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 "physical layer performance evaluation of wireless infrared based lifi uplink"):
  Abstract: LiFi (light-fidelity) is recognised as a promising technology for the next generation wireless access network. However, little research effort has been spent on the uplink transmission system in LiFi networks. In this paper, an analytical framework for the performance analysis of an wireless infrared-based LiFi uplink at system level is presented. This work focuses on the performance of a single user who is randomly located in a network. Many important factors in practice are taken into account, such as front-end characteristics, channel path loss, link blockage and user device random orientations. In particular, accurate analytical expressions for the statistics of optical channel path loss has been derived. Based on this path loss statistics, the distribution of signal-to-noise ratio (SNR) and the average achievable data rate are evaluated. A channel factor is defined as a quantity which only depends on the used devices, optical channel and noise power spectral density function (PSD). The result shows that with commercial front-end elements, an average data rate of up to 250 Mbps is achievable.

Includes members:
  Member "modeling the random orientation of mobile devices measurement analysis and lifi use case":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "hybrid lifi and wifi networks a survey")
  Member "coverage and spectral efficiency of indoor mmwave networks with ceiling mounted access points":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "performance analysis of indoor mmwave networks with ceiling mounted access points")

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.IT(Information Theory)