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 "secure swipt networks based on a non linear energy harvesting model"):
  Abstract: We optimize resource allocation to enable communication security in simultaneous wireless information and power transfer (SWIPT) for internet-of-things (IoT) networks. The resource allocation algorithm design is formulated as a non-convex optimization problem. We aim at maximizing the total harvested power at energy harvesting (EH) receivers via the joint optimization of transmit beamforming vectors and the covariance matrix of the artificial noise injected to facilitate secrecy provisioning. The proposed problem formulation takes into account the non-linearity of energy harvesting circuits and the quality of service requirements for secure communication. #R##N#To obtain a globally optimal solution of the resource allocation problem, we first transform the resulting non-convex sum-of-ratios objective function into an equivalent objective function in parametric subtractive form, which facilitates the design of a novel iterative resource allocation algorithm. In each iteration, the semidefinite programming (SDP) relaxation approach is adopted to solve a rank-constrained optimization problem optimally. Numerical results reveal that the proposed algorithm can guarantee communication security and provide a significant performance gain in terms of the harvested energy compared to existing designs which are based on the traditional linear EH model.

Includes members:
  Member "robust layered transmission in secure miso multiuser unicast cognitive radio systems":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "robust resource allocation for full duplex cognitive radio systems")
  Member "secrecy wireless information and power transfer challenges and opportunities":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "downlink secrecy rate of one bit massive mimo system with active eavesdropping")
  Member "practical non linear energy harvesting model and resource allocation for swipt systems":
    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 "energy efficient resource allocation for wireless powered communication networks":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "common throughput maximization for uav enabled interference channel with wireless powered communications")
  Member "enhancing wireless information and power transfer by exploiting multi antenna techniques":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "wireless energy beamforming using received signal strength indicator feedback")
  Member "multi objective optimization for robust power efficient and secure full duplex wireless communication systems":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "joint trajectory and resource allocation design for energy efficient secure uav communication systems")
  Member "robust beamforming for secure communication in systems with wireless information and power transfer":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "angle aware user cooperation for secure massive mimo in rician fading channel")
  Member "simultaneous wireless information and power transfer in modern communication systems":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "wirelessly powered sensor networks power allocation for channel estimation and energy beamforming")

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)