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 "cooperative spectrum sharing between d2d users and edge users a matching theory perspective"):
  Abstract: The device-to-device (D2D) communication theoretically provides both the cellular traffic offloading and convenient content delivery directly among proximity users. However, in practice, no matter in underlay or overlay mode, the employment of D2D may impair the performance of the cellular links. Therefore, it is important to design a spectrum sharing scheme, under which the performance of both links can be improved simultaneously. In this paper, we consider the cell-edge user (CEU) scenario, where both sides have the demand to improve the quality of experience or service. Therefore, CEUs and D2D users both have intentions to form pairs, namely, CEU-D2D pairs, to cooperate mutually. Different from the conventional equilibrium point evaluation, the stable matching between D2D users and CEUs are formulated under matching theory framework instead. For each CEU-D2D pair, a two-stage pricing-based Stackelberg game is modeled to describe the willingness to cooperate, where the win-win goal is reached finally.

Includes members:
  Member "a survey on device to device communication in cellular networks":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "simultaneous energy harvesting and information transmission in a mimo full duplex system a machine learning based design")
  Member "matching theory for future wireless networks fundamentals and applications":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "multi agent meta reinforcement learning for self powered and sustainable edge computing systems")

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)