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 "fundamentals of the downlink green coverage and energy efficiency in heterogeneous networks"):
  Abstract: This paper studies the proposed green (energy-efficient) coverage probability, link and network energy efficiencies in the downlink of a heterogeneous cellular network (HetNet) consisting of $K$ independent Poisson point processes (PPPs) of base stations (BSs). The important statistical properties of the universal (general) cell association functions are first studied and the cell load statistics for power-law cell association functions, which can characterize the accurate void cell probability of a BS in every tier, is also derived. A simple and feasible green channel-aware cell association (GCA) scheme is proposed and the green coverage probability is also proposed for any particular cell association scheme, such as the maximum received power association (MRPA) and nearest base station association (NBA) schemes. Then the link and network energy efficiencies are proposed to characterize the mean spectrum efficiency per unit power consumption for a BS and the mean area spectrum efficiency for a HetNet, respectively. All the tight bounds on the green coverage probability, link and network energy efficiencies for the GCA, MRPA and NBA schemes are found. They are theoretically shown to pose the fundamental maximum limits on the link and network energy efficiencies achieved by any other cell association schemes and such a fact is validated by numerical results as well.

Includes members:
  Member "energy efficient cell activation user association and spectrum allocation in heterogeneous networks":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "reinforcement learning based vehicle cell association algorithm for highly mobile millimeter wave communication")
  Member "random cell association and void probability in poisson distributed cellular networks":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "mmwave uav networks with multi cell association performance limit and optimization")
  Member "optimal base station deployment for small cell networks with energy efficient power control":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "delay optimal biased user association in heterogeneous networks")
  Member "optimal cell load and throughput in green small cell networks with generalized cell association":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "mmwave uav networks with multi cell association performance limit and optimization")
  Member "throughput and energy efficiency analysis of small cell networks with multi antenna base stations":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "enhancing physical layer security of random caching in large scale multi antenna heterogeneous wireless networks")
  Member "energy efficiency evaluation of cellular networks based on spatial distributions of traffic load and power consumption":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "an actor critic based uav bss deploymentmethod for dynamic environments")
  Member "joint resource partitioning and offloading in heterogeneous cellular networks":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "millimeter wave integrated access and backhaul in 5g performance analysis and design insights")
  Member "offloading in heterogeneous networks modeling analysis and design insights":
    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)