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 "small cell offloading through cooperative communication in software defined heterogeneous networks"):
  Abstract: To meet the ever-growing demand for a higher communicating rate and better communication quality, more and more small cells are overlaid under the macro base station (MBS) tier, thus forming the heterogeneous networks. Small cells can ease the load pressure of MBS but lack of the guarantee of performance. On the other hand, cooperation draws more and more attention because of the great potential of small cell densification. Some technologies matured in wired network can also be applied to cellular networks, such as software-defined networking (SDN). SDN helps simplify the structure of multi-tier networks. In addition, it is more reasonable for the SDN controller to implement cell coordination. In this paper, we propose a method to offload users from MBSs through small cell cooperation in heterogeneous networks. Association probability is the main indicator of offloading. By using the tools from stochastic geometry, we then obtain the coverage probabilities when users are associated with different types of BSs. All the cell association and cooperation are conducted by the SDN controller. Then, on this basis, we compare the overall coverage probabilities, achievable rate, and energy efficiency with and without cooperation. Numerical results show that small cell cooperation can offload more users from MBS tier. It can also increase the system’s coverage performance. As small cells become denser, cooperation can bring more gains to the energy efficiency of the network.

Includes members:
  Member "spatial spectrum and energy efficiency of random cellular networks":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "spatio temporal modeling for massive and sporadic access")
  Member "user mobility evaluation for 5g small cell networks based on individual mobility model":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "spatio temporal modeling for massive and sporadic access")
  Member "5g ultra dense cellular networks":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "reinforcement learning based cooperative coded caching under dynamic popularities in ultra dense networks")
  Member "a stochastic geometry framework for analyzing pairwise cooperative cellular networks":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "area spectral efficiency and sinr scaling laws in multi antenna cellular networks")
  Member "5g wireless backhaul networks challenges and research advances":
    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 "software defined networking a comprehensive survey":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "5g network slicing using sdn and nfv a survey of taxonomy architectures and future challenges")
  Member "a tractable model for noncoherent joint transmission base station cooperation":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "edge computing enabled cell free massive mimo systems")
  Member "analysis of non coherent joint transmission cooperation in heterogeneous cellular networks":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "base station cooperation in millimeter wave cellular networks performance enhancement of cell edge users")

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.NI(Networking and Internet Architecture)