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 "secrecy rate region of swipt wiretap interference channels"):
  Abstract: The secrecy rate region of wiretap interference channels with a multi-antenna passive eavesdropper is studied under receiver energy harvesting constraints. To stay operational in the network, the legitimate receivers demand energy alongside information, which is fulfilled by power transmission and exploiting a power splitting (PS) receiver. By simultaneous wireless information and power transfer (SWIPT), the amount of leakage to the eavesdropper increases, which in turn reduces the secrecy rates. For this setup, lower-bounds for secure communication rate are derived without imposing any limitation at the eavesdropper processing. These lower-bounds are then compared with the rates achieved by assuming the worst-case linear eavesdropper processing. We show that in certain special cases the worst-case eavesdropper does not enlarge the achievable secure rate region in comparison to the unconstrained eavesdropper case. It turns out that in order to achieve the Pareto boundary of the secrecy rate region, smart tuning of the transmit power and receiver PS coefficient is required. Hence, we propose an efficient algorithm to optimize these parameters jointly in polynomial-time. The secrecy rate region characterization is formulated as a weighted max-min optimization problem. This problem turns out to be a non-convex problem due to the non-convex constrained set. This set is replaced by a convex subset that in consequence leads to an achievable suboptimal solution which is improved iteratively. By solving the problem efficiently, we obtain the amount of rate loss for providing secrecy, meanwhile satisfying the energy demands.

Includes members:
  Member "optimal power splitting for simultaneous information detection and energy harvesting":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "towards optimal energy harvesting receiver design in mimo systems")
  Member "joint power control in wiretap interference channels":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "physical layer security for rf satellite channels in the finite length regime")
  Member "multiobjective signal processing optimization the way to balance conflicting metrics in 5g systems":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "joint dynamic pricing and radio resource allocation framework for iot services")
  Member "optimal relay selection for physical layer security in cooperative wireless networks":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "secrecy outage analysis of non orthogonal spectrum sharing for heterogeneous cellular networks")
  Member "wireless information and power transfer a dynamic power splitting approach":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "on maximizing information reliability in wireless powered cooperative networks")
  Member "discrete memoryless interference and broadcast channels with confidential messages secrecy rate regions":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "cognitive radio networks an information theoretic perspective")
  Member "the gaussian multiple access wire tap channel":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "an achievable region for the multiple access wiretap channels with confidential and open messages")

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)