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: "a new scaling law on throughput and delay performance of wireless mobile relay networks over parallel fading channels"
  Abstract: In this paper, utilizing the relay buffers, we propose an opportunistic decode-wait-and-forward relay scheme for a point-to-point communication system with a half-duplexing relay network to better exploit the time diversity and relay mobility. For instance, we analyze the asymptotic throughput-delay tradeoffs in a dense relay network for two scenarios: (1) fixed relays with \textit{microscopic fading} channels (multipath channels), and (2) mobile relays with \textit{macroscopic fading} channels (path loss). In the first scenario, the proposed scheme can better exploit the \textit{multi-relay diversity} in the sense that with $K$ fixed relays and a cost of $\mathcal{O}(K)$ average end-to-end packet delay, it could achieve the same optimal asymptotic average throughput as the existing designs (such as regular decode-and-forward relay schemes) with $K^2$ fixed relays. In the second scenario, the proposed scheme achieves the maximum throughput of $\Theta(\log K)$ at a cost of $\mathcal{O}(K/q)$ average end-to-end packet delay, where $0<q\leq {1/2}$ measures the speed of relays' mobility. This system throughput is unattainable for the existing designs with low relay mobility, the proposed relay scheme can exploit the relays' mobility more efficiently.

Connected through hyperedge HE-1 (induced by source paper "throughput maximization of mixed fso rf uav aided mobile relaying with a buffer"):
  with members:
    - "a qos oriented trajectory optimization in swarming unmanned aerial vehicles communications"
    - "a uav mounted free space optical communication trajectory optimization for flight time"
    - "energy minimization for wireless communication with rotary wing uav"
    - "a tutorial on uavs for wireless networks applications challenges and open problems"
    - "survey of important issues in uav communication networks"
    - "energy efficient uav communication with trajectory optimization"
    - "fso based vertical backhaul fronthaul framework for 5g wireless networks"
    - "wireless communications with unmanned aerial vehicles opportunities and challenges"

Connected through hyperedge HE-2 (induced by source paper "buffer aided relaying with adaptive link selection fixed and mixed rate transmission"):
  with members:
    - "buffer aided relaying with adaptive link selection"
    - "a simple cooperative diversity method based on network path selection"

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)