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: "c ran with hybrid rf fso fronthaul links joint optimization of rf time allocation and fronthaul compression"
  Abstract: This paper considers the uplink of a cloud radio access network (C-RAN) comprised of several multi-antenna remote radio units (RUs) which compress the signals that they receive from multiple mobile users (MUs) and forward them to a CU via wireless fronthaul links. To enable reliable high rate fronthaul links, we employ a hybrid radio frequency (RF)/free space optical (FSO) system for fronthauling. To strike a balance between complexity and performance, we consider three different quantization schemes at the RUs, namely per-antenna vector quantization (AVQ), per-RU vector quantization (RVQ), and distributed source coding (DSC), and two different receivers at the CU, namely the linear minimum mean square error receiver and the optimal successive interference cancellation receiver. For this network architecture, we investigate the joint optimization of the quantization noise covariance matrices at the RUs and the RF time allocation to the multiple-access and fronthaul links for rate region maximization. To this end, we formulate a unified weighted sum rate maximization problem valid for each possible pair of the considered quantization and detection schemes. To handle the non-convexity of the unified problem, we transform it into a bi-convex problem which facilitates the derivation of an efficient suboptimal solution using alternating convex optimization and golden section search. Our simulation results show that for each pair of the considered quantization and detection schemes, C-RAN with hybrid RF/FSO fronthauling can achieve a considerable sum rate gain compared to conventional systems employing pure FSO fronthauling, especially under unfavorable atmospheric conditions. Moreover, employing a more sophisticated quantization scheme can significantly improve the system performance under adverse atmospheric conditions.

Connected through hyperedge HE-1 (induced by source paper "intelligent reflecting and transmitting surface aided millimeter wave massive mimo"):
  with members:
    - "a novel communication paradigm for high capacity and security via programmable indoor wireless environments in next generation wireless systems"
    - "intelligent reflecting surfaces for free space optical communications"
    - "feedback aware precoding for millimeter wave massive mimo systems"
    - "energy efficiency of mmwave massive mimo precoding with low resolution dacs"
    - "intelligent reflecting surface enhanced wireless network via joint active and passive beamforming"
    - "scalable and energy efficient millimeter massive mimo architectures reflect array and transmit array antennas"
    - "intelligent reflecting surface enhanced wireless network joint active and passive beamforming design"
    - "spectrum and energy efficient beamspace mimo noma for millimeter wave communications using lens antenna array"

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)