human: Given a node-centered hypergraph: <hypergraph>, where nodes represent papers and hyperedges represent sets of papers co-cited by a source paper.

Details of the hypergraph:
Center node: "constructive interference based secure precoding a new dimension in physical layer security"
  Abstract: Conventionally, interference and noise are treated as catastrophic elements in wireless communications. However, it has been shown recently that exploiting known interference constructively can even contribute to signal detection ability at the receiving end. This paper exploits this concept to design artificial noise (AN) beamformers constructive to the intended receiver (IR) yet keeping AN disruptive to possible eavesdroppers (Eves). The scenario considered here is a multiple-input single-output (MISO) wiretap channel with multiple eavesdroppers. Both perfect and imperfect channel information have been considered. The main objective is to improve the receive signal-to-interference and noise ratio (SINR) at IR through exploitation of AN power in an attempt to minimize the total transmit power, while confusing the Eves. Numerical simulations demonstrate that the proposed constructive AN precoding approach yields superior performance over conventional AN schemes in terms of transmit power as well as symbol error rate (SER).

Connected through hyperedge HE-1 (induced by source paper "rethinking secure precoding via interference exploitation a smart eavesdropper perspective"):
  with members:
    - "quantized constant envelope precoding with psk and qam signaling"
    - "linear precoding of data and artificial noise in secure massive mimo systems"
    - "directional modulation via symbol level precoding a way to enhance security"
    - "power efficient resource allocation for full duplex radio distributed antenna networks"
    - "exploiting known interference as green signal power for downlink beamforming optimization"
    - "on secrecy rate analysis of mimo wiretap channels driven by finite alphabet input"
    - "outage constrained robust transmit optimization for multiuser miso downlinks tractable approximations by conic optimization"
    - "secure transmission with artificial noise over fading channels achievable rate and optimal power allocation"

Connected through hyperedge HE-2 (induced by source paper "an overview of physical layer security with finite alphabet signaling"):
  with members:
    - "a survey of physical layer security techniques for 5g wireless networks and challenges ahead"
    - "physical layer cryptography through massive mimo"
    - "linear precoding of data and artificial noise in secure massive mimo systems"
    - "sum secrecy rate maximization for full duplex two way relay networks using alamouti based rank two beamforming"
    - "performance of lattice coset codes on universal software radio peripherals"
    - "secure m psk communication via directional modulation"
    - "finite blocklength bounds for wiretap channels"
    - "physical layer security in millimeter wave cellular networks"

Connected through hyperedge HE-3 (induced by source paper "exploiting physical layer security for multiuser multicarrier computation offloading"):
  with members:
    - "probabilistically robust swipt for secrecy misome systems"
    - "a survey on mobile edge computing the communication perspective"
    - "joint offloading and computing optimization in wireless powered mobile edge computing systems"
    - "energy efficient resource allocation for mobile edge computation offloading"
    - "efficient multi user computation offloading for mobile edge cloud computing"
    - "power and subcarrier allocation for physical layer security in ofdma based broadband wireless networks"

Question: Please tell me which class the center node 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)