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 "on stochastic geometry modeling of cellular uplink transmission with truncated channel inversion power control"):
  Abstract: Using stochastic geometry, we develop a tractable uplink modeling paradigm for outage probability and spectral efficiency in both single and multi-tier cellular wireless networks. The analysis accounts for per user equipment (UE) power control as well as the maximum power limitations for UEs. More specifically, for interference mitigation and robust uplink communication, each UE is required to control its transmit power such that the average received signal power at its serving base station (BS) is equal to a certain threshold $\rho_o$. Due to the limited transmit power, the UEs employ a truncated channel inversion power control policy with a cutoff threshold of $\rho_o$. We show that there exists a transfer point in the uplink system performance that depends on the tuple: BS intensity ($\lambda$), maximum transmit power of UEs ($P_u$), and $\rho_o$. That is, when $P_u$ is a tight operational constraint with respect to [w.r.t.] $\lambda$ and $\rho_o$, the uplink outage probability and spectral efficiency highly depend on the values of $\lambda$ and $\rho_o$. In this case, there exists an optimal cutoff threshold $\rho^*_o$, which depends on the system parameters, that minimizes the outage probability. On the other hand, when $P_u$ is not a binding operational constraint w.r.t. $\lambda$ and $\rho_o$, the uplink outage probability and spectral efficiency become independent of $\lambda$ and $\rho_o$. We obtain approximate yet accurate simple expressions for outage probability and spectral efficiency which reduce to closed-forms in some special cases.

Includes members:
  Member "spectrum sharing for device to device communication in cellular networks":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "sense and predict harnessing spatial interference correlation for cognitive radio networks")
  Member "downlink rate distribution in heterogeneous cellular networks under generalized cell selection":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "millimeter wave integrated access and backhaul in 5g performance analysis and design insights")
  Member "analytical modeling of uplink cellular networks":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "dynamic tdd interference analysis in macro cell and small cell deployments")
  Member "modeling heterogeneous network interference using poisson point processes":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "towards reliable uav swarm communication in d2d enhanced cellular network")
  Member "modeling and analysis of k tier downlink heterogeneous cellular networks":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "reinforcement learning based cooperative coded caching under dynamic popularities in ultra dense networks")
  Member "mean interference in hard core wireless networks":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "air to air communications beyond 5g a novel 3d comp transmission scheme")
  Member "a tractable approach to coverage and rate in cellular networks":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "area spectral efficiency and sinr scaling laws in multi antenna cellular networks")
  Member "analytical evaluation of fractional frequency reuse for ofdma cellular networks":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "a unified framework for the tractable analysis of multi antenna wireless networks")

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)