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 "random access transport capacity"):
  Abstract: We develop a new metric for quantifying end-to-end throughput in multihop wireless networks, which we term random access transport capacity, since the interference model presumes uncoordinated transmissions. The metric quantifies the average maximum rate of successful end-to-end transmissions, multiplied by the communication distance, and normalized by the network area. We show that a simple upper bound on this quantity is computable in closed-form in terms of key network parameters when the number of retransmissions is not restricted and the hops are assumed to be equally spaced on a line between the source and destination. We also derive the optimum number of hops and optimal per hop success probability and show that our result follows the well-known square root scaling law while providing exact expressions for the preconstants, which contain most of the design-relevant network parameters. Numerical results demonstrate that the upper bound is accurate for the purpose of determining the optimal hop count and success (or outage) probability.

Includes members:
  Member "on capacity scaling in arbitrary wireless networks":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "throughput scaling of covert communication over wireless adhoc networks")
  Member "spatial and temporal correlation of the interference in aloha ad hoc networks":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "spatio temporal modeling for massive and sporadic access")
  Member "interference and outage in clustered wireless ad hoc networks":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "smart radio environments empowered by ai reconfigurable meta surfaces an idea whose time has come")
  Member "spectrum sharing between cellular and mobile ad hoc networks transmission capacity trade off":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "spatial and temporal analysis of direct communications from static devices to mobile vehicles")
  Member "bandwidth partitioning in decentralized wireless networks":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "reliability and local delay in wireless networks does bandwidth partitioning help")
  Member "scaling laws for overlaid wireless networks a cognitive radio network vs a primary network":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "an overview of the transmission capacity of wireless networks")
  Member "transmission capacity of ad hoc networks with spatial diversity":
    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 "the effect of fading channel inversion and threshold scheduling on ad hoc networks":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "hiding communications in awgn channels and thz band with interference uncertainty")

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)