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 "simple approximations of the sir meta distribution in general cellular networks"):
  Abstract: Compared to the standard success (coverage) probability, the meta distribution of the signal-to-interference ratio (SIR) provides much more fine-grained information about the network performance. We consider general heterogeneous cellular networks (HCNs) with base station tiers modeled by arbitrary stationary and ergodic non-Poisson point processes. The exact analysis of non-Poisson network models is notoriously difficult, even in terms of the standard success probability, let alone the meta distribution. Hence we propose a simple approach to approximate the SIR meta distribution for non-Poisson networks based on the ASAPPP ("approximate SIR analysis based on the Poisson point process") method. We prove that the asymptotic horizontal gap $G_0$ between its standard success probability and that for the Poisson point process exactly characterizes the gap between the $b$th moment of the conditional success probability, as the SIR threshold goes to $0$. The gap $G_0$ allows two simple approximations of the meta distribution for general HCNs: 1) the per-tier approximation by applying the shift $G_0$ to each tier and 2) the effective gain approximation by directly shifting the meta distribution for the homogeneous independent Poisson network. Given the generality of the model considered and the fine-grained nature of the meta distribution, these approximations work surprisingly well.

Includes members:
  Member "sir meta distribution of k tier downlink heterogeneous cellular networks with cell range expansion":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "optimal coverage and rate in downlink cellular networks a sir meta distribution based approach")
  Member "efficient calculation of meta distributions and the performance of user percentiles":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "per link reliability and rate control two facets of the sir meta distribution")
  Member "equi coverage contours in cellular networks":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "coverage analysis of integrated sub 6ghz mmwave cellular networks with hotspots")
  Member "3gpp inspired hetnet model using poisson cluster process sum product functionals and downlink coverage":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "joint energy and sinr coverage in spatially clustered rf powered iot network")
  Member "the meta distribution of the sir for cellular networks with power control":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "a spatiotemporal framework for information freshness in iot uplink networks")
  Member "asymptotics and approximation of the sir distribution in general cellular networks":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "sir analysis via signal fractions")
  Member "the meta distribution of the sir in poisson bipolar and cellular networks":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "spatio temporal modeling for massive and sporadic access")
  Member "asymptotic deployment gain a simple approach to characterize the sinr distribution in general cellular networks":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "smart radio environments empowered by ai reconfigurable meta surfaces an idea whose time has come")

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)