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: "the topology of wireless communication"
  Abstract: In this paper we study the topological properties of wireless communication maps and their usability in algorithmic design. We consider the SINR model, which compares the received power of a signal at a receiver against the sum of strengths of other interfering signals plus background noise. To describe the behavior of a multi-station network, we use the convenient representation of a \emph{reception map}. In the SINR model, the resulting \emph{SINR diagram} partitions the plane into reception zones, one per station, and the complementary region of the plane where no station can be heard. We consider the general case where transmission energies are arbitrary (or non-uniform). Under that setting, the reception zones are not necessarily convex or even connected. This poses the algorithmic challenge of designing efficient point location techniques as well as the theoretical challenge of understanding the geometry of SINR diagrams. We achieve several results in both directions. We establish a form of weaker convexity in the case where stations are aligned on a line. In addition, one of our key results concerns the behavior of a $(d+1)$-dimensional map. Specifically, although the $d$-dimensional map might be highly fractured, drawing the map in one dimension higher "heals" the zones, which become connected. In addition, as a step toward establishing a weaker form of convexity for the $d$-dimensional map, we study the interference function and show that it satisfies the maximum principle. Finally, we turn to consider algorithmic applications, and propose a new variant of approximate point location.

Connected through hyperedge HE-1 (induced by source paper "resolving sinr queries in a dynamic setting"):
  with members:
    - "dynamic geometric data structures via shallow cuttings"
    - "dynamic planar voronoi diagrams for general distance functions and their algorithmic applications"
    - "batched point location in sinr diagrams via algebraic tools"
    - "approximating minimization diagrams and generalized proximity search"
    - "sinr diagram with interference cancellation"

Connected through hyperedge HE-2 (induced by source paper "batched point location in sinr diagrams via algebraic tools"):
  with members:
    - "approximating minimization diagrams and generalized proximity search"
    - "sinr diagram with interference cancellation"
    - "computing the distance between piecewise linear bivariate functions"
    - "wireless capacity with oblivious power in general metrics"
    - "a constant factor approximation for wireless capacity maximization with power control in the sinr model"
    - "wireless scheduling with power control"
    - "fast multipoint evaluation of bivariate polynomials"

Connected through hyperedge HE-3 (induced by source paper "braess s paradox in wireless networks the danger of improved technology"):
  with members:
    - "sinr diagram with interference cancellation"
    - "wireless connectivity and capacity"
    - "a constant factor approximation for wireless capacity maximization with power control in the sinr model"
    - "on a game theoretic approach to capacity maximization in wireless networks"
    - "sinr diagrams towards algorithmically usable sinr models of wireless networks"
    - "gaussian interference channel capacity to within one bit"

Connected through hyperedge HE-4 (induced by source paper "sinr diagram with interference cancellation"):
  with members:
    - "open loop spatial multiplexing and diversity communications in ad hoc networks"
    - "sinr diagrams towards algorithmically usable sinr models of wireless networks"
    - "gaussian interference channel capacity to within one bit"
    - "hierarchical cooperation achieves optimal capacity scaling in ad hoc networks"

Connected through hyperedge HE-5 (induced by source paper "generalized perron frobenius theorem for nonsquare matrices"):
  with members:
    - "sinr diagram with interference cancellation"

Connected through hyperedge HE-6 (induced by source paper "the power of non uniform wireless power"):
  with members:
    - "approximation algorithms for wireless link scheduling with flexible data rates"
    - "distributed connectivity of wireless networks"
    - "dynamic packet scheduling in wireless networks"
    - "wireless network stability in the sinr model"
    - "on the problem of wireless scheduling with linear power levels"
    - "nearly optimal bounds for distributed wireless scheduling in the sinr model"
    - "secondary spectrum auctions for symmetric and submodular bidders"
    - "wireless connectivity and capacity"

Connected through hyperedge HE-7 (induced by source paper "near optimal distributed scheduling algorithms for regular wireless sensor networks"):
  with members:
    - "nearly optimal bounds for distributed wireless scheduling in the sinr model"

Connected through hyperedge HE-8 (induced by source paper "wireless capacity with arbitrary gain matrix"):
  with members:
    - "approximation algorithms for wireless link scheduling with flexible data rates"
    - "nearly optimal bounds for distributed wireless scheduling in the sinr model"
    - "wireless capacity with oblivious power in general metrics"
    - "a constant factor approximation for wireless capacity maximization with power control in the sinr model"
    - "approximation algorithms for secondary spectrum auctions"
    - "coloring k colorable graphs using relatively small palettes"
    - "approximate graph coloring by semidefinite programming"

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.DS(Data Structures and Algorithms)