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: "a note on uniform power connectivity in the sinr model"
  Abstract: In this paper we study the connectivity problem for wireless networks under the Signal to Interference plus Noise Ratio (SINR) model. Given a set of radio transmitters distributed in some area, we seek to build a directed strongly connected communication graph, and compute an edge coloring of this graph such that the transmitter-receiver pairs in each color class can communicate simultaneously. Depending on the interference model, more or less colors, corresponding to the number of frequencies or time slots, are necessary. We consider the SINR model that compares the received power of a signal at a receiver to the sum of the strength of other signals plus ambient noise . The strength of a signal is assumed to fade polynomially with the distance from the sender, depending on the so-called path-loss exponent $\alpha$. #R##N#We show that, when all transmitters use the same power, the number of colors needed is constant in one-dimensional grids if $\alpha>1$ as well as in two-dimensional grids if $\alpha>2$. For smaller path-loss exponents and two-dimensional grids we prove upper and lower bounds in the order of $\mathcal{O}(\log n)$ and $\Omega(\log n/\log\log n)$ for $\alpha=2$ and $\Theta(n^{2/\alpha-1})$ for $\alpha<2$ respectively. If nodes are distributed uniformly at random on the interval $[0,1]$, a \emph{regular} coloring of $\mathcal{O}(\log n)$ colors guarantees connectivity, while $\Omega(\log \log n)$ colors are required for any coloring.

Connected through hyperedge HE-1 (induced by source paper "deterministic protocols in the sinr model without knowledge of coordinates"):
  with members:
    - "achieving dilution without knowledge of coordinates in the sinr model"
    - "deterministic backbone creation in an sinr network without knowledge of location"
    - "multi broadcasting under the sinr model"
    - "distributed communication in bare bones wireless networks"
    - "almost optimal cover free families"
    - "beyond geometry towards fully realistic wireless models"
    - "on the impact of geometry on ad hoc communication in wireless networks"
    - "distributed deterministic broadcasting in uniform power ad hoc wireless networks"

Connected through hyperedge HE-2 (induced by source paper "on the impact of geometry on ad hoc communication in wireless networks"):
  with members:
    - "randomized broadcast in radio networks with collision detection"
    - "distributed deterministic broadcasting in uniform power ad hoc wireless networks"
    - "dynamic packet scheduling in wireless networks"
    - "towards tight bounds for local broadcasting"
    - "nearly optimal bounds for distributed wireless scheduling in the sinr model"
    - "wireless connectivity and capacity"

Connected through hyperedge HE-3 (induced by source paper "arbitrary transmission power in the sinr model local broadcasting coloring and mis"):
  with members:
    - "towards tight bounds for local broadcasting"
    - "wireless connectivity and capacity"

Connected through hyperedge HE-4 (induced by source paper "a fast distributed approximation algorithm for minimum spanning trees in the sinr model"):
  with members:
    - "nearly optimal bounds for distributed wireless scheduling in the sinr model"
    - "a constant factor approximation for wireless capacity maximization with power control in the sinr model"

Connected through hyperedge HE-5 (induced by source paper "distributed backbone structure for deterministic algorithms in the sinr model of wireless networks"):
  with members:
    - "distributed deterministic broadcasting in wireless networks under the sinr model"
    - "a constant factor approximation for wireless capacity maximization with power control in the sinr model"

Connected through hyperedge HE-6 (induced by source paper "percolation and connectivity on the signal to interference ratio graph"):
  with members:
    - "directed percolation in wireless networks with interference and noise"

Connected through hyperedge HE-7 (induced by source paper "distributed deterministic broadcasting in wireless networks of weak devices under the sinr model"):
  with members:
    - "sinr diagrams towards algorithmically usable sinr models of wireless networks"

Connected through hyperedge HE-8 (induced by source paper "on the problem of wireless scheduling with linear power levels"):
  with members:
    - "nearly optimal bounds for distributed wireless scheduling in the sinr model"
    - "algorithms for scheduling with power control in wireless networks"
    - "algorithms for scheduling with power control in wireless networks"
    - "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"

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.DM(Discrete Mathematics)