "on the performance gain of noma over oma in uplink communication systems")
  Member "multi objective beamforming for secure communication in systems with wireless information and power transfer":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "transceiver design to maximize the weighted sum secrecy rate in full duplex swipt systems")
  Member "distributed robust multicell coordinated beamforming with imperfect csi an admm approach":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "robust urllc packet scheduling of ofdm systems")
  Member "wireless information and power transfer architecture design and rate energy tradeoff":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "cognitive wireless power transfer in the presence of reactive primary communication user")

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)