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 "distributed coalition formation games for secure wireless transmission"):
  Abstract: Cooperation among wireless nodes has been recently proposed for improving the physical layer (PHY) security of wireless transmission in the presence of multiple eavesdroppers. While existing PHY security literature answered the question ``what are the link-level secrecy rate gains from cooperation?'', this paper attempts to answer the question of ``how to achieve those gains in a practical decentralized wireless network and in the presence of a cost for information exchange?''. For this purpose, we model the PHY security cooperation problem as a coalitional game with non-transferable utility and propose a distributed algorithm for coalition formation. Through the proposed algorithm, the wireless users can cooperate and self-organize into disjoint independent coalitions, while maximizing their secrecy rate taking into account the security costs during information exchange. We analyze the resulting coalitional structures for both decode-and-forward and amplify-and-forward cooperation and study how the users can adapt the network topology to environmental changes such as mobility. Through simulations, we assess the performance of the proposed algorithm and show that, by coalition formation using decode-and-forward, the average secrecy rate per user is increased of up to 25.3 % and 24.4 % (for a network with 45 users) relative to the non-cooperative and amplify-and-forward cases, respectively.

Includes members:
  Member "physical layer security coalitional games for distributed cooperation":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "secure multicast communications with private jammers")
  Member "coalitional game theory for communication networks a tutorial":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "coalition formation game for delay reduction in instantly decodable network coding assisted d2d communications")
  Member "a distributed merge and split algorithm for fair cooperation in wireless networks":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "online knapsack problem and budgeted truthful bipartite matching")
  Member "a generic approach to coalition formation":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "coalitional game framework for content distribution using device to device communication")

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)