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: "towards a simple relationship to estimate the capacity of static and mobile wireless networks"
  Abstract: Extensive research has been done on studying the capacity of wireless multi-hop networks. These efforts have led to many sophisticated and customized analytical studies on the capacity of particular networks. While most of the analyses are intellectually challenging, they lack universal properties that can be extended to study the capacity of a different network. In this paper, we sift through various capacity-impacting parameters and present a simple relationship that can be used to estimate the capacity of both static and mobile networks. Specifically, we show that the network capacity is determined by the average number of simultaneous transmissions, the link capacity and the average number of transmissions required to deliver a packet to its destination. Our result is valid for both finite networks and asymptotically infinite networks. We then use this result to explain and better understand the insights of some existing results on the capacity of static networks, mobile networks and hybrid networks and the multicast capacity. The capacity analysis using the aforementioned relationship often becomes simpler. The relationship can be used as a powerful tool to estimate the capacity of different networks. Our work makes important contributions towards developing a generic methodology for network capacity analysis that is applicable to a variety of different scenarios.

Connected through hyperedge HE-1 (induced by source paper "throughput of infrastructure based cooperative vehicular networks"):
  with members:
    - "coalitional graph games for popular content distribution in cognitive radio vanets"

Connected through hyperedge HE-2 (induced by source paper "cost efficiency optimization of 5g wireless backhaul networks"):
  with members:
    - "joint optimization of computation and communication power in multi user massive mimo systems"
    - "environment aware minimum cost wireless backhaul network planning with full duplex links"
    - "inter operator resource management for millimeter wave multi hop backhaul networks"
    - "a comparison of mimo techniques in downlink millimeter wave cellular networks with hybrid beamforming"
    - "spatial spectrum and energy efficiency of random cellular networks"
    - "5g ultra dense cellular networks"
    - "mmwave massive mimo based wireless backhaul for the 5g ultra dense network"
    - "5g wireless backhaul networks challenges and research advances"

Connected through hyperedge HE-3 (induced by source paper "capacity of cooperative vehicular networks with infrastructure support multi user case"):
  with members:
    - "on capacity and delay of multichannel wireless networks with infrastructure support"

Connected through hyperedge HE-4 (induced by source paper "5g ultra dense cellular networks"):
  with members:
    - "5g wireless backhaul networks challenges and research advances"
    - "millimeter wave beamforming for wireless backhaul and access in small cell networks"

Connected through hyperedge HE-5 (induced by source paper "transport capacity of distributed wireless csma networks"):
  with members:
    - "high sir transmission capacity of wireless networks with general fading and node distribution"
    - "on the throughput delay trade off in georouting networks"
    - "capacity of large scale csma wireless networks"
    - "mean interference in hard core wireless networks"
    - "an overview of the transmission capacity of wireless networks"
    - "random access transport capacity"
    - "effective carrier sensing in csma networks under cumulative interference"
    - "interference and outage in clustered wireless ad hoc 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.NI(Networking and Internet Architecture)