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 layered transmission in secure miso multiuser unicast cognitive radio systems"):
  Abstract: This paper studies robust resource-allocation algorithm design for a multiuser multiple-input–single-output (MISO) cognitive radio (CR) downlink communication network. We focus on a secondary system that provides wireless unicast secure layered video information to multiple single-antenna secondary receivers. The resource-allocation algorithm design is formulated as a nonconvex optimization problem for the minimization of the total transmit power at the secondary transmitter. The proposed framework takes into account a quality-of-service (QoS) requirement regarding video communication secrecy in the secondary system, the imperfection of the channel state information (CSI) of potential eavesdroppers (primary receivers) at the secondary transmitter, and a limit for the maximum tolerable received interference power at the primary receivers. Thereby, the proposed problem formulation exploits the    self-protecting   architecture of layered transmission and artificial noise generation to ensure communication secrecy. The considered nonconvex optimization problem is recast as a convex optimization problem via semi-definite programming (SDP) relaxation. It is shown that the global optimal solution of the original problem can be constructed by exploiting both the primal and the dual optimal solutions of the SDP-relaxed problem. In addition, two suboptimal resource-allocation schemes are proposed for the case when the solution of the dual problem is unavailable for constructing the optimal solution. Simulation results demonstrate significant transmit power savings and robustness against CSI imperfection for the proposed optimal and suboptimal resource-allocation algorithms employing layered transmission compared to baseline schemes employing traditional single-layer transmission.

Includes members:
  Member "securing physical layer communications for cognitive radio networks":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "adversarial deep learning for over the air spectrum poisoning attacks")
  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 "secrecy outage and diversity analysis of cognitive radio systems":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "secrecy outage and diversity analysis of multiple cooperative source destination pairs")
  Member "secure and green swipt in distributed antenna networks with limited backhaul capacity":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "joint trajectory and resource allocation design for energy efficient secure uav communication systems")
  Member "radio resource allocation for scalable video services over wireless cellular networks":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "radio resource management based on reused frequency allocation for dynamic channel borrowing scheme in wireless networks")
  Member "power efficient miso beamforming for secure layered transmission":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "multi objective optimization for power efficient full duplex wireless communication systems")
  Member "secrecy wireless information and power transfer with miso beamforming":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "energy efficient resource allocation for secure noma enabled mobile edge computing networks")
  Member "spatially selective artificial noise aided transmit optimization for miso multi eves secrecy rate maximization":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "secure millimeter wave cloud radio access networks relying on microwave multicast fronthaul")

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)