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 "d2d multicast in underlay cellular networks with exclusion zones"):
  Abstract: Underlay device-to-device (D2D) multicast communication has potential to improve performance of cellular networks. However, co-channel interference among cellular users (CUs) and D2D multicast groups (MGs) limits the gains of such communication. Allowing the CUs to have exclusion zones around them where no receiver of any MG can exist, is a realistic and pragmatic approach to reduce the co-channel interference of cellular transmission on D2D multicast reception. #R##N#We use a stochastic geometry based approach to model this scenario. Specifically, we model the locations of CUs and D2D MG receivers with homogeneous Poisson Point Process (PPP), and Poisson Hole Process (PHP), respectively. We formulate the network sum throughput maximization problem in terms of a joint MG channel and power allocation problem with constraints on cellular and MG users maximum transmit and acceptable quality of service. #R##N#We establish that the MG channel allocation problem has computational complexity that is exponential in both, the number of MGs and the number of available cellular channels. Then, we decompose this problem into two subproblems: subset selection problem and subset channel assignment problem. Based on observations and insights obtained from numerical analysis of the optimal solution of the subset selection problem in wide variety of scenarios, we propose a computationally efficient scheme that achieves almost optimal performance for the subset selection problem. We further provide a computationally efficient algorithm that achieves almost optimal performance for the subset channel assignment problem. Finally, combining these two schemes, we provide a computationally efficient and almost optimal scheme to solve the MG channel allocation problem, and various results and insights on the variation of the optimal system performance with respect to different system parameters.

Includes members:
  Member "optimal resource allocation in multicast device to device communications underlaying lte networks":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "energy efficient power and channel allocation in underlay device to multi device communications")
  Member "a stochastic geometric analysis of device to device communications operating over generalized fading channels":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "uav to uav communications in cellular networks")
  Member "poisson hole process theory and applications to wireless networks":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "stochastic geometry based uplink analysis of massive mimo systems with fractional pilot reuse")
  Member "modeling cellular networks with full duplex d2d communication a stochastic geometry approach":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "self organized scheduling request for uplink 5g networks a d2d clustering approach")
  Member "an analytical framework for device to device communication in cellular networks":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "uav to uav communications in cellular networks")
  Member "operational region of d2d communications for enhancing cellular network performance":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "cross mode interference characterization in cellular networks with voronoi guard regions")
  Member "device to device communication underlaying a finite cellular network region":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "coded caching clusters with device to device communications")
  Member "spectrum sharing for device to device communication in cellular networks":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "sense and predict harnessing spatial interference correlation for cognitive radio 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.NI(Networking and Internet Architecture)