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: "optimal relay location and power allocation for low snr broadcast relay channels"
  Abstract: We consider the broadcast relay channel (BRC), where a single source transmits to multiple destinations with the help of a relay, in the limit of a large bandwidth. We address the problem of optimal relay positioning and power allocations at source and relay, to maximize the multicast rate from source to all destinations. To solve such a network planning problem, we develop a three-faceted approach based on an underlying information theoretic model, computational geometric aspects, and network optimization tools. Firstly, assuming superposition coding and frequency division between the source and the relay, the information theoretic framework yields a hypergraph model of the wideband BRC, which captures the dependency of achievable rate-tuples on the network topology. As the relay position varies, so does the set of hyperarcs constituting the hypergraph, rendering the combinatorial nature of optimization problem. We show that the convex hull C of all nodes in the 2-D plane can be divided into disjoint regions corresponding to distinct hyperarcs sets. These sets are obtained by superimposing all k-th order Voronoi tessellation of C. We propose an easy and efficient algorithm to compute all hyperarc sets, and prove they are polynomially bounded. Using the switched hypergraph approach, we model the original problem as a continuous yet non-convex network optimization program. Ultimately, availing on the techniques of geometric programming and $p$-norm surrogate approximation, we derive a good convex approximation. We provide a detailed characterization of the problem for collinearly located destinations, and then give a generalization for arbitrarily located destinations. Finally, we show strong gains for the optimal relay positioning compared to seemingly interesting positions.

Connected through hyperedge HE-1 (induced by source paper "deploy as you go wireless relay placement an optimal sequential decision approach using the multi relay channel model"):
  with members:
    - "measurement based impromptu deployment of a multi hop wireless relay network"
    - "optimal capacity relay node placement in a multi hop wireless network on a line"
    - "a robust relay placement framework for 60ghz mmwave wireless personal area networks"
    - "wireless network information flow a deterministic approach"

Connected through hyperedge HE-2 (induced by source paper "quasi concavity for gaussian multicast relay channels"):
  with members:
    - "reducibility of joint relay positioning and flow optimization problem"
    - "on the geometry of wireless network multicast in 2 d"
    - "on maximizing coverage in gaussian relay channels"

Connected through hyperedge HE-3 (induced by source paper "reducibility of joint relay positioning and flow optimization problem"):
  with members:
    - "on the geometry of wireless network multicast in 2 d"
    - "on maximizing coverage in gaussian relay channels"

Connected through hyperedge HE-4 (induced by source paper "optimal capacity relay node placement in a multi hop wireless network on a line"):
  with members:
    - "wireless network information flow a deterministic approach"

Connected through hyperedge HE-5 (induced by source paper "on the geometry of wireless network multicast in 2 d"):
  with members:
    - "on optimizing low snr wireless networks using network coding"
    - "on the non coherent wideband multipath fading relay channel"

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)