human: Given a hyperedge-centered hypergraph: <hypergraph>, where the center hyperedge is induced by one source paper and its member nodes are the cited papers.

Details of the hypergraph:
Center hyperedge (induced by source paper "to overlap or not to overlap enabling channel bonding in high density wlans"):
  Abstract: Wireless local area networks (WLANs) are the most popular kind of wireless Internet connection because of their simplicity of deployment and operation. As a result, the number of devices accessing the Internet through WLANs such as laptops, smartphones, or wearables, is increasing drastically at the same time that applications' throughput requirements do. To cope with these challenges, channel bonding (CB) techniques are used for enabling higher data rates by transmitting in wider channels, thus increasing spectrum efficiency. However, important issues like higher potential co-channel and adjacent channel interference arise when bonding channels. This may harm the performance of the carrier sense multiple access (CSMA) protocol because of recurrent backoff freezing while making nodes more sensitive to hidden node effects. In this paper, we address the following point at issue: is it convenient for high-density (HD) WLANs to use wider channels and potentially overlap in the spectrum? First, we highlight key aspects of DCB in toy scenarios through a continuous time Markov network (CTMN) model. Then, by means of extensive simulations covering a wide range of traffic loads and access point (AP) densities, we show that dynamic channel bonding (DCB) - which adapts the channel bandwidth on a per-packet transmission - significantly outperforms traditional single-channel on average. Nevertheless, results also corroborate that DCB is more prone to generate unfair situations where WLANs may starve. Contrary to most of the current thoughts pushing towards non-overlapping channels in HD deployments, we highlight the benefits of allocating channels as wider as possible to WLANs altogether with implementing adaptive access policies to cope with the unfairness situations that may appear.

Includes members:
  Member "komondor a wireless network simulator for next generation high density wlans":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "spatial reuse in ieee 802 11ax wlans")
  Member "dynamic channel bonding in spatially distributed high density wlans":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "potential and pitfalls of multi armed bandits for decentralized spatial reuse in wlans")
  Member "toward low latency and ultra reliable virtual reality":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "wireless edge computing with latency and reliability guarantees")
  Member "a channel allocation algorithm to maximize aggregate throughputs in dcb wlans":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "dynamic channel bonding in spatially distributed high density wlans")
  Member "ieee 802 11ax high efficiency wlans":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "deep learning enabled optimization of downlink beamforming under per antenna power constraints algorithms and experimental demonstration")
  Member "on the interactions between multiple overlapping wlans using channel bonding":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "online primary channel selection for dynamic channel bonding in high density wlans")
  Member "analysis of dynamic channel bonding in dense networks of wlans":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "dynamic channel bonding in spatially distributed high density wlans")

Question: Please tell me which class the source paper 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)