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 "operational region of d2d communications for enhancing cellular network performance"):
  Abstract: An important enabler towards the successful deployment of any new element/feature to the cellular network is the investigation and characterization of the operational conditions where its introduction will enhance performance. Although there has been significant research activity on the potential of device-to-device (D2D) communications, there are currently no clear indications of whether D2D communications are actually able to provide benefits for a  wide range  of operational conditions, thus justifying their introduction to the system. This paper attempts to fill this gap by taking a stochastic geometry approach on characterizing the set (region) of operational conditions for which D2D communications enhance performance in terms of average user rate. For the practically interesting case of a heavy-loaded network, the operational region is provided in closed form as a function of a variety of parameters such as maximum D2D link distances and user densities, reflecting a wide range of operational conditions (points). It is shown that, under the appropriate deployment scheme, D2D communications can indeed be beneficial not only for the usually considered regime of “proximal communications” but to a wide range of operational conditions that include D2D link distances comparable to the distance to the cellular access point and considerably large user densities.

Includes members:
  Member "an analytical framework for device to device communication in cellular networks":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "uav to uav communications in cellular networks")
  Member "a survey on device to device communication in cellular networks":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "simultaneous energy harvesting and information transmission in a mimo full duplex system a machine learning based design")
  Member "spectrum sharing for device to device communication in cellular networks":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "sense and predict harnessing spatial interference correlation for cognitive radio networks")
  Member "managing interference correlation through random medium access":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "spatio temporal modeling for massive and sporadic access")
  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 "resource optimization in device to device cellular systems using time frequency hopping":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "interference prediction in wireless networks stochastic geometry meets recursive filtering")
  Member "power control for d2d underlaid cellular networks modeling algorithms and analysis":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "analysis of d2d communication with rf energy harvesting and interference management")
  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)