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: "optimal relay selection for the parallel hybrid rf fso relay channel non buffer aided and buffer aided designs"
  Abstract: Hybrid radio frequency (RF)/free space optical (FSO) systems are among the candidate enabling technologies for the next generation of wireless networks since they benefit from both the high data rates of the FSO subsystem and the high reliability of the RF subsystem. In this paper, we focus on the problem of throughput maximization in the parallel hybrid RF/FSO relay channel. In the parallel hybrid RF/FSO relay channel, a source node sends its data to a destination node with the help of multiple relay nodes. Thereby, for a given relay, the source-relay and the relay-destination FSO links are orthogonal with respect to each other due to the narrow beam employed for FSO transmission, whereas, due to the broadcast nature of the RF channel, half-duplex operation is required for the RF links if self-interference is to be avoided. Moreover, we consider the two cases where the relays are and are not equipped with buffers. For both cases, we derive the optimal relay selection policies for the RF and FSO links and the optimal time allocation policy for transmission and reception for the RF links. The proposed optimal protocols provide important insights for optimal system design. Since the optimal buffer-aided (BA) policy introduces an unbounded end-to-end delay, we also propose a suboptimal BA policy which ensures certain target average delays. Moreover, we present distributed implementations for both proposed optimal protocols. Simulation results demonstrate that a considerable gain can be achieved by the proposed adaptive protocols in comparison with benchmark schemes from the literature.

Connected through hyperedge HE-1 (induced by source paper "generalized optimal two way relays subsets pairings in cloud based region cognitive networks"):
  with members:
    - "non orthogonal multiple access for cooperative communications challenges opportunities and trends"
    - "cognitive non orthogonal multiple access with cooperative relaying a new wireless frontier for 5g spectrum sharing"
    - "resource allocation and outage analysis for an adaptive cognitive two way relay network"
    - "cooperation in 5g hetnets advanced spectrum access and d2d assisted communications"
    - "performance of adaptive link selection with buffer aided relays in underlay cognitive networks"
    - "separation framework an enabler for cooperative and d2d communication for future 5g networks"
    - "relay subset selection in wireless networks using partial decode and forward transmission"

Connected through hyperedge HE-2 (induced by source paper "game theoretic spectrum trading in rf relay assisted free space optical communications"):
  with members:
    - "price based resource allocation for spectrum sharing femtocell networks a stackelberg game approach"
    - "on the capacity of free space optical intensity channels"

Connected through hyperedge HE-3 (induced by source paper "c ran with hybrid rf fso fronthaul links joint optimization of rf time allocation and fronthaul compression"):
  with members:
    - "on the design of matched filters for molecule counting receivers"
    - "on the optimal fronthaul compression and decoding strategies for uplink cloud radio access networks"
    - "recent advances in cloud radio access networks system architectures key techniques and open issues"
    - "fronthaul compression and transmit beamforming optimization for multi antenna uplink c ran"
    - "fronthaul constrained cloud radio access networks insights and challenges"
    - "hybrid radio free space optical design for next generation backhaul systems"
    - "optimized backhaul compression for uplink cloud radio access network"
    - "on the capacity of free space optical intensity channels"

Connected through hyperedge HE-4 (induced by source paper "statistical modeling of fso fronthaul channel for drone based networks"):
  with members:
    - "fso based vertical backhaul fronthaul framework for 5g 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)