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: "secure users oriented downlink miso noma"
  Abstract: This paper proposes a secure users oriented multiple-input and single-output (MISO) non-orthogonal multiple access (NOMA) downlink transmission scheme, where multiple legitimate users are categorized as quality of service (QoS)-required users (QU) and the security-required users (SU) overheard by a passive eavesdropper. The basic idea is to exploit zero-forcing beamforming (ZFBF) to cancel interference among SUs, and then several QUs are efficiently scheduled based on the obtained beamforming vectors to divide the legitimate users into several user clusters, in such a way that the QUs could share the concurrent transmissions and help to interfere with the eavesdropper to enhance SU secrecy. The goal is to maximize the achievable minimum secrecy rate (MSR) and sum secrecy rate (SSR) of all SUs, respectively, subject to the secrecy outage probability (SOP) constraint of each SU and the QoS constraint of each QU. To provide a comprehensive investigation we consider two extreme cases that the eavesdropper has perfect multiuser detection ability (lower bound of secrecy) or does not have multiuser detection ability (upper bound of secrecy). In the lower bound case, the Dinkelbach algorithm and the monotonic optimization (MO)-based outer polyblock approximation algorithm are proposed to solve the max-min secrecy rate (MMSR) and max-sum secrecy rate (MSSR) problems, respectively. As for the upper bound case, an alternative optimization (AO)-based algorithm is proposed to solve the two non-convex problems. Finally, the superiority of the proposed cases to the conventional orthogonal multiple access (OMA) one is verified by numerical results.

Connected through hyperedge HE-1 (induced by source paper "physical layer security for noma transmission in mmwave drone networks"):
  with members:
    - "uav communications for 5g and beyond recent advances and future trends"
    - "enhancing physical layer security for noma transmission in mmwave drone networks"
    - "beamforming design and power allocation for secure transmission with noma"
    - "exploiting inter user interference for secure massive non orthogonal multiple access"
    - "secrecy sum rate maximization in non orthogonal multiple access"
    - "on the design of secure non orthogonal multiple access systems"
    - "enhancing the physical layer security of non orthogonal multiple access in large scale networks"

Connected through hyperedge HE-2 (induced by source paper "secure communication for spatially sparse millimeter wave massive mimo channels via hybrid precoding"):
  with members:
    - "secure massive mimo communication with low resolution dacs"
    - "a hardware efficient analog network structure for hybrid precoding in millimeter wave systems"
    - "performance analysis of multi cell millimeter wave massive mimo networks with low precision adcs"
    - "low complexity reconfigurable mimo for millimeter wave communications"
    - "a survey of physical layer security techniques for 5g wireless networks and challenges ahead"
    - "millimeter wave communications with reconfigurable antennas"
    - "millimeter wave mimo channel estimation using overlapped beam patterns and rate adaptation"
    - "analysis of one bit quantized precoding for the multiuser massive mimo downlink"

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)