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 "general spectrum sensing in cognitive radio networks"):
  Abstract: The successful operation of cognitive radio (CR) between CR transmitter and CR receiver (CR link) relies on reliable spectrum sensing. To network CRs requires spectrum sensing at CR transmitter and further information regarding the spectrum availability at CR receiver. Redefining the spectrum sensing along with statistical inference suitable for cognitive radio networks (CRN), we mathematically derive conditions to allow CR transmitter forwarding packets to CR receiver under guaranteed outage probability, and prove that the correlation of localized spectrum availability between a cooperative node and CR receiver determines effectiveness of the cooperative scheme. Applying our novel mathematical model to potential hidden terminals in CRN, we illustrate that the allowable transmission region of a CR, defined as neighborhood, is no longer circular shape even in a pure path loss channel model. This results in asymmetric CR links to make bidirectional links generally inappropriate in CRN, though this challenge can be alleviated by cooperative sensing. Therefore, spectrum sensing capability determines CRN topology. For multiple cooperative nodes, to fully utilize spectrum availability, the selection methodology of cooperative nodes is developed due to limited overhead of information exchange. Defining reliability as information of spectrum availability at CR receiver provided by a cooperative node and by applying neighborhood area, we can compare sensing capability of cooperative nodes from both link and network perspectives. In addition, due to lack of centralized coordination in dynamic CRN, CRs can only acquire local and partial information within limited sensing duration, robust spectrum sensing is therefore proposed. Limits of cooperative schemes and their impacts on network operation are also derived.

Includes members:
  Member "optimal multiband joint detection for spectrum sensing in cognitive radio networks":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "optimization of the belief propagation algorithm for distributed detection by linear data fusion techniques")
  Member "spectrum sensing algorithms for cognitive radio based on statistical covariances":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "unified analysis of cooperative spectrum sensing over composite and generalized fading channels")

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)