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: "multi phase smart relaying and cooperative jamming in secure cognitive radio networks"
  Abstract: In this paper we investigate cooperative secure communications in a four-node cognitive radio network where the secondary receiver is treated as a potential eavesdropper with respect to the primary transmission. The secondary user is allowed to transmit his own signals under the condition that the primary user's secrecy rate and transmission scheme are intact. Under this setting we derive the secondary user's achievable rates and the related constraints to guarantee the primary user's weak secrecy rate, when Gelfand-Pinsker coding is used at the secondary transmitter. In addition, we propose a multi-phase transmission scheme to include 1) the phases of the clean relaying with cooperative jamming and 2) the latency to successfully decode the primary message at the secondary transmitter. A capacity upper bound for the secondary user is also derived. Numerical results show that: 1) the proposed scheme can outperform the traditional ones by properly selecting the secondary user's parameters of different transmission schemes according to the relative positions of the nodes; 2) the derived capacity upper bound is close to the secondary user's achievable rate within 0.3 bits/channel use, especially when the secondary transmitter/receiver is far/close enough to the primary receiver/transmitter, respectively. Thereby, a smart secondary transmitter is able to adapt its relaying and cooperative jamming to guarantee primary secrecy rates and to transmit its own data at the same time from relevant geometric positions.

Connected through hyperedge HE-1 (induced by source paper "secure communications in noma system subcarrier assignment and power allocation"):
  with members:
    - "secure transmission with large numbers of antennas and finite alphabet inputs"
    - "sub channel assignment power allocation and user scheduling for non orthogonal multiple access networks"
    - "on the spectral efficiency and security enhancements of noma assisted multicast unicast streaming"
    - "secrecy wireless information and power transfer in fading wiretap channel"
    - "optimal joint power and subcarrier allocation for full duplex multicarrier non orthogonal multiple access systems"
    - "power and channel allocation for non orthogonal multiple access in 5g systems tractability and computation"
    - "secure massive mimo transmission with an active eavesdropper"
    - "fairness for non orthogonal multiple access in 5g systems"

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)