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 "a mathematical justification for exponentially distributed nlos bias"):
  Abstract: In the past few decades, the localization literature has seen many models attempting to characterize the non-line-of-sight (NLOS) bias error commonly experienced in range measurements. These models have either been based on specific measurement data or chosen due to attractive features of a particular distribution, yet to date, none have been backed by rigorous analysis. Leveraging tools from stochastic geometry, this paper attempts to fill this void by providing the first analytical backing for an NLOS bias error model. Using a Boolean model to statistically characterize the random locations, orientations, and sizes of reflectors, and assuming first-order (i.e., single-bounce) reflections, the distance traversed by the first-arriving NLOS path is characterized. Under these assumptions, this analysis reveals that NLOS bias exhibits an exponential form and can in fact be well approximated by an exponential distribution -- a result consistent with previous NLOS bias error models in the literature. This analytically derived distribution is then compared to a common exponential model from the literature, revealing this distribution to be a close match in some cases and a lower bound in others. Lastly, the assumptions under which these results were derived suggest this model is aptly suited to characterize NLOS bias in 5G millimeter wave systems as well.

Includes members:
  Member "a tractable analysis of the blind spot probability in localization networks under correlated blocking":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "exploiting randomly located blockages for large scale deployment of intelligent surfaces")
  Member "a novel geometry based stochastic double directional analytical model for millimeter wave outdoor nlos channels":
    also connected through other hyperedges:
      (none)
  Member "modeling and analyzing millimeter wave cellular systems":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "coverage analysis of uavs in millimeter wave networks a stochastic geometry approach")
  Member "analysis of blockage effects on urban cellular networks":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "exploiting randomly located blockages for large scale deployment of intelligent surfaces")

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)