human: Given a node-centered hypergraph: <hypergraph>, where nodes represent papers and hyperedges represent sets of papers co-cited by a source paper.

Details of the hypergraph:
Center node: "coalitional game theory for communication networks a tutorial"
  Abstract: Game theoretical techniques have recently become prevalent in many engineering applications, notably in communications. With the emergence of cooperation as a new communication paradigm, and the need for self-organizing, decentralized, and autonomic networks, it has become imperative to seek suitable game theoretical tools that allow to analyze and study the behavior and interactions of the nodes in future communication networks. In this context, this tutorial introduces the concepts of cooperative game theory, namely coalitional games, and their potential applications in communication and wireless networks. For this purpose, we classify coalitional games into three categories: Canonical coalitional games, coalition formation games, and coalitional graph games. This new classification represents an application-oriented approach for understanding and analyzing coalitional games. For each class of coalitional games, we present the fundamental components, introduce the key properties, mathematical techniques, and solution concepts, and describe the methodologies for applying these games in several applications drawn from the state-of-the-art research in communications. In a nutshell, this article constitutes a unified treatment of coalitional game theory tailored to the demands of communications and network engineers.

Connected through hyperedge HE-1 (induced by source paper "coalition formation game for delay reduction in instantly decodable network coding assisted d2d communications"):
  with members:
    - "data dissemination using instantly decodable binary codes in fog radio access networks"
    - "instantly decodable network coding for real time scalable video broadcast over wireless networks"
    - "a game theoretic framework for decentralized cooperative data exchange using network coding"
    - "a survey on device to device communication in cellular networks"
    - "delay reduction in multi hop device to device communication using network coding"
    - "completion time reduction in instantly decodable network coding through decoding delay control"
    - "a game theoretic approach to minimize the completion time of network coded cooperative data exchange"
    - "what will 5g be"

Connected through hyperedge HE-2 (induced by source paper "solutions of partition function based tu games for cooperative communication networking"):
  with members:
    - "the geometric lattice of embedded subsets"
    - "coalitional games in partition form for joint spectrum sensing and access in cognitive radio networks"
    - "coalition formation games for collaborative spectrum sensing"
    - "the lattice of embedded subsets"

Connected through hyperedge HE-3 (induced by source paper "toward intelligent network optimization in wireless networking an auto learning framework"):
  with members:
    - "cognitive lpwan towards intelligent wireless services in hybrid low power wide area networks"
    - "machine learning for networking workflow advances and opportunities"
    - "massive mimo and small cells improving energy efficiency by optimal soft cell coordination"

Connected through hyperedge HE-4 (induced by source paper "socially trusted collaborative edge computing in ultra dense networks"):
  with members:
    - "online learning for offloading and autoscaling in energy harvesting mobile edge computing"
    - "a survey on mobile edge computing the communication perspective"
    - "online learning for offloading and autoscaling in renewable powered mobile edge computing"
    - "a cooperative scheduling scheme of local cloud and internet cloud for delay aware mobile cloud computing"
    - "what will 5g be"
    - "optimization of radio and computational resources for energy efficiency in latency constrained application offloading"
    - "coalitional games with overlapping coalitions for interference management in small cell networks"
    - "coalition formation games for collaborative spectrum sensing"

Connected through hyperedge HE-5 (induced by source paper "collaborative smartphone sensing using overlapping coalition formation games"):
  with members:
    - "a layered coalitional game framework of wireless relay network"
    - "coalitional games with overlapping coalitions for interference management in small cell networks"
    - "coalition formation games for collaborative spectrum sensing"
    - "cooperative games with overlapping coalitions"
    - "a generic approach to coalition formation"

Connected through hyperedge HE-6 (induced by source paper "distributed long term base station clustering in cellular networks using coalition formation"):
  with members:
    - "adaptive pilot clustering in heterogeneous massive mimo networks"
    - "globally optimal base station clustering in interference alignment based multicell networks"
    - "cooperative base station coloring for pair wise multi cell coordination"
    - "overhead aware distributed csi selection in the mimo interference channel"
    - "interference alignment aided base station clustering using coalition formation"
    - "what will 5g be"
    - "on the feasibility of linear interference alignment for mimo interference broadcast channels with constant coefficients"
    - "coalitional games in partition form for joint spectrum sensing and access in cognitive radio networks"

Connected through hyperedge HE-7 (induced by source paper "adaptive pilot clustering in heterogeneous massive mimo networks"):
  with members:
    - "pilot clustering in asymmetric massive mimo networks"
    - "massive mimo with non ideal arbitrary arrays hardware scaling laws and circuit aware design"
    - "coalitional games in miso interference channels epsilon core and coalition structure stable set"
    - "blind pilot decontamination"
    - "massive mimo for maximal spectral efficiency how many users and pilots should be allocated"
    - "scaling up mimo opportunities and challenges with very large arrays"
    - "a coordinated approach to channel estimation in large scale multiple antenna systems"
    - "coalitional games in partition form for joint spectrum sensing and access in cognitive radio networks"

Connected through hyperedge HE-8 (induced by source paper "network resource sharing games with instantaneous reciprocity"):
  with members:
    - "asymptotically optimal distributed channel allocation a competitive game theoretic approach"
    - "a comprehensive survey of potential game approaches to wireless networks"
    - "coordination protocol for inter operator spectrum sharing in co primary 5g small cell networks"

Question: Please tell me which class the center node 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)