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 "stochastic geometric analysis of energy efficient dense cellular networks"):
  Abstract: Dense cellular networks (DenseNets) are fast becoming a reality with the rapid deployment of base stations (BSs) aimed at meeting the explosive data traffic demand. In legacy systems however this comes with the penalties of higher network interference and energy consumption. In order to support network densification in a sustainable manner, the system behavior should be made 'load-proportional' thus allowing certain portions of the network to activate on-demand. In this work, we develop an analytical framework using tools from stochastic geometry theory for the performance analysis of DenseNets where load-awareness is explicitly embedded in the design. The model leverages on a flexible cellular network architecture where there is a complete separation of the data and signaling communication functionalities. Using the proposed model, we identify the most energy- efficient deployment solution for meeting certain minimum service criteria and analyze the corresponding power savings through dynamic sleep modes. Based on state-of-the-art system parameters, a homogeneous pico deployment for the data plane with a separate layer of signaling macro-cells is revealed to be the most energy-efficient solution in future dense urban environments.

Includes members:
  Member "the intensity matching approach a tractable stochastic geometry approximation to system level analysis of cellular networks":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "smart radio environments empowered by ai reconfigurable meta surfaces an idea whose time has come")
  Member "spatial spectrum and energy efficiency of random cellular networks":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "spatio temporal modeling for massive and sporadic access")
  Member "modeling analysis and design for carrier aggregation in heterogeneous cellular networks":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "capacity and delay tradeoff of secondary cellular networks with spectrum aggregation")
  Member "average rate of downlink heterogeneous cellular networks over generalized fading channels a stochastic geometry approach":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "spatio temporal correlation of interference in manet under spatially correlated shadowing environment")
  Member "downlink rate distribution in heterogeneous cellular networks under generalized cell selection":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "millimeter wave integrated access and backhaul in 5g performance analysis and design insights")
  Member "load aware modeling and analysis of heterogeneous cellular networks":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "an efficient requirement aware attachment policy for future millimeter wave vehicular networks")
  Member "user association for load balancing in heterogeneous cellular networks":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "reinforcement learning based cooperative coded caching under dynamic popularities in ultra dense networks")
  Member "modeling and analysis of k tier downlink heterogeneous cellular networks":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "reinforcement learning based cooperative coded caching under dynamic popularities in ultra dense 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)